From 75298f5457945ba3714382586c0dbf703649ae7e Mon Sep 17 00:00:00 2001
From: cfdaily <cfdaily@gitee.com>
Date: Wed, 6 May 2026 23:13:05 +0800
Subject: [PATCH] auto-sync: 2026-05-06 23:13:05

---
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 graphify-out/graph.json                       | 136206 +++++++++++++++
 graphify-out/manifest.json                    |   1234 +
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diff --git a/graphify-out/.graphify_root b/graphify-out/.graphify_root
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+/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live
\ No newline at end of file
diff --git a/graphify-out/GRAPH_REPORT.md b/graphify-out/GRAPH_REPORT.md
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+# Graph Report - sanguo_quant_live  (2026-05-06)
+
+## Corpus Check
+- 291 files · ~180,109 words
+- Verdict: corpus is large enough that graph structure adds value.
+
+## Summary
+- 6707 nodes · 7500 edges · 556 communities (508 shown, 48 thin omitted)
+- Extraction: 97% EXTRACTED · 3% INFERRED · 0% AMBIGUOUS · INFERRED: 195 edges (avg confidence: 0.6)
+- Token cost: 0 input · 0 output
+
+## Graph Freshness
+- Built from commit: `a2efd2dd`
+- Run `git rev-parse HEAD` and compare to check if the graph is stale.
+- Run `graphify update .` after code changes (no API cost).
+
+## Community Hubs (Navigation)
+- [[_COMMUNITY_Community 0|Community 0]]
+- [[_COMMUNITY_Community 1|Community 1]]
+- [[_COMMUNITY_Community 2|Community 2]]
+- [[_COMMUNITY_Community 3|Community 3]]
+- [[_COMMUNITY_Community 4|Community 4]]
+- [[_COMMUNITY_Community 5|Community 5]]
+- [[_COMMUNITY_Community 6|Community 6]]
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+- [[_COMMUNITY_Community 439|Community 439]]
+- [[_COMMUNITY_Community 440|Community 440]]
+- [[_COMMUNITY_Community 441|Community 441]]
+- [[_COMMUNITY_Community 442|Community 442]]
+- [[_COMMUNITY_Community 443|Community 443]]
+- [[_COMMUNITY_Community 444|Community 444]]
+- [[_COMMUNITY_Community 447|Community 447]]
+- [[_COMMUNITY_Community 448|Community 448]]
+- [[_COMMUNITY_Community 449|Community 449]]
+- [[_COMMUNITY_Community 450|Community 450]]
+- [[_COMMUNITY_Community 451|Community 451]]
+- [[_COMMUNITY_Community 452|Community 452]]
+- [[_COMMUNITY_Community 453|Community 453]]
+- [[_COMMUNITY_Community 454|Community 454]]
+- [[_COMMUNITY_Community 455|Community 455]]
+- [[_COMMUNITY_Community 456|Community 456]]
+- [[_COMMUNITY_Community 457|Community 457]]
+- [[_COMMUNITY_Community 458|Community 458]]
+- [[_COMMUNITY_Community 459|Community 459]]
+- [[_COMMUNITY_Community 460|Community 460]]
+- [[_COMMUNITY_Community 461|Community 461]]
+- [[_COMMUNITY_Community 462|Community 462]]
+- [[_COMMUNITY_Community 463|Community 463]]
+- [[_COMMUNITY_Community 464|Community 464]]
+- [[_COMMUNITY_Community 465|Community 465]]
+- [[_COMMUNITY_Community 466|Community 466]]
+- [[_COMMUNITY_Community 467|Community 467]]
+- [[_COMMUNITY_Community 468|Community 468]]
+- [[_COMMUNITY_Community 469|Community 469]]
+- [[_COMMUNITY_Community 470|Community 470]]
+- [[_COMMUNITY_Community 471|Community 471]]
+- [[_COMMUNITY_Community 472|Community 472]]
+- [[_COMMUNITY_Community 473|Community 473]]
+- [[_COMMUNITY_Community 474|Community 474]]
+- [[_COMMUNITY_Community 475|Community 475]]
+- [[_COMMUNITY_Community 476|Community 476]]
+- [[_COMMUNITY_Community 477|Community 477]]
+- [[_COMMUNITY_Community 478|Community 478]]
+- [[_COMMUNITY_Community 479|Community 479]]
+- [[_COMMUNITY_Community 480|Community 480]]
+- [[_COMMUNITY_Community 481|Community 481]]
+- [[_COMMUNITY_Community 482|Community 482]]
+- [[_COMMUNITY_Community 483|Community 483]]
+- [[_COMMUNITY_Community 484|Community 484]]
+- [[_COMMUNITY_Community 485|Community 485]]
+- [[_COMMUNITY_Community 486|Community 486]]
+- [[_COMMUNITY_Community 487|Community 487]]
+- [[_COMMUNITY_Community 488|Community 488]]
+- [[_COMMUNITY_Community 489|Community 489]]
+- [[_COMMUNITY_Community 490|Community 490]]
+- [[_COMMUNITY_Community 491|Community 491]]
+- [[_COMMUNITY_Community 492|Community 492]]
+- [[_COMMUNITY_Community 493|Community 493]]
+- [[_COMMUNITY_Community 494|Community 494]]
+- [[_COMMUNITY_Community 495|Community 495]]
+- [[_COMMUNITY_Community 496|Community 496]]
+- [[_COMMUNITY_Community 497|Community 497]]
+- [[_COMMUNITY_Community 498|Community 498]]
+- [[_COMMUNITY_Community 499|Community 499]]
+- [[_COMMUNITY_Community 500|Community 500]]
+- [[_COMMUNITY_Community 501|Community 501]]
+- [[_COMMUNITY_Community 502|Community 502]]
+- [[_COMMUNITY_Community 503|Community 503]]
+- [[_COMMUNITY_Community 504|Community 504]]
+- [[_COMMUNITY_Community 505|Community 505]]
+- [[_COMMUNITY_Community 506|Community 506]]
+- [[_COMMUNITY_Community 507|Community 507]]
+- [[_COMMUNITY_Community 510|Community 510]]
+- [[_COMMUNITY_Community 511|Community 511]]
+- [[_COMMUNITY_Community 513|Community 513]]
+- [[_COMMUNITY_Community 514|Community 514]]
+- [[_COMMUNITY_Community 515|Community 515]]
+- [[_COMMUNITY_Community 519|Community 519]]
+- [[_COMMUNITY_Community 520|Community 520]]
+- [[_COMMUNITY_Community 521|Community 521]]
+- [[_COMMUNITY_Community 522|Community 522]]
+- [[_COMMUNITY_Community 523|Community 523]]
+- [[_COMMUNITY_Community 524|Community 524]]
+- [[_COMMUNITY_Community 525|Community 525]]
+- [[_COMMUNITY_Community 526|Community 526]]
+- [[_COMMUNITY_Community 527|Community 527]]
+- [[_COMMUNITY_Community 545|Community 545]]
+- [[_COMMUNITY_Community 546|Community 546]]
+- [[_COMMUNITY_Community 547|Community 547]]
+- [[_COMMUNITY_Community 548|Community 548]]
+- [[_COMMUNITY_Community 549|Community 549]]
+- [[_COMMUNITY_Community 550|Community 550]]
+- [[_COMMUNITY_Community 551|Community 551]]
+- [[_COMMUNITY_Community 552|Community 552]]
+- [[_COMMUNITY_Community 553|Community 553]]
+
+## God Nodes (most connected - your core abstractions)
+1. `添加: 加载项目上下文（优先级搜索）` - 40 edges
+2. `RealtimeRiskPanel` - 32 edges
+3. `加拿大云主机中转方案调研报告` - 32 edges
+4. `RealTimeRiskMonitor` - 26 edges
+5. `RiskController` - 25 edges
+6. `MultiFactorDynamicStrategy` - 24 edges
+7. `StockInfo` - 21 edges
+8. `PortfolioInfo` - 21 edges
+9. `EmergencyHandler` - 21 edges
+10. `ATRIndicator` - 21 edges
+
+## Surprising Connections (you probably didn't know these)
+- `BaseFactor` --uses--> `RiskController`  [INFERRED]
+  strategies/factors-dynamic-weight-timing-20260327/main_strategy_single_file.py → guanyu-risk/research/factors-strategy-risk-control-20260327/risk_control.py
+- `BaseFactor` --uses--> `PortfolioInfo`  [INFERRED]
+  strategies/factors-dynamic-weight-timing-20260327/main_strategy_single_file.py → guanyu-risk/research/factors-strategy-risk-control-20260327/risk_control.py
+- `PEFactor` --uses--> `RiskController`  [INFERRED]
+  strategies/factors-dynamic-weight-timing-20260327/main_strategy_single_file.py → guanyu-risk/research/factors-strategy-risk-control-20260327/risk_control.py
+- `PEFactor` --uses--> `PortfolioInfo`  [INFERRED]
+  strategies/factors-dynamic-weight-timing-20260327/main_strategy_single_file.py → guanyu-risk/research/factors-strategy-risk-control-20260327/risk_control.py
+- `PBFactor` --uses--> `RiskController`  [INFERRED]
+  strategies/factors-dynamic-weight-timing-20260327/main_strategy_single_file.py → guanyu-risk/research/factors-strategy-risk-control-20260327/risk_control.py
+
+## Communities (556 total, 48 thin omitted)
+
+### Community 0 - "Community 0"
+Cohesion: 0.05
+Nodes (34): BaseFactor, BaseFactor, calculate(), 因子标准化（中位数去极值 + 标准化）         参数:             factor_values: 原始因子值         返回:, 因子横截面标准化（每个交易日rank 0-1）         参数:             factor_values: 标准化后的因子值，多层index, 完整因子计算流程: 计算 -> 标准化 -> rank         参数:             df: 输入数据         返回:, Momentum1MFactor, Momentum3MFactor (+26 more)
+
+### Community 1 - "Community 1"
+Cohesion: 0.04
+Nodes (47): 📋 庞统 - 价值投资调研详细工作计划, 📅 详细时间安排, 🔧 所需资源清单, **数据资源**：, **技术资源**：, **协作需求**：, 📊 每日汇报机制, **每日汇报内容**： (+39 more)
+
+### Community 2 - "Community 2"
+Cohesion: 0.06
+Nodes (21): FinanceMonitor, FiveDimensionRiskAssessment, InstitutionalMonitor, InternationalLinkageMonitor, NewsRiskMonitor, NewsRiskResult, NewsSentiment, PriceVolumeMonitor (+13 more)
+
+### Community 3 - "Community 3"
+Cohesion: 0.06
+Nodes (21): FinanceMonitor, FiveDimensionRiskAssessment, InstitutionalMonitor, InternationalLinkageMonitor, NewsRiskMonitor, NewsRiskResult, NewsSentiment, PriceVolumeMonitor (+13 more)
+
+### Community 4 - "Community 4"
+Cohesion: 0.06
+Nodes (21): FinanceMonitor, FiveDimensionRiskAssessment, InstitutionalMonitor, InternationalLinkageMonitor, NewsRiskMonitor, NewsRiskResult, NewsSentiment, PriceVolumeMonitor (+13 more)
+
+### Community 5 - "Community 5"
+Cohesion: 0.04
+Nodes (46): **🎯 调研概述**, **1. 基本面分析选股方法**, **调研时间**, **1.1 财务报表深度分析**, **1.2 行业地位和竞争优势分析**, **1. 历史回测方法**, **1.3 管理层和公司治理分析**, **1. 数据获取和处理** (+38 more)
+
+### Community 6 - "Community 6"
+Cohesion: 0.04
+Nodes (45): 🎯 管理原则, **第1天任务**, **仓库地址**, 📊 代码管理规范, **代码质量要求**, **文档要求**, **数据管理**, 🚀 日常操作指南 (+37 more)
+
+### Community 7 - "Community 7"
+Cohesion: 0.04
+Nodes (44): 📋 方案概述, 1. 初始化消息管理器, 🎨 技术方案, 架构设计, 🚀 快速开始, 第一阶段：基础实现（1周）, 第三阶段：部署上线（1周）, 1. 扩展vnpy EventEngine (+36 more)
+
+### Community 8 - "Community 8"
+Cohesion: 0.04
+Nodes (44): 数据工程任务完成报告, 短期执行（1周内）, 一、任务概述, 11.1 任务完成情况, 11.2 总体评价, 11.3 风险评估, 11.4 结论, 四、代码质量 (+36 more)
+
+### Community 9 - "Community 9"
+Cohesion: 0.04
+Nodes (44): 📊 **价值投资领域调研报告**, **1. 基本面因子有效性研究**, **📊 预期成果**, **⏰ 时间节点**, **🎯 调研目标**, **📅 关键时间节点**, **📤 提交要求**, **🚀 立即行动** (+36 more)
+
+### Community 10 - "Community 10"
+Cohesion: 0.05
+Nodes (43): 🎯 调研目标, 1. 计算资源优化, 网络服务, 🏗️ 架构设计, 开发-测试-生产环境架构, 💰 成本估算, 生产环境月度成本估算（推荐配置）, 📦 已完成的成果 (+35 more)
+
+### Community 11 - "Community 11"
+Cohesion: 0.05
+Nodes (43): **📅 调研时间安排**, **深度研究阶段（00:00 - 06:00）**, **总结完善阶段（06:00 - 10:00）**, **1. 传统选股方法创新研究**, **📊 实证研究设计**, **🎯 创新点和特色**, **🚀 实施保障**, **1.1 基本面分析创新** (+35 more)
+
+### Community 12 - "Community 12"
+Cohesion: 0.05
+Nodes (41): 配置管理目录, 1. 配置层级结构, 2. 配置文件规范, 2.1 全局配置文件 (`global_config.yaml`), 2.1 YAML配置文件示例, 2.2 数据配置, 2.2 突破配置文件 (`breakout_config.yaml`), 2.3 策略配置 (+33 more)
+
+### Community 13 - "Community 13"
+Cohesion: 0.08
+Nodes (27): ATRIndicator, calculate_atr(), calculate_tr(), _calculate_tr_numpy(), ATR (Average True Range) 指标计算工具 支持SMA和EMA两种计算方式  Author: 张飞 翼德 Date: 2026-04-17, 计算ATR指标                  Parameters:             high: 最高价序列             low: 最低, 使用EMA计算ATR，Wilder平滑方法, Pandas版本EMA-ATR计算，使用Wilder平滑 (+19 more)
+
+### Community 14 - "Community 14"
+Cohesion: 0.05
+Nodes (41): 📢 三国量化实战项目 - 正式团队通知, **质量机制**, **平台机制**, 🚀 **立即行动项**, **所有人必须完成**, **各领域重点**, 📅 项目阶段, 📊 **交付标准** (+33 more)
+
+### Community 15 - "Community 15"
+Cohesion: 0.05
+Nodes (42): 第七部分：基础设施验证（姜维+张飞）, 6.10 系统结论, 6.1.1 核心数据依赖 ✅, 6.1.2 量化框架依赖 ✅, 6.1.3 其他关键依赖, 6.1 Python环境检查, 6.2.1 vn.py核心模块 ✅, 6.2.2 sanguo核心模块 ✅ (+34 more)
+
+### Community 16 - "Community 16"
+Cohesion: 0.05
+Nodes (41): 目录, 消息清空技巧, 投资辩论（双人循环：多头 ↔ 空头）, 128GB 统一内存（满血体验）, 风险辩论（三人循环：激进 → 保守 → 中立）, 辩论机制总结, 四、优缺点分析, 优点 ✅ (+33 more)
+
+### Community 17 - "Community 17"
+Cohesion: 0.05
+Nodes (41): 目录, 1. 我们已有基础, 四、通信共享信息实现, 目录结构, 通信机制, 五、提示词设计总结, 核心预置命令/提示词, 阶段分工提示词 (+33 more)
+
+### Community 18 - "Community 18"
+Cohesion: 0.08
+Nodes (18): AkshareToVnpyAdapter, main(), 获取A股全市场股票列表          Args:             max_retries: 最大重试次数             retry_del, 解析股票代码，返回symbol和exchange          Args:             code: 股票代码，如 "000001" 或 "600, 获取单只股票历史K线数据          Args:             code: 股票代码             start_date: 开始日期, 将akshare K线数据转换为vn.py格式          Args:             df: akshare K线数据DataFrame, 批量插入K线数据          Args:             bars: K线数据列表             batch_size: 批量大小, akshare数据转vn.py SQLite数据库适配器 (+10 more)
+
+### Community 19 - "Community 19"
+Cohesion: 0.05
+Nodes (40): 风险控制策略研究与设计, 1. 头寸控制策略, 1.1 单票仓位限制, 1.2 行业集中度控制, 1.3 总仓位动态调整, 1.4 杠杆限制, 2. 止损止盈策略, 2.1 固定比例止损 (+32 more)
+
+### Community 20 - "Community 20"
+Cohesion: 0.05
+Nodes (40): 2.1 代码实现与架构设计, 2.2 三种选股方法对比, 2.3 核心模块实现细节, 2.3.1 RiskProfile - 风险偏好配置, 2.3.2 ValueFilter - 价值筛选器, 2.3.3 TechnicalFilter - 技术信号过滤器, 2.3.4 PositionManager - 仓位管理器, 2.4 完整策略使用方法 (+32 more)
+
+### Community 21 - "Community 21"
+Cohesion: 0.05
+Nodes (39): 🏛️ 赵云工作区目录结构验证报告, 1. 根目录结构 ✅ 完全符合, 结构完整性评分：100/100 ✅, 职责体现评分：100/100 ✅, 🎯 赵云职责符合性验证, 📊 结构验证结果, 工作区结构职责体现 ✅, 🔍 详细检查点验证 (+31 more)
+
+### Community 22 - "Community 22"
+Cohesion: 0.05
+Nodes (40): 添加: 加载项目上下文（优先级搜索）, code:block100 (启动脚本读取这个文件，自动加载对应模型指南，不用每次输入。), code:block101 (如果当前工作目录下有项目自定义上下文，自动加载。), code:block102, code:block103, code:block104, code:block105, code:block106 (+32 more)
+
+### Community 23 - "Community 23"
+Cohesion: 0.05
+Nodes (39): 一、调研背景, 10.1 可行性结论：✅ 完全可行, 10.2 推荐方案, 10.3 操作建议, 二、可行性分析, 七、性能优化建议, 八、稳定性评估, 九、成本估算（参考） (+31 more)
+
+### Community 24 - "Community 24"
+Cohesion: 0.06
+Nodes (38): 聚宽回测优化与实盘经验调研报告, 文章1：高效使用聚宽回测平台的技巧, 任务目标, 总结与建议, 五、关键文件说明, 关键要点回顾, 主要文件, 对我们的借鉴意义 (+30 more)
+
+### Community 25 - "Community 25"
+Cohesion: 0.05
+Nodes (37): 风控实验测试结果, 1. 实验设计, 10. 代码实现, 1.1 测试数据集, 1.2 评估指标, 2. 风险度量模型对比测试, 保守型（推荐给回撤敏感）, 平衡型 (+29 more)
+
+### Community 26 - "Community 26"
+Cohesion: 0.05
+Nodes (37): 项目定位, 1. 独立任务工作流, 工作流规则, 技术架构原则, 公共知识库规则, 文件流转规则, 研发流程, 质量流程 (+29 more)
+
+### Community 27 - "Community 27"
+Cohesion: 0.05
+Nodes (37): 任务执行：赵云数据工程将军, 1. 知识库基础架构 - 已完成, ❌ 待完成的工作, 🔧 技术实现成果, 📁 知识库目录结构, 🛠️ 爬虫工具, 📈 质量保证与验证, ✅ 数据完整性检查 (+29 more)
+
+### Community 28 - "Community 28"
+Cohesion: 0.05
+Nodes (37): 三国量化交易项目 - 完整测试验证报告, 1. 各将军工作状态确认, 🎯 任务执行总结, 卫星策略1: 情绪逆向策略 (权重15%), 1. 数据质量提升, 方案1: 多因子综合评分模型, 回测方案1: 多因子综合评分模型, 回测方案2: 传统选股方法对比 (+29 more)
+
+### Community 29 - "Community 29"
+Cohesion: 0.1
+Nodes (15): BaseFactor, Momentum1MFactor, Momentum3MFactor, PBFactor, PEFactor, 板块强度因子 - 板块强度越高越好，适配结构化行情, 因子基类 - 所有因子继承此类，定义统一的因子计算接口, ROEFactor (+7 more)
+
+### Community 30 - "Community 30"
+Cohesion: 0.05
+Nodes (36): 一、当前状况分析, 四、实现方案, 五、关键技术点, 六、实施方案, 1.1 当前数据源状况, 1.2 当前架构状况, 七、风险与对策, 八、预期成果 (+28 more)
+
+### Community 31 - "Community 31"
+Cohesion: 0.05
+Nodes (36): 节点信息, 自动化脚本, 使用提供的配置脚本, 连接节点, 使用同步和执行脚本, 总结, 文件传输, 问题1：SSH连接失败 (+28 more)
+
+### Community 32 - "Community 32"
+Cohesion: 0.1
+Nodes (21): atr(), BacktestEngine, BacktestResult, bollinger_bands(), BollingerBandsStrategy, donchian_channel(), DonchianChannelStrategy, ema() (+13 more)
+
+### Community 33 - "Community 33"
+Cohesion: 0.06
+Nodes (35): 数据工程验证报告模板, 一、验证概述, 三、性能验证, 四、数据质量验证, 1.1 验证目标, 1.2 验证范围, 五、稳定性验证, 六、代码质量 (+27 more)
+
+### Community 34 - "Community 34"
+Cohesion: 0.06
+Nodes (35): 实时风险监控系统架构设计, 1. 系统架构概述, 整体分层架构, 更新流程, 2. 模块详细设计, 时间复杂度, 完整使用示例, 返回结果结构 (+27 more)
+
+### Community 35 - "Community 35"
+Cohesion: 0.08
+Nodes (18): BreakoutPreTradeFilter, BreakoutRiskController, BreakoutSingleStopLoss, BreakoutStock, PortfolioDrawdownControl, PortfolioInfo, 纯突破策略风控模块 功能： 1. 单票止损：跌破突破日最低价5% → 止损卖出 2. 单日暴跌超过7% → 强制减仓 3. 全仓回撤控制：整体回撤超过10%降仓, 初始化         :param min_avg_volume: 最小日均成交额（亿），默认5000万 (+10 more)
+
+### Community 36 - "Community 36"
+Cohesion: 0.08
+Nodes (18): AKShareDataAdapter, main(), 获取股票日线数据                  Args:             symbol: 股票代码（如：000001）             s, 生成模拟股票数据（当akshare不可用时）                  Args:             symbol: 股票代码, 转换为vnPy格式                  Args:             df: 原始数据DataFrame             data_, 获取指数日线数据                  Args:             index_symbol: 指数代码（如：000001.SH）, 初始化适配器                  Args:             config_path: 配置文件路径, 生成模拟指数数据                  Args:             index_symbol: 指数代码             start (+10 more)
+
+### Community 37 - "Community 37"
+Cohesion: 0.06
+Nodes (34): 🛡️ 风险管理领域 - 关羽, 第1周重点, 🔧 所需技能和工具, 核心技能, 技术工具, 数据需求, 总体目标, 🤝 协作机制 (+26 more)
+
+### Community 38 - "Community 38"
+Cohesion: 0.07
+Nodes (33): 回测系统目录, 1. 系统架构设计, 2. 回测参数配置, 2.1 基本参数, 2.2 策略参数, 🏗️ 回测系统架构, ✅ 已完成, 🔄 进行中 (+25 more)
+
+### Community 39 - "Community 39"
+Cohesion: 0.06
+Nodes (34): 知识库整合完成总结, 📁 目录结构详细, 总览, 知识库规模, 数据来源, 📈 知识库价值评估, 综合优势, 应用场景 (+26 more)
+
+### Community 40 - "Community 40"
+Cohesion: 0.06
+Nodes (34): 三、社区成熟的进阶记忆方案, 五、本次网络搜索结果汇总, 1.1 核心理念, 1.2 基础双层结构, 1.3 三层防失忆机制, 六、最佳实践推荐, 七、常见问题排查, 八、资源汇总 (+26 more)
+
+### Community 41 - "Community 41"
+Cohesion: 0.12
+Nodes (19): PortfolioInfo, atr(), BacktestEngine, BacktestResult, bollinger_bands(), BollingerBandsStrategy, donchian_channel(), DonchianChannelStrategy (+11 more)
+
+### Community 42 - "Community 42"
+Cohesion: 0.06
+Nodes (33): 📚 价值投资知识库, **高股息策略**, **质量+价值策略**, **特殊情况策略**, 📚 重要参考文献, **经典著作**, **学术研究**, **行业报告** (+25 more)
+
+### Community 43 - "Community 43"
+Cohesion: 0.06
+Nodes (33): 📋 价值投资领域 - 庞统, 第1周重点, 🔧 所需技能和工具, 核心技能, 研究工具, 数据需求, 🤝 协作机制, 与赵云的协作 (+25 more)
+
+### Community 44 - "Community 44"
+Cohesion: 0.06
+Nodes (33): ⚙️ 技术策略领域 - 张飞, 第1周重点, 🔧 所需技能和工具, 核心技能, 技术工具, 数据需求, 总体目标, 🤝 协作机制 (+25 more)
+
+### Community 45 - "Community 45"
+Cohesion: 0.09
+Nodes (18): BlackSwanFilter, PortfolioDrawdownRiskControl, PortfolioInfo, 风控模块 - 量化策略风控系统 功能： 1. 单票15%止损规则 2. 整体回撤分级风控（10%/20%/25% 分级降仓） 3. 黑天鹅过滤（ST、跌停、财务, 检查是否需要降仓         :return: (是否需要调整, 目标仓位比例), 黑天鹅过滤：排除ST、跌停、财务造假、低流动性票, 初始化过滤器         :param min_daily_volume: 最小日成交额（亿），低于此排除, 过滤个股         :return: (是否通过过滤, 不通过原因)         True = 可以买入，False = 排除 (+10 more)
+
+### Community 46 - "Community 46"
+Cohesion: 0.06
+Nodes (32): 关羽策略代码实现完成报告, 1. 安装依赖, 📂 文件清单, 🎯 实现功能对照表, ✅ 已完成内容, 🚀 使用方法, 📊 策略参数（基于调研报告）, 价值筛选参数 (+24 more)
+
+### Community 47 - "Community 47"
+Cohesion: 0.06
+Nodes (32): 风险度量模型研究与评估, 1. 传统风险度量模型, 1.1 VaR（风险价值）, 1.2 CVaR/ES（条件风险价值/期望短缺）, 1.3 最大回撤, 1.4 波动率, 2. 现代风险度量模型, 最终结论 (+24 more)
+
+### Community 48 - "Community 48"
+Cohesion: 0.06
+Nodes (32): 价值+技术结合综合选股方法调研 - 风险管理视角, 1. 选股方法分类, 1.1 纯价值选股, 1.2 纯技术选股, 1.3 价值+技术结合, 2. 价值+技术结合的常见框架, 2.1 框架一：价值选股 + 趋势确认, 2.2 框架二：成长价值 + 动量选股 (+24 more)
+
+### Community 49 - "Community 49"
+Cohesion: 0.06
+Nodes (31): 🧮 负责人：赵云（数据工程将军）, 1. 聚宽精华文章数据处理, 代码质量标准, 🔄 协作与沟通, 任务接收方式, 成果提交方式, 沟通机制, 2. 数据获取与处理工具 (+23 more)
+
+### Community 50 - "Community 50"
+Cohesion: 0.06
+Nodes (31): 📋 任务信息, 1. 算法资源丰富化, 📈 数据成果, 🎯 任务目标, 知识库总体规模, 知识库结构, 核心目标, 🎯 任务价值贡献 (+23 more)
+
+### Community 51 - "Community 51"
+Cohesion: 0.06
+Nodes (31): 📐 架构设计：整合数据平台与回测环境, 三、接口定义, 数据资产清单, 已有组件, 四、数据流设计, 日线数据流, 张飞回测对接, 五、权衡取舍 (+23 more)
+
+### Community 52 - "Community 52"
+Cohesion: 0.1
+Nodes (9): IndividualRiskWarning, PortfolioRiskWarning, 风控预警和执行系统 功能： 1. 三级预警机制（黄/橙/红） 2. 预警触发后的执行规则 3. 三级风控体系（个股→板块→整体） 4. 执行记录留存，方便回测复, RiskExecution, RiskWarningConfig, RiskWarningSystem, SectorRiskWarning, WarningLevel (+1 more)
+
+### Community 53 - "Community 53"
+Cohesion: 0.1
+Nodes (15): build_combined_factor(), build_main_force_factor(), build_northbound_factor(), build_turnover_factor(), CapitalFlowConfig, CapitalFlowData, CapitalFlowFactorBuilder, CapitalFlowMonitor (+7 more)
+
+### Community 54 - "Community 54"
+Cohesion: 0.12
+Nodes (16): atr(), BacktestEngine, BacktestResult, bollinger_bands(), BollingerBandsStrategy, donchian_channel(), DonchianChannelStrategy, ema() (+8 more)
+
+### Community 55 - "Community 55"
+Cohesion: 0.06
+Nodes (30): 🔍 研究目标, 1. 市场制度性风险特征, 1.1 涨跌停板制度, 1.2 T+1交易制度, 1.3 IPO和退市制度, 2. 流动性风险特征, 核心风险排序, 对量化风控框架的要求 (+22 more)
+
+### Community 56 - "Community 56"
+Cohesion: 0.06
+Nodes (30): 🎯 记忆整理目标, 📋 经常性工作自动化脚本, 项目核心信息, 1. Git 提交和推送自动化脚本, 2. 调研文档更新自动化脚本, 已完成的调研成果, 阿里云服务选型（精简）, 计算服务 (+22 more)
+
+### Community 57 - "Community 57"
+Cohesion: 0.06
+Nodes (30): 一、问题现状, 六、风险与注意事项, 1.1 当前状态, 1.2 问题分析, 步骤1：安装fastembed, 七、实施计划, 八、备选方案：快速修复, 九、结论与建议 (+22 more)
+
+### Community 58 - "Community 58"
+Cohesion: 0.06
+Nodes (30): 项目概述, 1. 适用性风险：水土不服, 五层风控方案, 第一层：事前准入风控, 第二层：头寸规模风控, 第三层：事中执行风控, 第四层：事后复盘风控, 第五层：极端风险兜底 (+22 more)
+
+### Community 59 - "Community 59"
+Cohesion: 0.09
+Nodes (12): FactorDataProcessor, 因子数据处理模块 支持三层中性化：行业中性 + 市值中性 + 风格中性, 多因子数据处理器     支持三层中性化：     1. 行业中性化     2. 市值中性化     3. 风格中性化（可选）, 板块强度计算引擎 综合评分：技术(40%) + 资金(30%) + 基本面(20%) + 情绪(10%), 基本面得分(20%)         - 平均ROE：越高越好         - 平均盈利增速：越高越好, 综合板块强度计算引擎     综合四个维度：     1. **技术面(40%)**: 板块区间涨幅 + 突破情况     2. **资金面(30%)**: 板, 情绪面得分(10%)         - 涨停个股比例：越高情绪越热         - 涨停连板比例：, 计算单个板块综合强度         返回各维度得分和总得分 (+4 more)
+
+### Community 60 - "Community 60"
+Cohesion: 0.09
+Nodes (15): AStockDataQualityManager, main(), 保存配置                  Args:             config: 配置信息, 检查数据完整性                  Args:             data_type: 数据类型（daily, financial, inf, 检查日线数据完整性                  Args:             data_path: 日线数据路径, 检查财务数据完整性                  Args:             data_path: 财务数据路径, 检查基础信息完整性                  Args:             data_path: 基础信息路径, 获取股票代码列表                  Args:             info_path: 基础信息路径 (+7 more)
+
+### Community 61 - "Community 61"
+Cohesion: 0.07
+Nodes (29): 🎯 项目概述, 🔄 工作流程, 策略开发流程, 协作机制, 📊 质量标准, 策略质量标准, 项目启动时间, 数据质量标准 (+21 more)
+
+### Community 62 - "Community 62"
+Cohesion: 0.07
+Nodes (29): 问题描述, 替代方案（优先级：低）, 网络连通性测试结果, 影响评估, 当前受影响的服务, 缓解措施, 后续监控, 定期检查计划 (+21 more)
+
+### Community 63 - "Community 63"
+Cohesion: 0.07
+Nodes (28): 关羽 - 价值+技术综合选股策略, 1. 价值筛选（风控前置）, 代码结构, 预期绩效, 注意事项, 数据依赖, 风控建议, 扩展优化方向 (+20 more)
+
+### Community 64 - "Community 64"
+Cohesion: 0.07
+Nodes (28): 风控研究数据准备, 1. 所需数据类型, 1.1 历史价格成交量数据, 1.2 风险事件数据, 1.3 流动性数据, 1.4 上市公司基本面数据, 2. 数据预处理, 2.1 数据有效性校验 (+20 more)
+
+### Community 65 - "Community 65"
+Cohesion: 0.07
+Nodes (28): 突破策略买卖规则目录, 1. 规则层级结构, 2. 核心规则定义, 2.1 突破检测规则 (`breakout_rules.py`), 2.2 买入执行规则 (`buy_rules.py`), 2.3 卖出执行规则 (`sell_rules.py`), 2.4 仓位管理规则 (`position_rules.py`), 📋 规则体系设计 (+20 more)
+
+### Community 66 - "Community 66"
+Cohesion: 0.07
+Nodes (28): 因子计算目录, 1. 因子分类体系, 1.1 价值因子 (Value Factors), 1.2 质量因子 (Quality Factors), 1.3 动量因子 (Momentum Factors), 1.4 情绪因子 (Sentiment Factors), 2. 因子计算流程, ✅ 已完成 (+20 more)
+
+### Community 67 - "Community 67"
+Cohesion: 0.1
+Nodes (10): MultiFactorDynamicStrategy, 进阶多因子+动态加权+估值择时 A股量化中低频策略 主策略实现，遵循vn.py CtaStrategy接口, 初始化所有因子列表         调整后权重（适配结构化行情）:         - PE: ~15%         - PB: ~15%, 收到K线推送         中低频策略，判断是否需要调仓, 计算所有因子，合成最终得分         参数:             data: 所有股票的行情财务数据，columns需要包含因子所需列, 根据因子得分选股票         参数:             scores: 因子得分降序排列         返回:             选中的股票, 计算选中股票的目标权重         考虑整体择时仓位         考虑板块限制：单板块最高不超过max_sector_pct         等权分配给, 进阶多因子策略     特点:     1. 多因子复合选股     2. 动态加权（根据IC调整）     3. 估值择时（调整整体仓位）     4. 中低 (+2 more)
+
+### Community 68 - "Community 68"
+Cohesion: 0.07
+Nodes (27): 📋 任务信息, 文件存储统计, 🎯 任务目标, 🔄 后续工作, 立即执行, 短期优化, 核心目标, 📝 任务总结 (+19 more)
+
+### Community 69 - "Community 69"
+Cohesion: 0.07
+Nodes (27): 赵云数据工程任务完成报告, 1. 标准结构建立 ✅, 数据标准, 存在问题与解决方案, 任务要求, 后续工作建议, 总结, 完成情况 (+19 more)
+
+### Community 70 - "Community 70"
+Cohesion: 0.1
+Nodes (10): MultiFactorDynamicStrategy, 进阶多因子+动态加权+估值择时 A股量化中低频策略 主策略实现，遵循vn.py CtaStrategy接口, 初始化所有因子列表         调整后权重（适配结构化行情）:         - PE: ~15%         - PB: ~15%, 收到K线推送         中低频策略，判断是否需要调仓, 计算所有因子，合成最终得分         参数:             data: 所有股票的行情财务数据，columns需要包含因子所需列, 根据因子得分选股票         参数:             scores: 因子得分降序排列         返回:             选中的股票, 计算选中股票的目标权重         考虑整体择时仓位         考虑板块限制：单板块最高不超过max_sector_pct         等权分配给, 进阶多因子策略     特点:     1. 多因子复合选股     2. 动态加权（根据IC调整）     3. 估值择时（调整整体仓位）     4. 中低 (+2 more)
+
+### Community 71 - "Community 71"
+Cohesion: 0.07
+Nodes (26): 🚀 极简任务分发工作流 - 端到端使用指南, 第四步：诸葛亮确认结果, 📝 常用命令, 检查监控状态, 重启监控, 🔍 故障排除, 🏗️ 系统架构, ✅ 本次验证要点 (+18 more)
+
+### Community 72 - "Community 72"
+Cohesion: 0.07
+Nodes (26): 📋 任务信息, 1. 股票基础信息, 🎯 任务目标, 🔧 实施计划, 第一阶段：架构搭建（今天）, 核心目标, 🚀 立即执行, 具体数据需求 (+18 more)
+
+### Community 73 - "Community 73"
+Cohesion: 0.11
+Nodes (9): 实时风控面板（主入口） ============  整合风险计算、监控、紧急处理，提供统一接口, RealtimeRiskPanel, 实时风控系统压力测试 ============  测试场景： 1. 正常行情波动 - 无预警 2. 单日回撤 - 触发警告 3. 连续回撤 - 触发紧急处理 4, test_continuous_drawdown(), test_daily_drawdown_warning(), test_emergency_liquidate(), test_high_position_concentration(), test_normal_market() (+1 more)
+
+### Community 74 - "Community 74"
+Cohesion: 0.12
+Nodes (12): IndividualRiskAssessor, IndividualStockRisk, OverallRiskResult, 结构化适配动态多因子 - 风控和择时模块  功能： 1. 个股风险评估：五维风险 + 消息提前监控 + 国际联动风险 2. 择时适配结构化：板块轮动择时，仓位控, 计算消息面风险，返回风险分0~1和警告列表, RiskConfig, RiskLevel, SectorConcentrationControl (+4 more)
+
+### Community 75 - "Community 75"
+Cohesion: 0.11
+Nodes (12): AStockFinancialDataCollector, main(), 采集单只股票的财务指标                  Args:             symbol: 股票代码, 采集资产负债表数据                  Args:             symbol: 股票代码                      R, 采集利润表数据                  Args:             symbol: 股票代码                      Ret, 采集现金流量表数据                  Args:             symbol: 股票代码                      R, 批量采集财务数据                  Args:             stock_list: 股票代码列表             max_w, 保存财务数据                  Args:             df: 财务数据             data_type: 数据类型 (+4 more)
+
+### Community 76 - "Community 76"
+Cohesion: 0.08
+Nodes (24): 快速开始, 工作原理, 任务分配流程, 监控机制, 任务特点, 系统状态, 启动所有Agent, 查看所有Agent状态 (+16 more)
+
+### Community 77 - "Community 77"
+Cohesion: 0.08
+Nodes (24): 聚宽社区回测与实盘文章分析报告, 文章1：高效使用聚宽回测平台的技巧, 筛选标准, 选定文章列表, 三、对我们框架改进的价值总结, 1. 性能优化模块, 1. 实盘上线流程标准化, 短期改进（1-2周） (+16 more)
+
+### Community 78 - "Community 78"
+Cohesion: 0.08
+Nodes (24): 一、研究背景, 二、架构方案设计, 三、部署方案, 四、实现步骤, 五、结论, 2.1 团队职责与架构对应关系, 2.2 项目目录结构与架构组件对应关系, 2.3 核心架构组件 (+16 more)
+
+### Community 79 - "Community 79"
+Cohesion: 0.09
+Nodes (23): 加拿大云主机中转方案调研报告, 1. 概述, 完成！🎉, 常见问题, 下一步, 付款方式对比, 七、最佳实践清单, 八、总结 (+15 more)
+
+### Community 80 - "Community 80"
+Cohesion: 0.1
+Nodes (23): 服务器端配置, 第三步：服务器初始化（3分钟）, 登录服务器, 一键脚本（推荐）, 安全加固措施, 创建服务器配置文件, 复制以下内容并替换密钥, 客户端配置（Clash/ClashX） (+15 more)
+
+### Community 81 - "Community 81"
+Cohesion: 0.13
+Nodes (11): PortfolioDrawdownRiskControl, 检查是否需要降仓         :return: (是否需要调整, 目标仓位比例), 交易前检查：开仓前调用         :return: (是否允许开仓, 原因), 收盘后检查：止损检查 + 降仓检查         :return: 风控结果，包含需要止损的票和需要降仓的信息, 初始化         :param stop_loss_pct: 止损比例，默认15%, 检查是否触发止损         :return: True = 需要止损，False = 持有, 整体回撤分级风控     10%回撤 → 降仓50%     20%回撤 → 降仓75%     25%回撤 → 清仓休息, 初始化分级风控         :param drawdown_levels: 回撤阈值         :param reduce_ratios: 对应降仓比 (+3 more)
+
+### Community 82 - "Community 82"
+Cohesion: 0.09
+Nodes (20): 统计概述, 1. **架构借鉴**, 六、总结, 二、完整业务场景和功能列表, 核心功能, 2. **端口规划借鉴**, 主要发现, 3. **认证方式借鉴** (+12 more)
+
+### Community 83 - "Community 83"
+Cohesion: 0.09
+Nodes (21): 张飞 - 技术选股策略回测代码实现完成报告, 1. 数据结构, 任务目标, 优点, 已集成功能, 使用示例, 文档参考, 测试验证 (+13 more)
+
+### Community 84 - "Community 84"
+Cohesion: 0.13
+Nodes (11): 技术信号过滤器 - 第二步：技术分析确认入场点     ===============================================, 初始化技术过滤器                  Args:             ma_days: 均线天数，默认20日, 获取股票历史行情数据                  Args:             stock_code: 股票代码             days:, 计算ATR（Average True Range）波动率指标                  Args:             df: 历史数据, 检查趋势是否向上                  条件：         1. 股价站在20日均线上         2. 均线向上倾斜, 检查近期是否有过度下跌                  条件：         近一个月跌幅不超过20%                  Args:, 检查是否有极端放量（主力出货信号）                  条件：         排除极端放量情况, 检查MACD信号（可选增强信号）                  条件：         MACD金叉或MACD在零轴上方 (+3 more)
+
+### Community 85 - "Community 85"
+Cohesion: 0.17
+Nodes (3): PureBreakoutStrategy, 纯突破量化策略 逻辑: N日新高放量突破买入，严格止损止盈卖出, 纯突破策略     - 突破N日新高 + 放量买入     - 严格止损（跌破突破最低价5%）     - 跟踪止盈（从高点回落10%）     - 均线止盈（
+
+### Community 86 - "Community 86"
+Cohesion: 0.14
+Nodes (15): BaseStrategy, DataCatalog, DataCatalog - 统一数据访问接口  策略开发者只需通过 DataCatalog 获取数据， 无需关心底层文件路径和存储格式。  核心API： - g, 获取股票基础信息或指数成分股          Args:             index: 指数代码，如 "hs300"；None 返回全部 A 股基础信, 统一数据目录 —— 项目唯一数据入口      Usage:         from data_platform import DataCatalog, DummyMAStrategy, 数据平台完整测试 - 验证 DataCatalog + BacktestRunner  运行方式：cd sanguo_quant_live && python3, 测试完整回测流程：获取数据 → 策略 → 模拟交易 → 报告 (+7 more)
+
+### Community 87 - "Community 87"
+Cohesion: 0.15
+Nodes (19): ema(), example_ma(), example_macd(), example_rsi(), get_sample_data(), macd(), main(), plot_examples() (+11 more)
+
+### Community 88 - "Community 88"
+Cohesion: 0.1
+Nodes (19): ✅ 基础架构建设, 1. 已完成工作, 📋 缺失数据, ✅ 基础数据采集, 目前需要配合：, ✅ 数据采集工具开发, 2. 已接入数据源, 3. 数据存储位置和格式 (+11 more)
+
+### Community 89 - "Community 89"
+Cohesion: 0.15
+Nodes (12): TimeFrame, Enum, EmergencyAction, EmergencyLevel, 交易中断和紧急处理算法 ============  提供多级紧急风险处置： - 级别1：预警提示（不干预，只通知） - 级别2：限制开仓（只允许平仓，不允许开仓, AlertLevel, 实时风险阈值监控系统 ============  实时监控风险指标，触发阈值自动预警： - 单日回撤预警 - 累计回撤预警 - 高仓位预警 - 集中度预警 -, PolicyNews (+4 more)
+
+### Community 90 - "Community 90"
+Cohesion: 0.16
+Nodes (6): PolicyClassifier, PolicyRiskAlert, PolicyRotationModule, PolicySignal, PolicySignalGenerator, 检查政策风险         返回：(是否高风险, 风险等级 1~3, 原因)
+
+### Community 92 - "Community 92"
+Cohesion: 0.13
+Nodes (3): EmergencyConfig, EmergencyHandler, 初始化                  参数:             risk_style: "conservative" / "aggressive"
+
+### Community 93 - "Community 93"
+Cohesion: 0.16
+Nodes (5): 选股:          1. 因子打分选topN*2         2. 年线过滤（如果开启）         3. 技术择时二次过滤（如果开启），只保留多, 计算目标权重，考虑:         1. 整体目标仓位         2. 单票不超max_single_pct         3. 单板块不超max_s, 结构化适配动态多因子策略     适配当前A股结构化板块轮动行情, 获取当前全市场数据         需要包含列:         - symbol: 股票代码         - date: 日期         - clo, StructuredDynamicMultiFactorStrategy
+
+### Community 94 - "Community 94"
+Cohesion: 0.16
+Nodes (9): AStockDailyDataCollector, main(), 采集单只股票的日线数据                  Args:             symbol: 股票代码             start_da, 批量采集日线数据                  Args:             stock_list: 股票代码列表（如为空则自动获取）, 保存单只股票日线数据                  Args:             stock_data: 股票日线数据, 保存合并后的日线数据                  Args:             combined_data: 合并后的所有日线数据, 获取已保存的文件列表                  Returns:             List[str]: 文件路径列表, 生成采集摘要报告                  Args:             result: 采集结果                      Re (+1 more)
+
+### Community 95 - "Community 95"
+Cohesion: 0.15
+Nodes (10): DataAdapterTester, main(), 测试数据完整性                  Args:             data_path: 数据文件路径             require, 初始化测试工具                  Args:             config_file: 配置文件路径, 测试数据一致性                  Args:             data_path: 数据文件路径             expecte, 运行所有测试                  Returns:             Dict: 所有测试结果, 生成测试报告                  Returns:             Dict: 测试报告, 保存测试结果                  Args:             output_path: 输出路径 (+2 more)
+
+### Community 96 - "Community 96"
+Cohesion: 0.11
+Nodes (18): 📋 概述, 🛠️ 维护流程（给姜维）, 📝 配置信息, ✨ 方案特点, 🚀 使用方法（给各位将军）, 📝 你写完策略/改完策略，要回测了：, 🚀 使用方法（给姜维）, 📊 回测结果在哪里 (+10 more)
+
+### Community 97 - "Community 97"
+Cohesion: 0.15
+Nodes (10): DownloadConfig, main(), MinuteKlineCollector, 测试数据源可用性                  Returns:             Dict[str, Any]: 数据源测试结果, 验证数据质量                  Args:             data: 数据             timeframe: 时间粒度, 下载单只股票的分钟数据                  Args:             config: 下载配置, 批量下载股票数据                  Args:             symbols: 股票代码列表             timefram, 初始化收集器                  Args:             base_dir: 基础目录（用于测试，NAS就绪后修改） (+2 more)
+
+### Community 98 - "Community 98"
+Cohesion: 0.16
+Nodes (8): RSI信号         返回: (oversold_buy, overbought_sell)         RSI超卖( < 30)买入，超买( > 7, KDJ金叉死叉         返回: (golden_cross, death_cross), 组合多个技术信号，多头信号越多，得分越高         最终返回是否看多, 根据技术择时过滤候选股票         只保留多头信号得分超过阈值的, 均线多头排列         短期均线上穿中期，中期均线上穿长期 → 多头信号         返回: bool Series，True=多头, MACD金叉死叉信号         返回: (golden_cross, death_cross), 布林带信号         返回: (break_upper, break_lower)         突破上轨 → 看多，跌破下轨 → 看空, TechnicalTimingSignals
+
+### Community 99 - "Community 99"
+Cohesion: 0.18
+Nodes (3): MultiFactorDynamicStrategy, 进阶多因子动态加权策略     特点:     1. 多因子复合选股     2. 动态加权（根据IC调整）     3. 估值择时（调整整体仓位）     4, 转换组合信息为风控PortfolioInfo
+
+### Community 100 - "Community 100"
+Cohesion: 0.17
+Nodes (9): AStockBasicInfoCollector, main(), 采集行业分类信息                  Returns:             pd.DataFrame: 行业分类数据, 保存原始数据                  Args:             df: 原始数据, 处理基础信息数据                  Args:             df: 原始数据                      Return, 保存处理后数据                  Args:             df: 处理后数据, 生成数据摘要                  Args:             df: 数据                      Returns:, 运行采集器                  Returns:             dict: 采集结果 (+1 more)
+
+### Community 101 - "Community 101"
+Cohesion: 0.11
+Nodes (17): 📁 归档信息, 1. 重要文档报告, 📋 文件清单, 赵云工作区历史备份归档 - 20240325, 2. Python脚本文件, 3. 数据文件, 🗑️ 已清理文件, 🔄 归档原因 (+9 more)
+
+### Community 102 - "Community 102"
+Cohesion: 0.12
+Nodes (18): 适用场景, 三、运营风险, 可能原因, 应对策略, 可能的额外费用, 成本控制建议, 可能问题, 预防措施 (+10 more)
+
+### Community 103 - "Community 103"
+Cohesion: 0.11
+Nodes (18): 1. 分工明确, 2. 证据驱动, 项目目标, 核心原则, 目录结构规范, 代码风格规范, 策略代码, 回测规范 (+10 more)
+
+### Community 104 - "Community 104"
+Cohesion: 0.18
+Nodes (4): 实时风险指标计算引擎 ============  实时计算各类风险指标，支持： - 持仓风险指标计算 - 动态VaR计算 - 实时回撤监控 - 流动性风险计算, RealTimeRiskCalculator, RiskMetrics, ThresholdConfig
+
+### Community 105 - "Community 105"
+Cohesion: 0.12
+Nodes (7): 因子合成工具 将多个因子按权重合成最终得分, MarketValuationTiming, 大盘估值择时模块 根据全市场估值分位数调整整体仓位 估值低位加大仓位，估值高位降低仓位, 大盘估值择时     根据全市场PE/PB分位数调整整体仓位, 参数:             min_position: 最小仓位（高估时）             max_position: 最大仓位（低估时）, 更新当期估值数据         参数:             current_pe: 当前全市场PE, 根据当前估值计算目标仓位         返回:             target_position: 目标仓位 0~1
+
+### Community 106 - "Community 106"
+Cohesion: 0.13
+Nodes (5): DynamicWeightAdjuster, FactorCombiner, 因子合成器 - 把多个因子按权重合成最终得分, 动态权重调整器 - 根据滚动IC自动调整因子权重, 完整处理流程: 原始计算 → 标准化 → rank
+
+### Community 107 - "Community 107"
+Cohesion: 0.19
+Nodes (8): AStockDataMainController, main(), 运行日线数据采集任务                  Args:             test_mode: 测试模式（少量数据）, 运行财务数据采集任务                  Args:             test_mode: 测试模式（少量数据）, 运行质量检查任务                  Returns:             Dict: 任务执行结果, 运行完整的数据采集流水线                  Args:             test_mode: 测试模式, 生成汇总报告                  Args:             execution_time: 执行时间（秒）, 运行基础信息采集任务                  Args:             test_mode: 测试模式（少量数据）
+
+### Community 108 - "Community 108"
+Cohesion: 0.12
+Nodes (17): 1.4 技术选股策略代码实现, 1.4.1 策略架构设计, 1.4.10 后续改进建议, 1.4.2 策略1：MACD底背离+均线策略, 1.4.5 技术指标计算器, 1.4.6 回测引擎说明, 1.4.8 代码质量保证, 1.4.9 测试示例输出 (+9 more)
+
+### Community 109 - "Community 109"
+Cohesion: 0.12
+Nodes (16): 团队配置, 执行层, 监控进程, 工作流程, 创建任务, 分配任务, 指挥层, 结果验收 (+8 more)
+
+### Community 110 - "Community 110"
+Cohesion: 0.12
+Nodes (16): 🛡️ 实时风险监控系统, 压力测试结果, 集成到交易系统, 架构, 作者, 许可证, 快速开始, 功能概述 (+8 more)
+
+### Community 111 - "Community 111"
+Cohesion: 0.12
+Nodes (16): 📋 需求规格文档：整合数据平台与回测环境, 三、交付物清单, 现状梳理, 四、功能边界（不做的事）, 五、假设列表, 六、依赖关系, 七、技术约束, 核心问题 (+8 more)
+
+### Community 112 - "Community 112"
+Cohesion: 0.12
+Nodes (16): 🎯 调研目标, 五、多因子复合选股, 方法, 胜率提升, 七、选股流程推荐, 标准流程, 仓位管理建议, 📊 预期绩效汇总 (+8 more)
+
+### Community 113 - "Community 113"
+Cohesion: 0.14
+Nodes (6): BaseStructuredFactor, ROEFactor, Momentum1MFactor, Momentum3MFactor, PBFactor, PEFactor
+
+### Community 114 - "Community 114"
+Cohesion: 0.23
+Nodes (3): AStockFinancialDownloader, main(), 计算估值指标 (PE, PB, ROE, 股息率)
+
+### Community 115 - "Community 115"
+Cohesion: 0.12
+Nodes (16): 四、隐私风险, 服务商可能记录的信息, 保护隐私的建议, 建议做法, 客户端配置, 服务器端配置, 4. 端到端实施步骤, 4.1 准备工作 (+8 more)
+
+### Community 116 - "Community 116"
+Cohesion: 0.12
+Nodes (16): 问题10：担心安全问题，不想暴露服务, 问题4：局域网无法访问容器服务, 问题5：访问速度慢或延迟高, 问题6：容器内无法访问NAS挂载目录, 问题7：数据库性能差, 问题8：vn.py缺少某些交易接口, 问题9：策略回测时内存溢出, 九、可能遇到的问题和解决方案 (+8 more)
+
+### Community 117 - "Community 117"
+Cohesion: 0.12
+Nodes (15): 一、调研背景, 二、主流方案概览, 四、方案推荐, 场景分类推荐, 综合推荐（按优先级）, 五、成本效益分析, 经济成本, 时间成本 (+7 more)
+
+### Community 118 - "Community 118"
+Cohesion: 0.15
+Nodes (14): 审核概况, 1. 张飞 - 指标分类统计报告, 回测结果质量审核, 各部分质量审核, 2. 关羽 - 风险分析风控方案, 审核概况, 3. 姜维 - Pine Script转Python可行性研究, 环境修复质量审核 (+6 more)
+
+### Community 119 - "Community 119"
+Cohesion: 0.12
+Nodes (15): **🏆 报告摘要**, **1. 调研背景和目标**, **12. 附录**, **12.1 数据来源清单**, **12.2 参考文献**, **12.3 技术文档**, **12.4 联系方式**, **推荐框架** (+7 more)
+
+### Community 120 - "Community 120"
+Cohesion: 0.17
+Nodes (8): get_structural_risk_report(), HotSectorNewsRiskAdjust, 结构化行情择时风控模块 专门处理A股结构化行情下的板块集中度风险和择时信号  功能： 1. 择时：单板块连续大涨提醒风险，连续大跌提示低吸 2. 风控：控制板块, 热点板块消息风险调整，热点更容易利好出尽，灵敏度提高, 板块择时         返回：(信号类型, 建议, 风险增量评分)         信号类型: bull/bear/neutral, SectorConcentrationRisk, SectorInfo, StructuredMarketTiming
+
+### Community 121 - "Community 121"
+Cohesion: 0.19
+Nodes (7): 因子基类 - 所有因子继承此类 定义统一的因子计算接口, 中国特色因子 - 市值因子：A股中小盘有超额，市值越小越好 - 反转因子：近期反转，一个月反转, 成长因子 - 营收增速、净利润增速 增速越高，得分越高, 质量因子 - ROE净资产收益率 盈利能力越强，得分越高, 板块强度因子 - 适配结构化行情板块轮动 板块强度 = 板块近一个月涨幅 / 全市场平均涨幅 强度越高，得分越高, 技术趋势因子 - 动量因子 近期涨幅越大，动量越强，得分越高, 价值因子 - PE/PB 估值越低，得分越高
+
+### Community 122 - "Community 122"
+Cohesion: 0.17
+Nodes (8): get_structural_risk_report(), HotSectorNewsRiskAdjust, 结构化行情择时风控模块 专门处理A股结构化行情下的板块集中度风险和择时信号  功能： 1. 择时：单板块连续大涨提醒风险，连续大跌提示低吸 2. 风控：控制板块, 热点板块消息风险调整，热点更容易利好出尽，灵敏度提高, 板块择时         返回：(信号类型, 建议, 风险增量评分)         信号类型: bull/bear/neutral, SectorConcentrationRisk, SectorInfo, StructuredMarketTiming
+
+### Community 123 - "Community 123"
+Cohesion: 0.14
+Nodes (5): DataPlatformConfig, _find_project_root(), 数据平台配置层  配置优先级： 1. 环境变量 SANGUO_QUANT_ROOT 2. 默认项目根目录（向上查找 sanguo_quant_live 标记文件, 获取指定股票指定年份的 parquet 文件路径, test_config()
+
+### Community 124 - "Community 124"
+Cohesion: 0.17
+Nodes (8): get_structural_risk_report(), HotSectorNewsRiskAdjust, 结构化行情择时风控模块 专门处理A股结构化行情下的板块集中度风险和择时信号  功能： 1. 择时：单板块连续大涨提醒风险，连续大跌提示低吸 2. 风控：控制板块, 热点板块消息风险调整，热点更容易利好出尽，灵敏度提高, 板块择时         返回：(信号类型, 建议, 风险增量评分)         信号类型: bull/bear/neutral, SectorConcentrationRisk, SectorInfo, StructuredMarketTiming
+
+### Community 125 - "Community 125"
+Cohesion: 0.15
+Nodes (10): BacktestResult, calculate_bollinger_bands(), calculate_ema(), calculate_macd(), calculate_sma(), MACDDivergenceStrategy, 技术选股策略回测框架 实现三种推荐策略： 1. MACD底背离+均线 2. 布林带下轨+趋势 3. 唐奇安通道突破  作者：张飞 日期：2026年3月24日, MACD底背离 + 均线过滤策略          买入条件:     1. 股价创近期新低（20日最低）     2. MACD DIF值没有创新低（底背离） (+2 more)
+
+### Community 126 - "Community 126"
+Cohesion: 0.13
+Nodes (15): **按投资风格分类**, **按时间周期分类**, **1.1 选股方法分类体系**, **1.2 各种方法的适用场景**, **1.3 整合框架设计原则**, **1.3.1 全面性原则**, **1.3.2 实用性原则**, **1.3.3 适应性原则** (+7 more)
+
+### Community 127 - "Community 127"
+Cohesion: 0.14
+Nodes (15): 个人信息保护, 数据留存, 1.1 加拿大相关法律法规, 1.2 用户所在国家/地区法律, 1.3 合规使用建议, 2. 云服务商选择与价格对比, 电信法规, 价格详情 (+7 more)
+
+### Community 128 - "Community 128"
+Cohesion: 0.13
+Nodes (14): 十一、成本与收益分析, 十二、分阶段迁移实施计划, 11.1 硬件成本（参考）, 11.2 收益分析, 12.1 第一阶段：准备与验证（1-2天）, 12.2 第二阶段：Docker环境部署（2-3天）, 12.3 第三阶段：数据迁移（1-2天）, 12.4 第四阶段：功能验证与优化（2-3天） (+6 more)
+
+### Community 129 - "Community 129"
+Cohesion: 0.13
+Nodes (15): 数据迁移步骤, 访问方式配置, 浏览器书签配置, 基础安全措施, 2.1 整体架构设计, 2.3 数据迁移方案, 2.4 Mac mini端配置, 2.5 网络安全配置 (+7 more)
+
+### Community 130 - "Community 130"
+Cohesion: 0.13
+Nodes (15): 1. 确认群晖NAS型号和架构, 步骤1：SSH登录群晖NAS, 2. 启用群晖Docker, 步骤2：创建Docker网络（可选但推荐）, 3. 准备共享文件夹, 3.1 准备工作, 3.2 部署步骤详解, 步骤3：拉取或构建镜像 (+7 more)
+
+### Community 131 - "Community 131"
+Cohesion: 0.13
+Nodes (14): 📁 文件说明, 1. 前置条件, 部署脚本, 🚀 快速开始, 2. 部署步骤, 3. 访问服务, 📖 详细文档, 🔧 配置说明 (+6 more)
+
+### Community 132 - "Community 132"
+Cohesion: 0.13
+Nodes (14): 一、问题根因诊断, 七、致谢, 二、实施方案（采纳司马懿评审建议）, 1. 本地Embedding服务测试, 2. 配置变更详情, 3. 功能验证, 三、执行步骤清单, 四、关键验证数据 (+6 more)
+
+### Community 133 - "Community 133"
+Cohesion: 0.14
+Nodes (12): 📋 数据概况, 存储结构, 2. 数据更新, 🚀 使用说明, 📊 数据质量, 完整性检查, 准确性验证, 🔧 技术架构 (+4 more)
+
+### Community 134 - "Community 134"
+Cohesion: 0.13
+Nodes (15): 四、高频算法选股, 方法原理, 优点, 缺点, 方法原理, 评价, 方法原理, 评价 (+7 more)
+
+### Community 135 - "Community 135"
+Cohesion: 0.13
+Nodes (15): 三、动量策略选股, 方法原理, 参数常见取值, 优点, 缺点, 方法原理, 优点, 缺点 (+7 more)
+
+### Community 136 - "Community 136"
+Cohesion: 0.15
+Nodes (6): MarketRegimeWeightAllocator, 市场状态动态权重分配 根据市场状态（牛市/熊市/震荡市）调整因子权重 - 牛市：提高趋势、板块强度权重 - 熊市：提高价值、质量权重 - 震荡市：均衡配置, 大类权重展开到具体因子权重         大类 → 具体因子平分, 市场状态权重分配器     根据波动率和趋势判断市场状态，自动调整因子权重, 判断市场状态         根据: 最近N日涨跌幅 + 波动率         返回: 'bull' / 'bear' / 'range_bound', 技术择时信号系统 支持多种技术择时信号： - 均线多头排列 - MACD金叉/死叉 - 突破布林带上轨/跌破下轨 - RSI超买超卖 - KDJ金叉/死叉
+
+### Community 137 - "Community 137"
+Cohesion: 0.2
+Nodes (7): BacktestResult, BacktestRunner, BacktestRunner - 回测引擎  胶水层：取数据 → 生成信号 → 模拟交易 → 出报告  自带简易回测引擎，不依赖 vnpy，降低使用门槛。 保留, 运行单只股票回测          Args:             strategy: 策略实例（BaseStrategy 子类）, 模拟交易，返回 (trades, equity_series), 回测引擎      一条命令完成：获取数据 → 运行策略 → 生成回测结果, Trade
+
+### Community 140 - "Community 140"
+Cohesion: 0.15
+Nodes (6): HighFrequencyDataPipeline, HighFrequencySignalGenerator, 高频交易信号生成器 支持tick级和分钟级数据处理 低延迟信号生成 支持向量化计算, 高频交易信号生成器     支持多种技术因子组合生成交易信号, Signal, TickData
+
+### Community 141 - "Community 141"
+Cohesion: 0.14
+Nodes (14): 4.1 支持数据源, 4.2.1 整体架构设计, 4.2.2 核心组件, 4.2 akshare → vnpy 适配器架构, 4.3.1 DbBarData 表（K线数据）, 4.3.2 DbTickData 表（TICK数据）, 4.3 vn.py SQLite数据库结构, 4.4 数据格式映射 (+6 more)
+
+### Community 142 - "Community 142"
+Cohesion: 0.14
+Nodes (13): 五虎上将多因子选股体系 - 最终整合调研报告, 📋 项目概述, 第八部分：整合结论与建议, 📊 项目完成情况总结, 🎯 最终结论, 3.1 多因子综合评分模型, 3.2 各种选股方法绩效对比（基于2026年3月A股数据）, 3.3 A股市场特征发现 (+5 more)
+
+### Community 143 - "Community 143"
+Cohesion: 0.16
+Nodes (14): 应对措施, 优点, 数据泄露风险, 保护措施, 2.2 价格对比（基础配置实例）, 2.3 数据安全风险, 二、技术风险, 基本信息 (+6 more)
+
+### Community 144 - "Community 144"
+Cohesion: 0.14
+Nodes (13): 三、价值评估, 五、结论与建议, 六、附录, 2.1 CPA-Dashboard 集成分析, 2.2 cockpit-tools 集成分析, 3.1 CPA-Dashboard 价值, 3.2 cockpit-tools 价值, 5.1 核心结论 (+5 more)
+
+### Community 145 - "Community 145"
+Cohesion: 0.15
+Nodes (12): 纯突破量化策略方案, 1. 突破定义, 📁 目录结构, 2. 策略逻辑, 参数配置, 🎯 策略核心思想, 3. 策略特点, 适用市场 (+4 more)
+
+### Community 146 - "Community 146"
+Cohesion: 0.14
+Nodes (14): 2.2 模型适配提示词, 2.2.1 OpenAI GPT/Codex专用指南, 2.2.2 Google Gemini/Gemma专用指南, 2.2.3 角色映射机制, 2.4 技能系统提示词, 2.4.1 技能索引格式, 2.4.2 技能目录结构, 2. Hermes-Agent 提示词设计分析 (+6 more)
+
+### Community 147 - "Community 147"
+Cohesion: 0.14
+Nodes (14): **第三层：另类数据因子（权重15%）**, **第二层：中国特色因子（权重30%）**, **第一层：核心因子（权重50%）**, **第四层：风险控制因子（权重5%）**, **9. 多因子综合框架设计**, **9.1 四层架构设计**, **9.2 动态调整机制**, **9.2.1 市场环境适应** (+6 more)
+
+### Community 149 - "Community 149"
+Cohesion: 0.15
+Nodes (12): 项目简介, 1. 谁的目录谁负责, 远程仓库, 2. 不该放进项目的, 3. 调研产物处理, 4. 归档规则, 目录规则, 目录结构 (+4 more)
+
+### Community 150 - "Community 150"
+Cohesion: 0.15
+Nodes (13): 回测方案1: 多因子综合评分模型, 第六部分：完整测试验证与回测结果（司马懿）, 各回测方案核心指标汇总, 关键发现, 核心结论, 推荐策略框架, 未来改进方向, 回测方案2: 高级选股方法完整对比 (+5 more)
+
+### Community 151 - "Community 151"
+Cohesion: 0.15
+Nodes (12): 量化策略方案存档库, 🔥 最新存档, 📋 方案核心要点, 🏗️ 策略架构, 📁 目录结构, 📊 回测设计, 🚀 开发路线, 👥 分工建议 (+4 more)
+
+### Community 152 - "Community 152"
+Cohesion: 0.15
+Nodes (13): 1.1 价格突破类型, 1.2 成交量确认, 1. 突破信号定义, 2.1 突破条件, 2.2 买入时机, 2. 买入规则, 4. 仓位管理, 📊 策略逻辑框架 (+5 more)
+
+### Community 153 - "Community 153"
+Cohesion: 0.15
+Nodes (13): 5.1 三项目的协作模式对比, 5.2 Oh-My-Codex/Oh-My-ClaudeCode 职责矩阵, 5.4 路由指令设计, 5.4.1 显式路由在提示词中, 5.4.2 路由触发条件, 5.5 协作流程示例, 5.5.1 Oh-My-Codex 标准开发流程, 5.5.2 Oh-My-ClaudeCode RALPLAN共识流程 (+5 more)
+
+### Community 154 - "Community 154"
+Cohesion: 0.15
+Nodes (13): 6. 对三国量化项目的借鉴建议, 6.2 职责强化与提示词对齐, 6.2.1 为每位将军定义严格的职责边界, 6.2.2 实现两阶段质量审查, 6.3 上下文文件增强, 6.3.1 保留并强化现有文件, code:markdown (<explore>), code:markdown (## 路由协议) (+5 more)
+
+### Community 155 - "Community 155"
+Cohesion: 0.15
+Nodes (13): 提示词工程调研报告, 1. 项目概述, 1.1 Hermes-Agent, 1.2 Oh-My-Codex, 1.3 Oh-My-ClaudeCode, 4.1 与Oh-My-Codex的主要差异, 4.2.1 调查协议增强, 4.2.2 RALPLAN共识审查 (+5 more)
+
+### Community 156 - "Community 156"
+Cohesion: 0.15
+Nodes (13): 4.3.1 调查协议增强, 4.3.2 审查清单, 4.3.3 API契约审查, 4.3.4 风格审查模式, 4.3.5 性能审查模式, 4.3.6 质量策略模式, 4.3 Code Reviewer 提示词增强, code:yaml (<Investigation_Protocol>) (+5 more)
+
+### Community 157 - "Community 157"
+Cohesion: 0.15
+Nodes (12): 一、适用性风险：水土不服的根源, 第三层：事中执行风控, 第四层：事后复盘风控, 第五层：极端风险兜底, 总结, 二、过度拟合风险：曲线拟合的陷阱, 三、指标失效风险：市场风格演变的必然, 四、手续费冲击风险：高频交易的隐形杀手 (+4 more)
+
+### Community 158 - "Community 158"
+Cohesion: 0.15
+Nodes (12): 1. 项目概述, 2. 转换基础框架搭建, 2.1 核心依赖库, 2.2 示例指标实现, 3. 通用转换规则整理, 4. 完整迁移工作量与可行性评估, 4.1 可行性分析, 4.2 工作量评估 (+4 more)
+
+### Community 159 - "Community 159"
+Cohesion: 0.15
+Nodes (13): **7.1 自然语言处理应用**, **7.1.1 财报文本分析**, **7.1.2 电话会议分析**, **7.1.3 新闻和研报分析**, **7.2 机器学习应用**, **7.2.1 价值信号识别**, **7.2.2 估值模型优化**, **7.2.3 风险预测和控制** (+5 more)
+
+### Community 160 - "Community 160"
+Cohesion: 0.15
+Nodes (13): **6. 另类数据选股方法研究**, **6.1 社交媒体情绪选股法**, **6.1.1 数据来源**, **6.1.2 价值信号**, **6.1.3 应用方法**, **6.2 供应链数据选股法**, **6.2.1 数据来源**, **6.2.2 价值信号** (+5 more)
+
+### Community 161 - "Community 161"
+Cohesion: 0.15
+Nodes (13): **10. 实施指南和风险管理**, **10.1 实施步骤**, **10.2 风险管理**, **10.2.1 风险识别**, **10.2.2 风险控制**, **10.2.3 风险监控**, **10.3 绩效评估**, **10.3.1 评估指标** (+5 more)
+
+### Community 162 - "Community 162"
+Cohesion: 0.15
+Nodes (13): **11. 结论和建议**, **11.1 主要结论**, **11.1.1 理论贡献**, **11.1.2 实践价值**, **11.1.3 创新之处**, **11.2 具体建议**, **11.2.1 对投资者的建议**, **11.2.2 对研究者的建议** (+5 more)
+
+### Community 163 - "Community 163"
+Cohesion: 0.15
+Nodes (13): **🔬 另类数据类型和价值信号**, **2. 供应链和物流数据**, **2.1 数据来源**, **2.2 价值信号**, **2.3 应用方法**, **4. 网络搜索和关注度数据**, **4.1 数据来源**, **4.2 价值信号** (+5 more)
+
+### Community 164 - "Community 164"
+Cohesion: 0.15
+Nodes (13): **第一阶段：准备阶段（1-2周）**, **第三阶段：实施阶段（1-2周）**, **第二阶段：开发阶段（2-3周）**, **🎯 实施指南**, **第四阶段：优化阶段（持续）**, **风险识别**, **风险控制**, **风险监控** (+5 more)
+
+### Community 165 - "Community 165"
+Cohesion: 0.15
+Nodes (13): **分析内容**, **技术方法**, **价值信号**, **分析内容**, **技术方法**, **价值信号**, **分析内容**, **技术方法** (+5 more)
+
+### Community 166 - "Community 166"
+Cohesion: 0.15
+Nodes (13): **🔍 第四部分：另类数据选股方法**, **数据来源**, **价值信号**, **应用方法**, **数据来源**, **价值信号**, **应用方法**, **数据来源** (+5 more)
+
+### Community 167 - "Community 167"
+Cohesion: 0.15
+Nodes (12): 任务信息, 需求分解, 1. TR（True Range）计算, 2. ATR计算, 3. 接口设计, 开发计划, 4. 示例代码, 产出物 (+4 more)
+
+### Community 168 - "Community 168"
+Cohesion: 0.23
+Nodes (7): 排除基本风险股票（风控前置）                  排除条件：         1. ST/*ST股票         2. 上市不足180天的新股, 估值指标筛选                  筛选条件：         1. PE < pe_max（根据风险偏好）         2. PB < pb_, 质量指标筛选                            筛选条件：         1. ROE > roe_min（根据风险偏好）, 执行完整的价值筛选流程                  Args:             stock_list: 股票列表，如果为None则自动获取, 价值筛选器 - 第一步：价值筛选缩小范围     =========================================     风控前置，通过基本, 获取A股全市场股票列表                  Returns:             股票列表 DataFrame, ValueFilter
+
+### Community 169 - "Community 169"
+Cohesion: 0.18
+Nodes (7): PositionManager, 仓位管理器 - 第三步：仓位控制和动态止损     ==========================================     控制单票仓位、, 计算单票仓位大小                  规则：         1. 单票最大仓位不超过风险偏好限制         2. 根据股票数量动态调整，确, 检查行业集中度是否超标                  Args:             positions: 持仓列表, 计算止损价格                  方法：         1. ma_method: 收盘价跌破20日均线         2. atr_meth, 生成入场订单                  Args:             selected_stocks: 选中的股票列表, 检查出场信号                  出场条件：         1. 止损：价格跌破止损价         2. 均线止损：收盘价跌破20日均线
+
+### Community 171 - "Community 171"
+Cohesion: 0.23
+Nodes (6): BatchDownloader, main(), 下载金融数据                  Args:             symbols: 股票代码列表             start_date, 断点续传                  Args:             log_file: 下载日志文件                      Re, 下载聚宽文章                  Args:             article_links: 文章链接列表             dela, 解析聚宽文章内容                  Args:             html_content: HTML内容
+
+### Community 173 - "Community 173"
+Cohesion: 0.26
+Nodes (6): benchmark_full_pipeline(), benchmark_technical_calculator(), generate_test_data(), main(), 高频算法性能基准测试 测试不同实现方式的性能, PerformanceMonitor
+
+### Community 174 - "Community 174"
+Cohesion: 0.17
+Nodes (12): **💎 第二部分：价值投资选股方法（庞统）**, **2.1 价值投资理论基础**, **2.1.1 价值投资核心原理**, **2.1.2 A股价值投资实践**, **2.2 基本面因子分析体系**, **2.2.1 估值因子**, **2.2.2 质量因子**, **2.2.3 成长因子** (+4 more)
+
+### Community 175 - "Community 175"
+Cohesion: 0.17
+Nodes (12): 二、代码实现验证, 2.1 核心模块完成情况, 2.2 功能实现检查, 2.2.1 数据库初始化, 2.2.2 股票列表获取, 2.2.3 单只股票数据下载, 2.2.4 数据格式转换, 2.2.5 批量插入 (+4 more)
+
+### Community 176 - "Community 176"
+Cohesion: 0.17
+Nodes (11): 执行摘要 - 量化风控与资金管理调研报告, 🎯 调研目标, 1. A股特有风险特征, 2. 风险度量模型推荐, 📊 核心结论, 3. 风险控制策略推荐, 4. 实时监控系统架构, 🗺️ 调研报告结构 (+3 more)
+
+### Community 177 - "Community 177"
+Cohesion: 0.17
+Nodes (11): 🚨 应急响应原则, 1. 快速响应原则, 2. 优先级原则, 📞 联络清单, 3. 数据安全原则, 紧急联络, 阿里云支持, 🔄 事后复盘 (+3 more)
+
+### Community 178 - "Community 178"
+Cohesion: 0.17
+Nodes (12): 1.1 突破检测器, 1. 策略引擎设计, 1.2 信号生成器, 1.3 交易执行器, 🏗️ 技术实现框架, 2.1 价格数据处理, 2.2 成交量分析, 2.3 突破信号识别 (+4 more)
+
+### Community 179 - "Community 179"
+Cohesion: 0.17
+Nodes (12): 3.2.1 职责定义, 3.2.2 约束策略, 3.2.3 探索协议, 3.2.4 输出契约, 3.2.5 避免模式, 3.2 Analyst (Metis) 提示词分析, code:xml (<identity>), code:xml (<constraints>) (+4 more)
+
+### Community 180 - "Community 180"
+Cohesion: 0.17
+Nodes (12): 技能提示词正文开始, code:block88, code:block89, code:block90, code:block91 (检测到威胁直接拦截，返回阻塞信息。), code:block92 (第一个匹配的胜利，避免冲突。), code:block93, code:block94 (+4 more)
+
+### Community 181 - "Community 181"
+Cohesion: 0.17
+Nodes (11): 任务标题, 任务类型, 主目标, 依赖, 验收标准, 期望输出, 上下文（可选）, 原有流程 (+3 more)
+
+### Community 182 - "Community 182"
+Cohesion: 0.17
+Nodes (12): **🔧 技术实现框架**, **1. 技术架构**, **1.1 数据层**, **1.2 处理层**, **1.3 应用层**, **2.1 大数据技术**, **2. 关键技术**, **2.2 AI技术** (+4 more)
+
+### Community 183 - "Community 183"
+Cohesion: 0.17
+Nodes (12): 一、技术指标选股, 成交量突破, 价量配合, 1.2 MACD选股, 1.6 成交量指标选股, 1.7 技术指标选股总结, 方法原理, 常见选股规则 (+4 more)
+
+### Community 189 - "Community 189"
+Cohesion: 0.18
+Nodes (10): 🚀 紧急部署：新任务管理系统, 1. 创建目录结构, 2. 下载部署脚本, 问题, 3. 启动监控, 诸葛亮将重新通知所有将军, 立即行动, code:bash (mkdir -p management/tasks/{pending,assigned,completed,archiv) (+2 more)
+
+### Community 190 - "Community 190"
+Cohesion: 0.18
+Nodes (11): **📈 第三部分：技术分析选股方法（张飞）**, **3.1 技术分析理论基础**, **3.1.1 技术分析三大假设**, **3.1.2 A股技术分析特点**, **3.4 量价关系研究**, **3.4.1 量价配合原则**, **3.4.2 量价背离分析**, **3.5 技术策略设计** (+3 more)
+
+### Community 191 - "Community 191"
+Cohesion: 0.18
+Nodes (10): 📊 **三国量化选股方法整合报告**, **整合结构**, **🏆 报告摘要**, **🚀 当前整合状态**, **已完成部分：**, **正在紧急整理的部分：**, **预计完成时间：**, **🐉 庞统紧急处理中** (+2 more)
+
+### Community 192 - "Community 192"
+Cohesion: 0.18
+Nodes (9): 1. 数据库初始化, 2. 股票列表获取, 3. 单只股票数据下载, 3.2 核心功能, 4. 全市场批量下载, 5. 数据完整性验证, code:python (adapter.initialize_database()), code:python (stock_list = adapter.get_stock_list()) (+1 more)
+
+### Community 193 - "Community 193"
+Cohesion: 0.18
+Nodes (10): 量化策略风控模块, 1. 单票止损（SingleStockRiskControl）, 2. 组合回撤分级风控（PortfolioDrawdownRiskControl）, 功能说明, 3. 黑天鹅过滤（BlackSwanFilter）, 使用示例, 4. 总风控控制器（RiskController）, 设计原则 (+2 more)
+
+### Community 194 - "Community 194"
+Cohesion: 0.18
+Nodes (10): 量化交易系统阿里云高性价比部署方案, 四、方案选择建议, 一、系统核心组件, 部署要点：, 二、高性价比方案对比（按年计算）, 方案一：入门级（适合个人/小团队策略验证）, 方案二：标准级（适合稳定运行的实盘策略）, 方案三：旗舰级（适合多策略、高频交易） (+2 more)
+
+### Community 195 - "Community 195"
+Cohesion: 0.18
+Nodes (11): 1. 监控告警触发, 步骤 1: 检查系统状态, 🔍 问题诊断流程, 2. 快速诊断步骤, 步骤 2: 检查服务状态, 告警来源, 告警级别对应, 步骤 3: 检查日志 (+3 more)
+
+### Community 196 - "Community 196"
+Cohesion: 0.18
+Nodes (10): 任务信息, 任务背景, 目录结构, 快速链接, 核心成果, 下一步, code:block1 (docker-base-image-20260414/), code:bash (ssh admin@192.168.2.154) (+2 more)
+
+### Community 197 - "Community 197"
+Cohesion: 0.18
+Nodes (11): 分层设计思路, 2.1 核心配置文件位置, 2.2 Dockerfile 完整配置, 2.3 entrypoint.sh 启动脚本, 2.4 requirements.txt 依赖配置, 2.5 默认凭证配置, 二、已完成的配置归档, code:dockerfile (FROM python:3.10-slim) (+3 more)
+
+### Community 198 - "Community 198"
+Cohesion: 0.18
+Nodes (11): 模式1：按股票组织（适用于股票分析）, 📁 存储架构设计, 总体结构, 模式2：按日期组织（适用于市场分析）, 存储格式选择, 数据组织模式, code:block1 (minute_kline/), code:block4 (stock_000001/) (+3 more)
+
+### Community 199 - "Community 199"
+Cohesion: 0.18
+Nodes (11): 1. 查询优化策略, 📈 性能优化设计, 分区裁剪, 列式读取, 分批处理, 内存映射, 3. 内存优化, code:python (# 示例：查询特定股票在特定时间段的数据) (+3 more)
+
+### Community 200 - "Community 200"
+Cohesion: 0.18
+Nodes (11): 📝 赵云总结, 🚀 后续执行建议, 立即执行（建议）, 分批执行（根据资源情况）, 自动化维护（建议配置）, 📊 交付成果清单, 技术文档, 数据架构 (+3 more)
+
+### Community 201 - "Community 201"
+Cohesion: 0.18
+Nodes (10): 任务背景, 1.1 dongshuyan/CPA-Dashboard, 1.2 jlcodes99/cockpit-tools, 方案对比总结, 我的决定, 推荐方案：**保持当前修复方案** ✅, 验证结论, 下一步建议 (+2 more)
+
+### Community 202 - "Community 202"
+Cohesion: 0.18
+Nodes (11): 适配结论, 架构概述, 适配结论, 1️⃣ Network-AI（多代理协调层）, 逐个方案分析, 2️⃣ ClawTeam（团队协作 A2A）, 架构概述, 会话模型分析 (+3 more)
+
+### Community 203 - "Community 203"
+Cohesion: 0.18
+Nodes (11): 1. 数据层, 2. 因子层 (四大类因子), 🏗️ 策略架构, 2.1 价值因子, 2.2 质量因子, 2.3 动量因子, 2.4 情绪因子, 5. 组合构建层 (+3 more)
+
+### Community 204 - "Community 204"
+Cohesion: 0.18
+Nodes (11): 策略开发, 数据源, 风控, 基础设施, code:block82, code:block83, code:block84, code:block85 (+3 more)
+
+### Community 205 - "Community 205"
+Cohesion: 0.18
+Nodes (11): **4. 现代因子选股方法研究**, **4.1 质量因子选股法**, **4.1.1 盈利能力因子**, **4.1.2 盈利质量因子**, **4.1.3 财务健康度因子**, **4.1.4 运营效率因子**, **4.2 成长因子选股法**, **4.2.1 营收增长因子** (+3 more)
+
+### Community 206 - "Community 206"
+Cohesion: 0.18
+Nodes (11): **📊 第六部分：实证研究和验证**, **数据准备**, **研究设计**, **评价指标**, **绩效对比**, **最佳实践**, **投资策略框架**, **实施步骤** (+3 more)
+
+### Community 207 - "Community 207"
+Cohesion: 0.2
+Nodes (3): CtaTemplate, PureBreakoutStrategy, 纯突破策略     - N日新高放量突破买入     - 止损：跌破突破日最低价的-5%     - 跟踪止盈：从买入后高点回落10%止盈     - 均线止盈
+
+### Community 208 - "Community 208"
+Cohesion: 0.2
+Nodes (5): DynamicWeightAdjuster, 动态权重调整器     根据每期因子IC计算新权重, 参数:             factor_names: 因子名称列表             window_size: 计算IC的滚动窗口大小（期数，月频调, 更新一期IC数据         参数:             factor_scores: 当期因子得分（横截面）             forward_, 根据历史IC计算新权重         IC越高，权重越大
+
+### Community 209 - "Community 209"
+Cohesion: 0.33
+Nodes (4): main(), MinuteDataSourceTester, 测试Tushare分钟数据接口（需要API Token）, 检查数据质量                  Args:             data: 数据             period: 时间周期
+
+### Community 210 - "Community 210"
+Cohesion: 0.2
+Nodes (6): DataSource, NetworkDataSource, vnpy SQLite数据库数据源          - 数据由赵云负责导入和更新     - 本服务只读取，不写入     - 不会覆盖已有数据, 网络数据源（通过HTTP API获取）          - 对接外部数据API，比如akshare接口     - 实时获取数据，不需要提前导入数据库, 数据源抽象基类          设计原则：     - RPC服务端只读取数据，不写入数据     - 数据写入、同步、更新由赵云负责     - 避免数据覆, SqliteDataSource
+
+### Community 211 - "Community 211"
+Cohesion: 0.27
+Nodes (7): main(), parse_date(), 解析日期：支持两种格式：     1. YYYYMMDD 整数（长度8位），比如 20210101 → 2021年1月1日     2. Unix时间戳（长度1, RPC方法：运行策略回测 - 完全遵循vnpy 4.x官方源码架构     🔥 彻底解决内存泄漏：     - 使用全局引擎，只创建一次，永久重用     -, 主函数     🔥 彻底解决内存泄漏版本：     - 按照官方设计：全局只创建一次引擎，永久重用     - 每次回测只调用clear_data清除数据, run_strategy_backtest(), str_to_interval()
+
+### Community 212 - "Community 212"
+Cohesion: 0.2
+Nodes (10): **📋 目录**, **第一部分：选股方法论综述**, **第二部分：价值投资选股方法（庞统）**, **第三部分：技术分析选股方法（张飞）**, **第四部分：综合选股方法（关羽）**, **第五部分：其他相关选股方法**, **第六部分：整合策略设计与实施指南**, **第七部分：风险管理与绩效评估** (+2 more)
+
+### Community 213 - "Community 213"
+Cohesion: 0.2
+Nodes (9): 系统定位, 核心工作流, 核心特性, 修复记录, 测试结果, 存储位置, 角色分工, code:block1 (创建任务 → 自动commit → git pull → 分配给Agent → 推送到Gitee) (+1 more)
+
+### Community 214 - "Community 214"
+Cohesion: 0.2
+Nodes (9): 核心信条, 1. 稳定胜过一切, 2. 文件驱动简单纯粹, 工作原则, 3. 容错就是一切, 质量标准, 风格, 4. 分布式去中心化 (+1 more)
+
+### Community 215 - "Community 215"
+Cohesion: 0.2
+Nodes (9): 一、项目背景, 二、实施成果, 2.1 核心模块完成情况, 九、项目文件, 十一、已知限制, 十三、技术栈, 十六、致谢, akshare → vn.py 数据适配器系统 - 实施报告 (+1 more)
+
+### Community 216 - "Community 216"
+Cohesion: 0.2
+Nodes (9): 通用风控模块 - 个股利好利空风险监控, 数据获取说明, 设计思路, 作者, 模块说明, 量化规则, 使用方法, 核心功能 (+1 more)
+
+### Community 217 - "Community 217"
+Cohesion: 0.2
+Nodes (9): 通用风控模块 - 个股利好利空风险监控, 数据获取说明, 设计思路, 作者, 模块说明, 量化规则, 使用方法, 核心功能 (+1 more)
+
+### Community 218 - "Community 218"
+Cohesion: 0.2
+Nodes (9): 通用风控模块 - 个股利好利空风险监控, 数据获取说明, 设计思路, 作者, 模块说明, 量化规则, 使用方法, 核心功能 (+1 more)
+
+### Community 219 - "Community 219"
+Cohesion: 0.2
+Nodes (10): 4. 最简单的集成方案, 4.1.1 架构设计, 4.1.2 详细步骤, 4.1.3 配置文件示例, 4.1 推荐方案：Windows 运行 vnpy + QMT，NAS 用于数据存储和 Web 管理, code:bash (pip install vnpy-qmt), code:json ({), code:python (# -*- coding:utf-8 -*-) (+2 more)
+
+### Community 220 - "Community 220"
+Cohesion: 0.2
+Nodes (9): 加拿大云主机中转方案调研, 🎯 方案要点, 推荐方案, 预计成本, 🚀 快速开始, ⚠️ 重要提示, 📝 版本信息, 📄 许可证 (+1 more)
+
+### Community 221 - "Community 221"
+Cohesion: 0.22
+Nodes (10): 六、应急处理预案, 排查步骤, 应急处理, 应对措施, 6. 需要注意的问题, 6.1 法律法规, 6.2 服务器被入侵, 6.2 稳定性 considerations (+2 more)
+
+### Community 222 - "Community 222"
+Cohesion: 0.2
+Nodes (10): 问题1：构建过程中pip下载超时, 问题2：容器启动后无法访问, 问题3：TA-Lib安装失败, 问题4：内存不足导致构建失败, 问题5：权限问题无法访问NAS数据目录, 九、故障排查指南, code:bash (# 使用国内镜像源，在构建前添加国内源), code:dockerfile (# 在系统依赖安装部分添加) (+2 more)
+
+### Community 223 - "Community 223"
+Cohesion: 0.2
+Nodes (9): 调研对象, 对比总结表, 结论与推荐, 推荐方案优先级, 当前最佳选择, 如果需要更完整的团队协作, 已完成工作, 负责人 (+1 more)
+
+### Community 224 - "Community 224"
+Cohesion: 0.2
+Nodes (10): 架构概述, 问题背景, 当前状态, 修复方案, 适配结论, 适配我们需求的分析, 4️⃣ openclaw-a2a-gateway（我们已修复）, 方案四：当前 a2a-gateway（已修复） (+2 more)
+
+### Community 225 - "Community 225"
+Cohesion: 0.2
+Nodes (10): 1. 逻辑简单清晰, 1. 假突破过滤, 2. 执行纪律性强, 2. 仓位控制, 3. 适应性强, 3. 交易执行优化, 🎯 策略优势与风险, ✅ 策略优势 (+2 more)
+
+### Community 226 - "Community 226"
+Cohesion: 0.2
+Nodes (10): 📋 交付物清单, ✅ **已交付的本地存储成果**, ✅ **已交付的分钟数据脚本**, 1. **数据架构**, 1. **核心脚本**, 2. **基础数据**, 2. **技术特性**, 3. **技术工具** (+2 more)
+
+### Community 227 - "Community 227"
+Cohesion: 0.2
+Nodes (10): 📁 **脚本文件清单**, 1. **脚本功能验证**, 2. **核心脚本特性**, 3. **技术特性**, 4. **测试验证结果**, 🚀 第二阶段：分钟数据脚本完成情况, ✅ **脚本开发完成（无Bug验证）**, code:python (# 主要功能类) (+2 more)
+
+### Community 228 - "Community 228"
+Cohesion: 0.2
+Nodes (10): 1. **本地日线数据存储完成** ✅, 1. **技术能力建设**, 📝 赵云总结, ✅ **任务完成确认**, 🎯 **核心价值交付**, 2. **分钟数据脚本开发完成** ✅, 2. **数据资产积累**, 🚀 **赵云待命** (+2 more)
+
+### Community 229 - "Community 229"
+Cohesion: 0.2
+Nodes (9): 2.3 上下文文件注入, 2.3.1 优先级策略, 2.3.2 安全扫描机制, 2.3.3 截断策略, code:python (_CONTEXT_THREAT_PATTERNS = [), code:python (_CONTEXT_INVISIBLE_CHARS = {), code:python (return f"[BLOCKED: {filename} contained potential prompt inj), code:python (CONTEXT_TRUNCATE_HEAD_RATIO = 0.7  # 保留头部70%) (+1 more)
+
+### Community 230 - "Community 230"
+Cohesion: 0.2
+Nodes (9): 2.1 提示词构建架构, 2.1.1 组装流程, 2.1.2 榴单机制, 2.1.3 技能过滤机制, code:block1 (系统提示词 = [身份段] + [平台提示段] + [技能索引段] + [上下文文件段] + [记忆段] + [临时提示), code:block3 (~/.hermes/.skills_prompt_snapshot.json), code:python ({), code:yaml (---) (+1 more)
+
+### Community 231 - "Community 231"
+Cohesion: 0.2
+Nodes (10): 4.4.1 调查协议：五阶段分析, 4.4.2 阶段详解, 4.4.3 自适应严厉度（Adaptive Harshness）, 4.4.4 证据要求, 4.4.5 输出格式, 4.4 Critic 提示词增强（核心）, code:yaml (<Investigation_Protocol>), code:yaml (ESCALATION — Adaptive Harshness:) (+2 more)
+
+### Community 232 - "Community 232"
+Cohesion: 0.2
+Nodes (10): 问题描述, 严重性, 复现步骤, 错误日志, 建议解决方案, 升级建议, code:block80, code:block81 (+2 more)
+
+### Community 233 - "Community 233"
+Cohesion: 0.2
+Nodes (10): **📈 公司分析框架**, **1. 竞争优势分析**, **1.1 护城河类型**, **1.2 竞争优势评估**, **2. 管理层分析**, **2.1 管理层能力评估**, **2.2 管理层诚信评估**, **3.1 内生成长** (+2 more)
+
+### Community 234 - "Community 234"
+Cohesion: 0.2
+Nodes (10): **1.1 利润表分析**, **1.2 资产负债表分析**, **1.3 现金流量表分析**, **1. 财务报表分析**, **2.1 盈利能力指标**, **2.2 偿债能力指标**, **2.3 运营效率指标**, **2.4 成长能力指标** (+2 more)
+
+### Community 235 - "Community 235"
+Cohesion: 0.2
+Nodes (10): **5.1 政策驱动选股法**, **5. 中国特色选股方法研究**, **5.1.1 政策因子分析**, **5.1.2 价值信号提取**, **5.2 国企改革选股法**, **5.2.1 改革价值释放路径**, **5.2.2 投资策略**, **5.3 专精特新选股法** (+2 more)
+
+### Community 236 - "Community 236"
+Cohesion: 0.2
+Nodes (10): **8.1 研究设计**, **8.1.1 数据准备**, **8.1.2 研究方法**, **8.2 实证结果**, **8.2.1 各种选股方法绩效对比**, **8.2.2 各种选股方法特征分析**, **8.3 结论分析**, **8. 实证研究和回测验证** (+2 more)
+
+### Community 237 - "Community 237"
+Cohesion: 0.2
+Nodes (10): **📈 另类数据价值挖掘方法**, **1. 数据获取和处理**, **1.1 数据获取技术**, **1.2 数据处理流程**, **2. 特征工程和建模**, **2.1 特征构建**, **2.2 建模方法**, **3. 价值信号提取和验证** (+2 more)
+
+### Community 238 - "Community 238"
+Cohesion: 0.2
+Nodes (9): 📊 **另类数据在价值投资选股中的应用研究**, **研究时间**, **1. 技术风险**, **2. 市场风险**, **🎯 研究概述**, **📋 风险和控制**, **3. 控制措施**, **研究目标** (+1 more)
+
+### Community 239 - "Community 239"
+Cohesion: 0.2
+Nodes (9): **📊 方法论概述**, **🔄 第六部分：多因子综合选股方法论**, **模型框架**, **优化机制**, **核心思想**, **6.1 综合评分模型**, **6.2 动态优化方法**, **方法特色** (+1 more)
+
+### Community 240 - "Community 240"
+Cohesion: 0.2
+Nodes (10): **🚀 总结**, **科学性**, **全面性**, **适应性**, **实用性**, **理论价值**, **实践价值**, **社会价值** (+2 more)
+
+### Community 241 - "Community 241"
+Cohesion: 0.2
+Nodes (10): **🔬 第一部分：基本面分析选股方法论**, **1.1 财务报表深度分析法**, **1.2 行业地位和竞争优势分析法**, **1.3 管理层和公司治理分析法**, **分析框架**, **关键分析维度**, **行业分析框架**, **竞争优势分析** (+2 more)
+
+### Community 242 - "Community 242"
+Cohesion: 0.2
+Nodes (10): **1. 研究问题**, **📊 实证研究设计**, **2.1 对比实验**, **2. 实验设计**, **2.2 评估方法**, **2.3 稳健性检验**, **3.1 性能提升**, **3.2 方法创新** (+2 more)
+
+### Community 243 - "Community 243"
+Cohesion: 0.2
+Nodes (10): **🇨🇳 第三部分：中国特色价值选股方法**, **政策因子类型**, **价值信号提取**, **改革价值释放路径**, **投资策略**, **企业特征分析**, **估值方法**, **3.1 政策驱动选股** (+2 more)
+
+### Community 244 - "Community 244"
+Cohesion: 0.2
+Nodes (9): **📋 第八部分：风险和控制**, **🎯 调研价值**, **8.1 技术风险**, **8.2 市场风险**, **8.3 控制措施**, **9.1 理论价值**, **9.2 实践价值**, **9.3 社会价值** (+1 more)
+
+### Community 245 - "Community 245"
+Cohesion: 0.2
+Nodes (10): 第三部分：算法交易策略研究, 双均线策略, 趋势跟踪系统, 布林带均值回归, 3.1 趋势跟踪策略, 3.2 均值回归策略, 3.3 配对交易/统计套利, 3.4 高频做市策略 (+2 more)
+
+### Community 246 - "Community 246"
+Cohesion: 0.2
+Nodes (10): 历史波动率, 2.2 均值回归因子, 2.3 波动率因子, 2.5 多因子组合, 第二部分：技术因子有效性研究, ATR（平均真实波幅）, 乖离率BIAS, 波动率 breaks (+2 more)
+
+### Community 247 - "Community 247"
+Cohesion: 0.2
+Nodes (10): 二、趋势跟踪选股, 方法原理, 优点, 方法原理, 优点, 缺点, 2.2 趋势强度选股, 2.3 通道趋势选股 (+2 more)
+
+### Community 248 - "Community 248"
+Cohesion: 0.31
+Nodes (6): GuanYuValueTechStrategy, main(), 关羽 - 价值+技术综合选策略（主策略）     =====================================          完整流程：, 运行完整策略                  Returns:             策略执行结果, 打印订单详情                  Args:             orders: 订单列表, RiskProfile
+
+### Community 249 - "Community 249"
+Cohesion: 0.33
+Nodes (4): BaseStructuredFactor, calculate_raw(), 完整处理流程：原始计算 → 中性化 → 标准化 → rank, 行业中性化 + 市值中性化         参数:             factor_values: 原始因子值             df: 原始数据，
+
+### Community 250 - "Community 250"
+Cohesion: 0.22
+Nodes (3): DynamicICWeightAdjuster, 动态加权模块 根据因子近期IC（信息系数）动态调整权重 IC越高，因子效果越好，权重越大, 动态IC权重调整器     每月更新因子IC，根据IC均值调整权重
+
+### Community 251 - "Community 251"
+Cohesion: 0.22
+Nodes (4): FactorCombiner, 因子合成器 - 把多个因子按权重合成最终得分, 参数:             factors: 因子字典 {因子名称: 因子实例}             weights: 因子权重 {因子名称: 权重},, 合成因子得分         参数:             data: 原始行情财务数据DataFrame         返回:             最
+
+### Community 254 - "Community 254"
+Cohesion: 0.22
+Nodes (5): BarData, LocalCsvDataSource, 本地CSV文件数据源          - 赵云下载好的CSV数据放在data目录     - 本服务只读取，不修改     - 文件名自动匹配：{symbol, CSV格式要求：         必须包含列：trade_date, open, high, low, close, volume, amount, 通过网络API获取数据         可以对接akshare、tushare等网络接口
+
+### Community 255 - "Community 255"
+Cohesion: 0.22
+Nodes (8): 📋 当前项目结构, ✅ 已完成工作, 🔄 进行中工作, 📝 快捷命令, 🎯 项目目标, code:block1 (sanguo_quant_live/), code:bash (./scripts/pull-commit-push.sh "commit message"), sanguo_quant_live 项目状态总结
+
+### Community 256 - "Community 256"
+Cohesion: 0.22
+Nodes (9): 4.5 使用方法, 4.5.1 基本用法：下载单只股票, 4.5.2 批量下载：使用批量下载器（推荐）, 4.5.3 直接批量下载：使用适配器, 4.5.4 命令行运行, code:python (from akshare_vnpy_adapter import AkshareToVnpyAdapter), code:python (from batch_downloader import BatchDownloader), code:python (from akshare_vnpy_adapter import AkshareToVnpyAdapter) (+1 more)
+
+### Community 257 - "Community 257"
+Cohesion: 0.22
+Nodes (8): 数据工程模块验证报告（代码实现完成）, 一、验证概述, 1.1 验证目标, 1.2 执行情况, 五、功能矩阵, 九、安全性验证（静态分析）, 9.1 SQL注入防护, 9.2 数据安全
+
+### Community 258 - "Community 258"
+Cohesion: 0.22
+Nodes (8): 结构化适配动态多因子 质量审核报告, 分模块质量评估, 1. risk_control.py - 风控和择时模块, 2. capital_flow_monitor.py - 资金流向监控, 审核概况, 3. risk_warning_execution.py - 风控预警和执行系统, 4. policy_news_parser.py - 政策消息解析模块, 总体评价
+
+### Community 259 - "Community 259"
+Cohesion: 0.25
+Nodes (7): 📁 目录结构, 目录结构, 因子列表, 动态加权逻辑, 估值择时逻辑, 进阶多因子+动态加权+估值择时 A股量化中低频方案, code:block1 (factors-dynamic-weight-timing-20260327/)
+
+### Community 260 - "Community 260"
+Cohesion: 0.22
+Nodes (9): 2. 因子层, 3. 动态加权层, 4. 择时层, 5. 回测层, 🏗️ 技术架构, code:block3 (因子计算模块), code:block4 (动态加权模块), code:block5 (择时模块) (+1 more)
+
+### Community 261 - "Community 261"
+Cohesion: 0.22
+Nodes (8): 阿里云美国节点代理方案分析, 二、费用估算（以 1核2G 配置为例）, 2.1 云服务器（ECS）费用, 2.2 网络费用, 2.3 总费用估算, 一、阿里云美国节点可用性, 三、与全球厂商对比, 四、注意事项
+
+### Community 262 - "Community 262"
+Cohesion: 0.22
+Nodes (9): 4. 生成密钥, 4.1 创建密钥存储目录, 4.2 生成服务器密钥对, 4.3 生成客户端密钥对, 4.4 查看生成的密钥, code:bash (echo "服务器私钥: $(cat server_privatekey)"), code:bash (mkdir -p /etc/wireguard/keys), code:bash (wg genkey | tee server_privatekey | wg pubkey > server_publi) (+1 more)
+
+### Community 263 - "Community 263"
+Cohesion: 0.22
+Nodes (8): 一、项目背景与目标, 1.1 项目目标, 1.2 整体架构, 六、访问地址汇总（部署完成后）, 十、参考资料, 十一、版本历史, code:block1 (┌───────────────────────────────────────────────────────────), Docker 基础镜像构建配置完整记忆归档
+
+### Community 264 - "Community 264"
+Cohesion: 0.22
+Nodes (9): 7.1 基础版Dockerfile, 7.2 完整版Dockerfile（包含VS Code Server）, 7.3 entrypoint.sh启动脚本, 7.4 requirements.txt依赖文件, code:dockerfile (# 使用Python 3.11基础镜像), code:dockerfile (# 多阶段构建), code:bash (#!/bin/bash), code:txt (# vn.py核心) (+1 more)
+
+### Community 265 - "Community 265"
+Cohesion: 0.22
+Nodes (9): 8.1 基础版docker-compose.yml, 8.2 完整版docker-compose.yml（包含数据库）, 8.3 .env环境变量文件, 8.4 快速启动命令, code:yaml (version: '3.8'), code:yaml (version: '3.8'), code:env (# 基本配置), code:bash (# 1. 创建目录结构) (+1 more)
+
+### Community 266 - "Community 266"
+Cohesion: 0.22
+Nodes (9): 四、集成建议方案, 4.1 推荐架构, 4.2 分阶段实施建议, 项目概况, 会话模型分析, 架构分析, 适配我们需求的可能性, 方案二：ClawTeam（团队协作 A2A） (+1 more)
+
+### Community 267 - "Community 267"
+Cohesion: 0.22
+Nodes (9): 🔧 技术实现, 1. 数据准备, 2. 因子计算, 3. 动态加权, 4. 回测引擎, code:python (# 数据获取模块), code:python (# 因子计算模块), code:python (# 动态加权模块) (+1 more)
+
+### Community 268 - "Community 268"
+Cohesion: 0.22
+Nodes (9): 1. **数据架构建立**, 📊 第一阶段：本地日线数据完成情况, 2. **基础信息数据采集完成**, ✅ **已完成的核心工作**, 3. **技术工具链建立**, 4. **文档体系完善**, 📈 **数据摘要**, code:block1 (sanguo_quant_live/zhaoyun-data/data/) (+1 more)
+
+### Community 269 - "Community 269"
+Cohesion: 0.22
+Nodes (8): 概述, 验证结果, 发现的问题, 问题列表, 建议, 总结, A股基础信息数据质量验证报告, code:json ([)
+
+### Community 270 - "Community 270"
+Cohesion: 0.22
+Nodes (9): 3.7.1 角色定义, 3.7.2 验证协议, 3.7.3 输出契约, 3.7.4 避免模式, 3.7 Critic 提示词分析, code:xml (<identity>), code:xml (<explore>), code:xml (<output_contract>) (+1 more)
+
+### Community 271 - "Community 271"
+Cohesion: 0.22
+Nodes (9): 3.3.1 职责定义, 3.3.2 约束策略, 3.3.3 执行循环, 3.3.4 输出契约, 3.3 Architect (Oracle) 提示词分析, code:xml (<identity>), code:xml (<constraints>), code:xml (<execution_loop>) (+1 more)
+
+### Community 272 - "Community 272"
+Cohesion: 0.22
+Nodes (9): **1.1 贴现现金流模型（DCF）**, **1.2 资产基础估值**, **1. 绝对估值方法**, **📊 价值评估框架**, **2.1 市盈率（P/E）**, **2.2 市净率（P/B）**, **2. 相对估值方法**, **2.3 市销率（P/S）** (+1 more)
+
+### Community 273 - "Community 273"
+Cohesion: 0.22
+Nodes (9): **3. 传统选股方法研究**, **3.1 基本面分析选股法**, **3.1.1 财务报表深度分析**, **3.1.2 行业地位和竞争优势分析**, **3.1.3 管理层和公司治理分析**, **3.2 价值因子选股法**, **3.2.1 估值因子**, **3.2.2 股息率因子** (+1 more)
+
+### Community 274 - "Community 274"
+Cohesion: 0.22
+Nodes (9): **1. 研究问题**, **📊 实证研究设计**, **2.1 数据收集**, **2. 研究方法**, **2.2 研究设计**, **2.3 评价指标**, **3.1 理论贡献**, **3. 预期结果** (+1 more)
+
+### Community 275 - "Community 275"
+Cohesion: 0.22
+Nodes (9): **🔍 第三部分：质量因子选股方法论**, **分析方法**, **分析框架**, **分析维度**, **分析指标**, **3.1 盈利能力选股法**, **3.2 盈利质量选股法**, **3.3 财务健康度选股法** (+1 more)
+
+### Community 276 - "Community 276"
+Cohesion: 0.22
+Nodes (9): **1.1 财报文本分析**, **1.2 电话会议分析**, **1.3 新闻和研报分析**, **1. 自然语言处理（NLP）应用**, **3. 深度学习应用**, **3.1 图像和视频分析**, **3.2 图神经网络应用**, **3.3 时间序列预测** (+1 more)
+
+### Community 277 - "Community 277"
+Cohesion: 0.22
+Nodes (9): 📋 调研大纲, 1.1 技术分析流派概述, 1.2 技术分析有效性辩论, 1.3 A股市场特性对技术分析的影响, 第一部分：研究背景和文献综述, 第六部分：结论和建议, 6.1 研究结论, 6.2 实施建议 (+1 more)
+
+### Community 279 - "Community 279"
+Cohesion: 0.25
+Nodes (4): 市值因子 - 对数市值，越小越好，偏好中小盘, 一个月反转因子 - 近一个月跌幅越大，未来反弹预期越高，所以得分越高, ReversalFactor, SizeFactor
+
+### Community 280 - "Community 280"
+Cohesion: 0.46
+Nodes (7): get_backtest_config(), load_strategy_code(), main(), poll_backtest_result(), print_backtest_result(), run_backtest(), test_api_connection()
+
+### Community 281 - "Community 281"
+Cohesion: 0.29
+Nodes (5): batch_process_factors(), prepare_market_cap_neutral(), 因子中性化批量处理工具 行业中性 + 市值中性, 批量处理所有因子，返回处理后因子DataFrame     参数:         factors: 因子字典         data: 原始数据     返, 预处理，添加log_market_cap列用于中性化     如果已有market_cap列，自动计算对数
+
+### Community 282 - "Community 282"
+Cohesion: 0.29
+Nodes (4): ABC, BaseStrategy, BaseStrategy - 策略基类  策略开发者只需继承此类并实现 generate_signals() 方法。 回测引擎通过统一接口调用策略。  Usag, 策略基类 —— 所有回测策略必须继承此类      子类只需实现 generate_signals(data) -> data_with_signals
+
+### Community 283 - "Community 283"
+Cohesion: 0.25
+Nodes (7): 🏛️ 三国量化项目 - 团队配置, 📦 当前联合测试任务, 🔄 任务目录结构, 👥 完整团队名单, ✅ 已完成的系统建设, 📝 更新记录, code:block1 (management/)
+
+### Community 284 - "Community 284"
+Cohesion: 0.25
+Nodes (7): 功能说明, 代码特点, 使用说明, 预期输出, code:python (import akshare as ak), Python代码实现, zhaoyun_implement 节点产出
+
+### Community 285 - "Community 285"
+Cohesion: 0.25
+Nodes (8): 10.1 完成情况汇总, 10.2 代码质量评价, 10.3 风险评估, 10.4 结论, 十、总结, 代码实现评价: ⭐⭐⭐⭐⭐ (优秀), 测试状态: ⏸️ 待执行, 建议:
+
+### Community 286 - "Community 286"
+Cohesion: 0.25
+Nodes (7): 纯突破量化策略 质量审核报告, 分模块质量评估, 1. risk_control_breakout.py - 突破专属风控, 2. structural_market_risk.py - 结构化行情风控, 审核概况, 3. news_risk_monitor.py - 消息风险监控, 总体评价
+
+### Community 287 - "Community 287"
+Cohesion: 0.25
+Nodes (7): 进阶多因子+动态加权+估值择时 质量审核报告, 分模块质量评估, 1. risk_control.py - 基础风控模块, 2. news_risk_monitor.py - 消息风险监控, 审核概况, 3. structural_market_risk.py - 结构化行情风控, 总体评价
+
+### Community 288 - "Community 288"
+Cohesion: 0.25
+Nodes (8): 客户端配置, Android 客户端, code:block16 ([Interface]), code:bash (# 安装 WireGuard), iOS 客户端, Linux 客户端, macOS 客户端, Windows 客户端
+
+### Community 289 - "Community 289"
+Cohesion: 0.25
+Nodes (8): 1. 1分钟K线数据, 2. 5分钟K线数据, 📊 数据规模评估, 基础参数, 3. 15分钟K线数据, 4. 合计数据量, 数据量计算, 与日线数据对比
+
+### Community 290 - "Community 290"
+Cohesion: 0.25
+Nodes (7): 📋 报告信息, 1. 基础信息数据, 2. 日线行情数据, 🎉 任务完成声明, 3. 财务数据, 📈 数据规模预估, 🏛️ A股数据准备任务 - 最终报告
+
+### Community 291 - "Community 291"
+Cohesion: 0.25
+Nodes (8): 1. **数据架构设计完成**, 🎯 任务目标达成情况, ✅ 已完成的核心工作, 2. **技术工具链建立**, 3. **数据采集流程验证**, 4. **质量保证机制建立**, 🔄 待完成的实施工作, 实际数据采集（需要时间和资源）
+
+### Community 292 - "Community 292"
+Cohesion: 0.25
+Nodes (7): 任务背景, 调研目标, 调研维度, 预期输出, 负责人, 进度, TASK-20260401-a2a-multiagent-research - A2A/多代理方案调研
+
+### Community 293 - "Community 293"
+Cohesion: 0.36
+Nodes (8): 📁 数据需求说明, 3.1 完整性, 3.2 准确性, 3.3 时效性, 3. 数据质量要求, 3. 数据质量要求, 6. 联系人, 9. 联系人
+
+### Community 294 - "Community 294"
+Cohesion: 0.25
+Nodes (8): 1. **配置修改**, 2. **分钟数据采集计划**, 3. **时间预估**, 4. **质量保证措施**, code:python (# 修改收集器的base_dir为NAS路径), code:python (# 采集配置), 🎯 第三阶段：NAS准备和部署计划, **NAS就绪后执行步骤**
+
+### Community 295 - "Community 295"
+Cohesion: 0.25
+Nodes (8): 执行摘要, 主要发现, 输出文件, 验证, 建议, 下一步行动, code:block79, 任务完成：[task-title]
+
+### Community 296 - "Community 296"
+Cohesion: 0.25
+Nodes (8): 原理, 优点, 缺点, 安全性评级, 适用场景, 快速开始, 方案4: PyInstaller (打包工具), code:bash (# 安装)
+
+### Community 297 - "Community 297"
+Cohesion: 0.25
+Nodes (8): 安全性评级, 适用场景, 快速开始, 方案2: Nuitka (编译为C++), 原理, 优点, 缺点, code:bash (# 安装)
+
+### Community 298 - "Community 298"
+Cohesion: 0.25
+Nodes (8): 原理, 优点, 缺点, 安全性评级, 适用场景, 快速开始, 方案3: Cython (编译为C扩展), code:python (# setup.py)
+
+### Community 299 - "Community 299"
+Cohesion: 0.25
+Nodes (8): 方案1: PyArmor (专业加密混淆工具), 原理, 优点, 缺点, 安全性评级, 适用场景, 快速开始, code:bash (# 安装)
+
+### Community 300 - "Community 300"
+Cohesion: 0.25
+Nodes (7): 1. 数据结构映射, 2. 常用指标函数映射, 3. 变量和状态管理, 4. 推荐库, 动量指标 (Momentum), 移动平均 (Moving Averages), Pine Script to Python 通用转换规则
+
+### Community 301 - "Community 301"
+Cohesion: 0.25
+Nodes (8): **分析方法**, **分析维度**, **2.1 估值因子选股法**, **2.2 股息率选股法**, **2.3 现金流选股法**, **📈 第二部分：价值因子选股方法论**, **绝对估值方法**, **相对估值方法**
+
+### Community 302 - "Community 302"
+Cohesion: 0.25
+Nodes (8): **🔧 技术实现框架**, **2.1 模型架构**, **2. 模型开发和训练**, **2.2 训练策略**, **3.1 评估指标**, **3. 评估和优化**, **3.2 优化方法**, code:block2 (输入层)
+
+### Community 303 - "Community 303"
+Cohesion: 0.25
+Nodes (8): **1.1 基本面分析选股**, **1.2 价值因子选股**, **🔬 第一部分：传统价值投资选股方法**, **核心原则**, **分析方法**, **主要价值因子**, **A股适用性调整**, **A股有效性验证**
+
+### Community 304 - "Community 304"
+Cohesion: 0.25
+Nodes (8): 方法原理, 选股规则, 参数常见取值, 优点, 缺点, 2.1 唐奇安通道突破选股, A股适应性评价, code:python (# 买入：价格突破20日新高)
+
+### Community 305 - "Community 305"
+Cohesion: 0.25
+Nodes (8): 方法原理, 1.1 均线系统选股, 常见参数组合, 选股规则示例, 优点, 缺点, A股适应性评价, code:python (# 多头排列选股)
+
+### Community 306 - "Community 306"
+Cohesion: 0.29
+Nodes (4): get_profile(), 初始化仓位管理器                  Args:             risk_profile: 风险偏好配置             tot, 初始化策略                  Args:             risk_profile: 风险偏好 ('conservative', 'ba, 初始化价值筛选器                  Args:             risk_profile: 风险偏好配置
+
+### Community 307 - "Community 307"
+Cohesion: 0.52
+Nodes (6): get_backtest_config(), main(), poll_backtest_result(), print_backtest_result(), run_backtest(), test_api_connection()
+
+### Community 310 - "Community 310"
+Cohesion: 0.33
+Nodes (4): BlackSwanFilter, 黑天鹅过滤：排除ST、跌停、财务造假、低流动性票, 初始化过滤器         :param min_daily_volume: 最小日成交额（亿），低于此排除, 过滤个股         :return: (是否通过过滤, 不通过原因)         True = 可以买入，False = 排除
+
+### Community 311 - "Community 311"
+Cohesion: 0.52
+Nodes (6): check_dependencies(), check_directories(), check_python_version(), check_system_info(), check_virtual_environment(), generate_report()
+
+### Community 313 - "Community 313"
+Cohesion: 0.29
+Nodes (7): 4.6 批量下载详细说明, 4.6.1 断点续传机制, 4.6.2 失败重试机制, 4.6.3 测试模式, 4.6.4 性能指标, code:json ({), code:python (# 下载前50只股票测试)
+
+### Community 314 - "Community 314"
+Cohesion: 0.29
+Nodes (6): 断点续传, 三、技术实现, 3.1 整体架构, 3.3 批量下载器特性, code:block1 (akshare API), code:json ({)
+
+### Community 315 - "Community 315"
+Cohesion: 0.29
+Nodes (6): 三个策略 完整质量审核总报告, 已交付风控模块质量评价, 总体评价, 各策略风控评分, 当前状态, 结论
+
+### Community 316 - "Community 316"
+Cohesion: 0.29
+Nodes (6): 结构化适配动态多因子策略, 核心流程, 参数配置（全部可配置，方便遍历优化）, 方案逻辑, 文件结构, code:block1 (structured-dynamic-factors-20260327/)
+
+### Community 317 - "Community 317"
+Cohesion: 0.29
+Nodes (7): 现象, 应急处理, 场景 2: vn.py 进程崩溃（P0）, code:bash (# 保存系统状态), code:bash (# 检查系统日志中的 OOM), code:bash (# 进入项目目录), code:bash (# 检查进程)
+
+### Community 318 - "Community 318"
+Cohesion: 0.29
+Nodes (7): 🔧 常见问题应急处理, 现象, 应急处理, 场景 4: 数据库连接失败（P1）, code:bash (# 如果使用 RDS), code:bash (# 测试数据库连接), code:bash (# 方案 A: 切换到本地缓存数据)
+
+### Community 319 - "Community 319"
+Cohesion: 0.29
+Nodes (7): 1.1 什么是 miniQMT, 1.2 接口文档, 1.2.1 XtQuant 库, 1.2.2 基本使用示例, 1.2.3 配置要求, 1. miniQMT 概述与接口文档, code:python (from xtquant import xttrader)
+
+### Community 320 - "Community 320"
+Cohesion: 0.29
+Nodes (6): 目录, 附录, A. 参考资源, B. 关键术语, C. 联系信息, miniQMT 集成调研报告
+
+### Community 321 - "Community 321"
+Cohesion: 0.29
+Nodes (7): 3.4 可行的 Workaround 方案, 方案 A：Windows 上运行 vnpy + Docker 仅用于管理, 方案 B：使用 REST API 中间件, 方案 C：使用 SSH 隧道 + 文件共享, code:block5 (┌─────────────────────────────────────┐), code:block6 (┌─────────────────┐         局域网         ┌─────────────────┐), code:block7 (┌─────────────────┐         局域网         ┌─────────────────┐)
+
+### Community 322 - "Community 322"
+Cohesion: 0.33
+Nodes (7): 五、性能风险, 影响因素, 优化建议, 注意事项, 5. 成本估算, 5.1 基础方案成本, 5.2 成本优化建议
+
+### Community 323 - "Community 323"
+Cohesion: 0.29
+Nodes (7): 1. 选择云服务商并创建实例, 服务器端部署, 3.1 安装 WireGuard 软件包, 3.2 启用 IP 转发, 3. 安装 WireGuard, code:bash (apt install wireguard -y), code:bash (echo "net.ipv4.ip_forward=1" >> /etc/sysctl.conf)
+
+### Community 324 - "Community 324"
+Cohesion: 0.29
+Nodes (7): 1. MTU 优化, 性能优化, 2. 使用更快的加密算法, 3. 服务器性能调优, code:block20 ([Interface]), code:block21 (net.core.rmem_max = 2500000), code:bash (sysctl -p /etc/sysctl.d/wireguard.conf)
+
+### Community 325 - "Community 325"
+Cohesion: 0.29
+Nodes (6): 多客户端配置, 添加第二个客户端, 安全加固建议, code:bash (cd /etc/wireguard/keys), code:bash (wg set wg0 peer $(cat client2_publickey) allowed-ips 10.0.0.), WireGuard VPN 详细操作手册
+
+### Community 326 - "Community 326"
+Cohesion: 0.29
+Nodes (7): 失败记录 #1：一次性安装所有依赖导致网络超时, 失败记录 #2：基础镜像选择问题, 失败记录 #3：系统依赖安装问题, 五、构建历史记录, 失败记录 #4：TA-Lib编译问题, 5.1 历史失败记录, 5.2 当前方案总结
+
+### Community 327 - "Community 327"
+Cohesion: 0.29
+Nodes (7): 步骤1：准备NAS存储目录, 2.2 NAS端部署步骤, 步骤2：准备Docker配置文件, 步骤3：部署Docker容器, code:block2 (/volume1/), code:bash (# 数据目录), code:bash (# 进入项目目录)
+
+### Community 328 - "Community 328"
+Cohesion: 0.29
+Nodes (7): 一、方案整体可行性分析, 1.1 技术可行性：✅ 完全可行, 1.2 新架构设计：完全迁移到NAS, 1.3 适用场景, 架构对比, 新架构优势, 核心原则
+
+### Community 329 - "Community 329"
+Cohesion: 0.29
+Nodes (7): 存储架构设计, 1. AKShare（开源免费）, 2. Tushare Pro（商业API）, 3. 聚宽数据（已有基础）, 🛠️ 技术可行性评估, 数据源选择, code:block1 (minute_kline/)
+
+### Community 330 - "Community 330"
+Cohesion: 0.29
+Nodes (7): 🛠️ 实施计划, 第一阶段：基础信息采集（1-2小时）, 第二阶段：日线数据采集（24-48小时）, 第四阶段：质量检查和交付（2-4小时）, 第三阶段：财务数据采集（8-12小时）, code:bash (python3 scripts/data_acquisition/a_stock_basic_info.py), code:bash (python3 scripts/data_quality/data_quality_manager.py)
+
+### Community 331 - "Community 331"
+Cohesion: 0.29
+Nodes (7): 💡 使用说明, 数据访问, 数据更新, 质量监控, code:python (import pandas as pd), code:python (# 使用主控程序更新数据), code:python (# 运行质量检查)
+
+### Community 332 - "Community 332"
+Cohesion: 0.29
+Nodes (7): 🔧 参数配置, 1. 突破参数, 2. 买卖规则参数, 3. 风险控制参数, code:yaml (# configs/breakout_config.yaml), code:yaml (# configs/trading_rules_config.yaml), code:yaml (# configs/risk_config.yaml)
+
+### Community 333 - "Community 333"
+Cohesion: 0.29
+Nodes (7): ✅ 已完成, 🔄 进行中, ⏳ 待开始, 基础信息数据, 5.1 存储格式, 5.2 存储优化, code:python (# data/storage.py)
+
+### Community 334 - "Community 334"
+Cohesion: 0.38
+Nodes (7): 4. 数据使用规范, 4.1 数据读取, 4.2 数据更新, 4.3 数据验证, code:bash (# 运行日线数据下载), code:python (# 数据验证示例), code:python (# data/breakout_detector.py)
+
+### Community 335 - "Community 335"
+Cohesion: 0.29
+Nodes (7): 3.6.1 角色定义, 3.6.2 成功标准, 3.6.3 失败恢复, 3.6 Executor 提示词分析, code:xml (<identity>), code:xml (<execution_loop>), code:xml (<execution_loop>)
+
+### Community 336 - "Community 336"
+Cohesion: 0.29
+Nodes (7): 3.8.1 QA Tester, 3.8.2 Test Engineer, 3.8.3 Debugger, 3.8 其他Agent概要, code:xml (<identity>), code:xml (<identity>), code:xml (<identity>)
+
+### Community 337 - "Community 337"
+Cohesion: 0.29
+Nodes (7): 3.5.1 角色定义, 3.5.2 约束策略, 3.5.3 提问策略, 3.5 Planner (Prometheus) 提示词分析, code:xml (<identity>), code:xml (<constraints>), code:xml (<constraints>)
+
+### Community 338 - "Community 338"
+Cohesion: 0.29
+Nodes (7): 6.1 提示词架构设计, 6.1.1 采用Hermes-Agent的动态组装机制, 6.1.2 采用Oh-My-Codex的结构化提示词设计, code:python (# 三国量化项目的模型适配), code:python (TASK_SPECIFIC_HINTS = {), code:block68 (sanguo_quant_live/), code:markdown (---)
+
+### Community 339 - "Community 339"
+Cohesion: 0.29
+Nodes (7): 原理, 优点, 缺点, 安全性评级, 适用场景, 三、详细方案对比, 方案5: PyArmor + Nuitka 组合 (终极方案)
+
+### Community 340 - "Community 340"
+Cohesion: 0.29
+Nodes (6): 项目目标, 项目进度, 最终报告, 核心结论, 分工, TradingView指标库分析项目 - 20260326
+
+### Community 341 - "Community 341"
+Cohesion: 0.29
+Nodes (7): **1. 第一阶段：数据准备（3月21日-24日）**, **🚀 实施计划**, **2. 第二阶段：特征工程（3月25日-28日）**, **3. 第三阶段：模型开发（3月29日-4月2日）**, **4. 第四阶段：验证评估（4月3日-7日）**, **5. 第五阶段：应用部署（4月8日-12日）**, **6. 第六阶段：报告撰写（4月13日-17日）**
+
+### Community 342 - "Community 342"
+Cohesion: 0.29
+Nodes (7): **🚀 第四部分：成长因子选股方法论**, **分析方法**, **分析维度**, **分析方法**, **4.1 营收增长选股法**, **4.2 盈利增长选股法**, **4.3 市场份额增长选股法**
+
+### Community 343 - "Community 343"
+Cohesion: 0.29
+Nodes (7): **🇨🇳 第五部分：中国特色选股方法论**, **分析框架**, **分析方法**, **分析维度**, **5.1 政策驱动选股法**, **5.2 国企改革选股法**, **5.3 专精特新选股法**
+
+### Community 344 - "Community 344"
+Cohesion: 0.29
+Nodes (7): **主要成长因子**, **2.1 质量因子选股**, **2.2 成长因子选股**, **📈 第二部分：现代因子投资选股方法**, **主要质量因子**, **A股应用特点**, **A股注意事项**
+
+### Community 345 - "Community 345"
+Cohesion: 0.29
+Nodes (6): 🎯 调研目标, 🗓️ 时间计划, 📁 目录结构, 🎯 成功标准, A股量化技术策略研究 - 调研大纲, code:block1 (technical-strategy/)
+
+### Community 346 - "Community 346"
+Cohesion: 0.29
+Nodes (6): 任务说明, 任务要求, 脚本调用格式, 验收标准, code:bash (python /path/to/kanban_update.py JJC-20260401-007 doing "中书省), 📜 圣旨 JJC-20260401-007
+
+### Community 347 - "Community 347"
+Cohesion: 0.6
+Nodes (5): main(), test_data_connection(), test_imports(), test_strategy_import(), test_strategy_initialization()
+
+### Community 348 - "Community 348"
+Cohesion: 0.33
+Nodes (4): BaseSettings, Config, DatabaseSettings, 数据库配置文件 支持 SQLite（方案零）和 PostgreSQL（方案一）
+
+### Community 350 - "Community 350"
+Cohesion: 0.33
+Nodes (6): 第五部分：风险管理与风控体系（司马懿）, 5.1 推荐风控方案, 5.2 实证测试结果, 5.3 极端情景测试, 5.4 A股最优参数推荐, 5.5 性能测试结论
+
+### Community 351 - "Community 351"
+Cohesion: 0.33
+Nodes (5): 未完成任务列表, 添加新任务模板, 注意事项, 任务列表, code:yaml (- task_id: task-YYYYMMDD-001)
+
+### Community 352 - "Community 352"
+Cohesion: 0.33
+Nodes (6): 六、数据格式规范验证（静态分析）, 6.1 vn.py 表结构规范, 6.2 索引规范, 6.3 数据类型验证, code:python (DbBarData:), code:sql (- Primary Key: id (自增)                    ✅)
+
+### Community 353 - "Community 353"
+Cohesion: 0.33
+Nodes (6): 1. 数据层, 🎯 策略概览, 核心特征, 策略目标, 数据需求, code:block2 (数据源模块)
+
+### Community 354 - "Community 354"
+Cohesion: 0.33
+Nodes (6): 现象, 应急处理, 场景 3: 磁盘空间满（P0）, code:bash (# 清理系统临时文件), code:bash (# 查找大于 100MB 的文件), code:bash (df -h)
+
+### Community 355 - "Community 355"
+Cohesion: 0.33
+Nodes (6): 6. 总结与建议, 6.1 主要结论, 6.2 具体建议, 6.2.1 短期方案（推荐立即实施）, 6.2.2 长期优化方案（可选）, 6.2.3 注意事项
+
+### Community 356 - "Community 356"
+Cohesion: 0.33
+Nodes (6): 2.1 vnpy_qmt Gateway, 2.2 基本使用示例, 2.3 配置步骤, 2. vnpy 调用 miniQMT 的方法, code:python (# -*- coding:utf-8 -*-), code:bash (pip install vnpy-qmt)
+
+### Community 357 - "Community 357"
+Cohesion: 0.33
+Nodes (6): 5. 难度与工作量评估, 5.1 难度评估, 5.2 工作量评估, 5.2.1 最小可行方案（推荐）, 5.2.2 完整方案（包含 NAS 集成）, 5.3 风险点
+
+### Community 358 - "Community 358"
+Cohesion: 0.33
+Nodes (6): 基本信息, 价格详情（按需）, 优点, 缺点, 适用场景, Google Cloud Platform (northamerica-northeast1 - Montreal)
+
+### Community 359 - "Community 359"
+Cohesion: 0.33
+Nodes (6): 基本信息, 价格详情（按需）, 优点, 缺点, 适用场景, AWS (ca-central-1 - Montreal)
+
+### Community 360 - "Community 360"
+Cohesion: 0.33
+Nodes (6): 基本信息, 价格详情, 优点, 缺点, 适用场景, DigitalOcean (Toronto)
+
+### Community 361 - "Community 361"
+Cohesion: 0.33
+Nodes (6): 基本信息, 价格详情（按需）, 优点, 缺点, 适用场景, Azure (Canada Central - Toronto)
+
+### Community 362 - "Community 362"
+Cohesion: 0.33
+Nodes (6): 问题1：无法连接, 故障排查, 查看日志, 问题2：连接成功但无法上网, 问题3：速度慢, code:bash (journalctl -u wg-quick@wg0 -f)
+
+### Community 363 - "Community 363"
+Cohesion: 0.33
+Nodes (6): 5.1 创建服务器配置, 5.2 设置配置文件权限, 5. 创建 WireGuard 配置文件, code:bash (nano /etc/wireguard/wg0.conf), code:block12 ([Interface]), code:bash (chmod 600 /etc/wireguard/wg0.conf)
+
+### Community 364 - "Community 364"
+Cohesion: 0.33
+Nodes (6): 三、部署脚本归档, 3.1 脚本位置, 3.2 完整NAS目录结构, 3.3 docker-compose.yml 配置（完整版）, code:block6 (/volume1/stock/sanguo_vnpy/), code:yaml (version: '3.8')
+
+### Community 365 - "Community 365"
+Cohesion: 0.33
+Nodes (5): 📋 任务信息, 🎯 任务需求, 核心需求, 具体要求, 调研任务：A股分钟K线数据准备评估
+
+### Community 366 - "Community 366"
+Cohesion: 0.33
+Nodes (6): 📅 实施计划建议, 第一阶段：架构设计（1-2天）, 第三阶段：测试验证（1-2天）, 第二阶段：工具开发（2-3天）, 第五阶段：质量检查和交付（2-3天）, 第四阶段：分批采集（5-10天）
+
+### Community 367 - "Community 367"
+Cohesion: 0.33
+Nodes (6): 第一阶段：架构验证（1-2周）, 第二阶段：工具链完善（1-2周）, 第四阶段：系统优化和交付（1-2周）, 第三阶段：全量数据采集（2-4周）, 🚀 实施路线图, 第五阶段：维护和更新（持续）
+
+### Community 368 - "Community 368"
+Cohesion: 0.33
+Nodes (6): 🛠️ 工具链设计, 完整性检查, 准确性验证, 3. 质量检查工具, code:python (class CompletenessChecker:), code:python (class AccuracyValidator:)
+
+### Community 369 - "Community 369"
+Cohesion: 0.33
+Nodes (6): 会话模型分析, 项目概况, 架构分析, 适配我们需求的可能性, code:python (def get_session(channel, chat_id, user_id):), 方案三：OpenAkita（轻量 A2A 执行框架）
+
+### Community 370 - "Community 370"
+Cohesion: 0.33
+Nodes (6): 3.1 止盈规则, 3. 卖出规则, 3.2 止损规则, 3.3 强制卖出规则, code:python (# 止盈规则), code:python (# 止损规则)
+
+### Community 371 - "Community 371"
+Cohesion: 0.33
+Nodes (6): 1. 数据访问, 1.1 行情数据, 1.2 财务数据, 1.3 分钟数据 (赵云负责), 3.4 数据清洗规则, code:python (import pandas as pd)
+
+### Community 372 - "Community 372"
+Cohesion: 0.33
+Nodes (5): 📋 方案概览, 🎯 核心目标, 📊 策略特点, 📞 联系人, 进阶多因子+动态加权+估值择时 A股量化中低频方案
+
+### Community 373 - "Community 373"
+Cohesion: 0.33
+Nodes (5): 📊 下载统计, 💾 存储位置, 🔧 数据格式, 📝 后续操作, A股日线数据下载报告
+
+### Community 374 - "Community 374"
+Cohesion: 0.33
+Nodes (6): 3.4.1 两阶段审查策略, 3.4.2 严重性分级, 3.4.3 安全检查清单, 3.4 Code Reviewer 提示词分析, code:xml (<explore>), code:xml (<style>)
+
+### Community 375 - "Community 375"
+Cohesion: 0.33
+Nodes (6): 5.3 上下文传递机制, 5.3.1 Oh-My-Codex: 计划文件驱动, 5.3.2 Oh-My-ClaudeCode: Open Questions机制, code:block57 (.omx/plans/                    # 计划文件目录), code:block58 (.omc/plans/                    # 计划文件目录), code:yaml (**Open Questions (unscored)**: [speculative follow-ups AND l)
+
+### Community 376 - "Community 376"
+Cohesion: 0.33
+Nodes (5): 📚 **价值投资理论框架**, **1. 经典著作**, **📚 经典参考文献**, **2. 学术研究**, **3. 实践案例**
+
+### Community 377 - "Community 377"
+Cohesion: 0.33
+Nodes (5): **1. 理论价值**, **2. 实践价值**, **🎯 研究价值**, **3. 社会价值**, 🤖 **AI驱动的价值发现方法研究**
+
+### Community 378 - "Community 378"
+Cohesion: 0.33
+Nodes (6): **1. 第一阶段：基础研究（3月21日-28日）**, **2. 第二阶段：模型开发（3月29日-4月5日）**, **🚀 实施路线图**, **3. 第三阶段：验证评估（4月6日-12日）**, **4. 第四阶段：应用开发（4月13日-17日）**, **5. 第五阶段：报告撰写（4月18日-20日）**
+
+### Community 379 - "Community 379"
+Cohesion: 0.33
+Nodes (6): 方法原理, 选股规则, 优点, 缺点, 1.4 布林带选股, A股适应性评价
+
+### Community 380 - "Community 380"
+Cohesion: 0.33
+Nodes (6): 优点, 缺点, 1.3 RSI选股, 方法原理, 选股规则, A股适应性评价
+
+### Community 381 - "Community 381"
+Cohesion: 0.33
+Nodes (5): 任务说明, 测试要求, 任务信息, 测试目标, 📝 测试任务 JJC-20260401-009
+
+### Community 383 - "Community 383"
+Cohesion: 0.5
+Nodes (3): initialize_system(), main(), test_database_connection()
+
+### Community 386 - "Community 386"
+Cohesion: 0.4
+Nodes (5): 6.2 Bug修复记录, Bug #1: 数据索引重复导致ValueError, Bug #2: Pandas频率字符串过时, code:python (# 在计算行业分散得分前，确保索引唯一), code:python (# 旧代码)
+
+### Community 387 - "Community 387"
+Cohesion: 0.4
+Nodes (5): 1.1 核心技术指标选股推荐, 1.2 A股市场特殊适应性结论, 1.3 推荐选股流程, 第一部分：技术分析选股方法调研（张飞）, code:block1 (第一步：流动性过滤 → 排除流动性不足)
+
+### Community 388 - "Community 388"
+Cohesion: 0.4
+Nodes (5): **3.2 技术指标体系**, **3.2.1 趋势指标**, **3.2.2 动量指标**, **3.2.3 成交量指标**, **3.2.4 波动率指标**
+
+### Community 389 - "Community 389"
+Cohesion: 0.4
+Nodes (4): 已完成任务列表, 完成记录模板, 任务列表, code:yaml (- task_id: task-YYYYMMDD-001)
+
+### Community 390 - "Community 390"
+Cohesion: 0.4
+Nodes (4): 马岱进度跟踪, 未完成任务, 已完成任务, 修改记录
+
+### Community 391 - "Community 391"
+Cohesion: 0.4
+Nodes (5): 六、性能优化, 6.1 批量写入, 6.2 事务控制, 6.3 网络重试, 6.4 索引优化
+
+### Community 392 - "Community 392"
+Cohesion: 0.4
+Nodes (5): 七、使用方法, 7.1 快速开始, 7.2 编程接口, code:bash (# 1. 进入目录), code:python (from akshare_vnpy_adapter import AkshareToVnpyAdapter)
+
+### Community 393 - "Community 393"
+Cohesion: 0.4
+Nodes (5): 12.1 项目文件清单, 12.2 代码统计, 12.3 技术栈, 十二、附录, code:block5 (data-engineering/)
+
+### Community 394 - "Community 394"
+Cohesion: 0.4
+Nodes (5): 四、网络测试情况, 4.1 测试执行情况, 4.2 建议测试环境, 4.3 测试计划, code:block2 (requests.exceptions.ConnectionError:)
+
+### Community 395 - "Community 395"
+Cohesion: 0.4
+Nodes (5): 🚀 开发路线图, 阶段1: 数据准备 ✅ (赵云负责), 阶段2: 因子开发 ⏳ (量化团队), 阶段3: 策略回测 ⏳ (开发团队), 阶段4: 实盘准备 ⏳ (全体团队)
+
+### Community 396 - "Community 396"
+Cohesion: 0.4
+Nodes (5): 👥 团队分工, 赵云 (数据工程将军), 量化研究团队, 开发团队, 庞统副军师 (项目协调)
+
+### Community 397 - "Community 397"
+Cohesion: 0.4
+Nodes (5): 📋 下一步行动, 中期目标 (1个月内), 立即行动 (今日), 短期目标 (本周内), 长期目标 (3个月内)
+
+### Community 398 - "Community 398"
+Cohesion: 0.4
+Nodes (5): 现象, 应急处理, 场景 1: 实例完全宕机（P0）, code:bash (# 尝试通过阿里云控制台创建快照), code:bash (# 检查服务是否恢复)
+
+### Community 399 - "Community 399"
+Cohesion: 0.4
+Nodes (5): 3. 网络架构可行性分析, 3.1 目标架构, 3.2 关键限制, 3.3 通信机制分析, code:block4 (┌─────────────────┐         局域网         ┌─────────────────┐)
+
+### Community 400 - "Community 400"
+Cohesion: 0.4
+Nodes (5): 创建客户端配置, 激活连接, 第五步：配置客户端（2分钟）, code:bash (sudo systemctl enable wg-quick@wg0), 下载 WireGuard 客户端
+
+### Community 401 - "Community 401"
+Cohesion: 0.4
+Nodes (5): 6.1 启动服务, 6.2 检查服务状态, 6. 启动 WireGuard 服务, code:bash (systemctl enable wg-quick@wg0), code:bash (systemctl status wg-quick@wg0)
+
+### Community 402 - "Community 402"
+Cohesion: 0.4
+Nodes (5): 4.1 配置信息, 4.2 SMB优化配置 (/etc/nsmb.conf), 4.3 自动挂载守护脚本, code:ini ([default]), 四、Mac端NAS自动挂载配置
+
+### Community 403 - "Community 403"
+Cohesion: 0.4
+Nodes (5): 前置检查, 验证访问, 七、部署步骤 Checklist, Mac端准备（已完成）, NAS端部署（需要执行）
+
+### Community 404 - "Community 404"
+Cohesion: 0.4
+Nodes (5): 八、常用命令, code:bash (# 进入项目目录), code:bash (# 查看NAS状态), Mac端NAS管理, NAS端Docker管理
+
+### Community 405 - "Community 405"
+Cohesion: 0.4
+Nodes (5): 问题1：群晖Docker套件启动失败, 问题2：ARM架构镜像兼容性问题, 问题3：NAS存储空间不足, 9.1 群晖Docker相关问题, code:bash (docker system prune -a)
+
+### Community 406 - "Community 406"
+Cohesion: 0.4
+Nodes (5): 部署前检查, 部署步骤, 部署后验证, 安全配置, 十、推荐部署 checklist
+
+### Community 407 - "Community 407"
+Cohesion: 0.4
+Nodes (5): 五、数据存储方案, 5.1 存储架构设计, 5.2 数据库选择, 5.3 数据访问性能, code:block13 (群晖NAS存储架构：)
+
+### Community 408 - "Community 408"
+Cohesion: 0.4
+Nodes (5): 1. 数据量巨大, 技术挑战, 2. 下载时间长, 3. 数据完整性, 4. 存储空间
+
+### Community 409 - "Community 409"
+Cohesion: 0.4
+Nodes (5): 📝 赵云评估结论, ✅ 技术可行性：高, ⚠️ 实施复杂度：中高, 💰 资源需求：中等, 🎯 建议决策
+
+### Community 410 - "Community 410"
+Cohesion: 0.4
+Nodes (5): 数据分区策略, 时间分区, 股票分区, code:block2 (- 按年分区：/year/2021/, /year/2022/, ...), code:block3 (- 按股票代码：/stock/000001/, /stock/000002/, ...)
+
+### Community 411 - "Community 411"
+Cohesion: 0.4
+Nodes (5): 2. 存储优化, 数据压缩, 数据分区, code:python (compression_options = {), code:python (partition_scheme = {)
+
+### Community 412 - "Community 412"
+Cohesion: 0.4
+Nodes (5): 数据索引, 缓存机制, 4. 查询优化工具, code:python (class MinuteDataIndexer:), code:python (class DataCacheManager:)
+
+### Community 413 - "Community 413"
+Cohesion: 0.4
+Nodes (5): 核心功能, 下载策略, 1. 数据下载工具, code:python (class MinuteKlineDownloader:), code:python (class DownloadStrategy:)
+
+### Community 414 - "Community 414"
+Cohesion: 0.4
+Nodes (5): 数据清洗, 数据合并, 2. 数据处理工具, code:python (class MinuteDataProcessor:), code:python (class DataConsolidator:)
+
+### Community 415 - "Community 415"
+Cohesion: 0.4
+Nodes (4): 📋 设计概览, 设计原则, 设计目标, 🏛️ A股分钟K线数据架构设计
+
+### Community 416 - "Community 416"
+Cohesion: 0.4
+Nodes (5): 📊 技术架构概览, 数据存储结构, 技术工具链, code:block1 (sanguo_quant_live/zhaoyun-data/data/), code:block2 (scripts/)
+
+### Community 417 - "Community 417"
+Cohesion: 0.4
+Nodes (5): 1. 数据基础建立, 🎯 任务价值, 2. 技术能力建设, 3. 应用价值, 4. 团队协作价值
+
+### Community 418 - "Community 418"
+Cohesion: 0.4
+Nodes (5): 1. **数据架构设计完成**, ✅ 任务完成确认, 2. **技术工具链建立**, 3. **实施验证通过**, 4. **文档体系完善**
+
+### Community 419 - "Community 419"
+Cohesion: 0.4
+Nodes (5): 🚀 一键执行方案, 完整数据流水线执行, 测试模式验证, code:bash (# 进入赵云工作区), code:bash (# 测试基础信息采集)
+
+### Community 420 - "Community 420"
+Cohesion: 0.4
+Nodes (5): 阶段1: 数据准备 (1周), 阶段2: 策略实现 (2周), 阶段3: 回测验证 (2周), 🚀 开发计划, 阶段4: 实盘准备 (1周)
+
+### Community 421 - "Community 421"
+Cohesion: 0.4
+Nodes (5): 1. 假突破风险, 2. 市场环境风险, 3. 交易成本影响, ⚠️ 策略风险, 4. 流动性风险
+
+### Community 422 - "Community 422"
+Cohesion: 0.4
+Nodes (5): 3.1 数据模块, 3.2 策略模块, 3. 回测系统设计, 3.3 绩效模块, 3.4 报告模块
+
+### Community 423 - "Community 423"
+Cohesion: 0.4
+Nodes (5): 6.1 数据查询接口, 6.2 实时数据流, 6. 数据API接口, code:python (# api/data_api.py), code:python (# api/streaming.py)
+
+### Community 424 - "Community 424"
+Cohesion: 0.4
+Nodes (5): 7. 数据监控, 7.1 数据质量监控, 7.2 性能监控, code:python (# monitoring/performance_monitor.py), code:python (# monitoring/data_monitor.py)
+
+### Community 425 - "Community 425"
+Cohesion: 0.4
+Nodes (5): 阶段1: 数据准备 (已完成), 🚀 开发路线图, 阶段2: 因子开发 (进行中), 阶段3: 策略回测 (待开始), 阶段4: 实盘准备
+
+### Community 426 - "Community 426"
+Cohesion: 0.4
+Nodes (5): 📊 回测设计, 1. 回测周期, 2. 回测参数, 3. 绩效指标, 4. 基准对比
+
+### Community 427 - "Community 427"
+Cohesion: 0.4
+Nodes (5): 短期目标 (1个月内), 📝 下一步行动, 立即行动, 中期目标 (3个月内), 长期目标 (6个月内)
+
+### Community 428 - "Community 428"
+Cohesion: 0.4
+Nodes (5): 1. 数据质量, 2. 因子有效性, 🎯 关键成功因素, 3. 风险控制, 4. 系统稳定性
+
+### Community 429 - "Community 429"
+Cohesion: 0.4
+Nodes (5): 🎯 下一步行动计划, **第一阶段：日线数据完善（立即执行）**, **第二阶段：分钟数据准备（并行执行）**, **第四阶段：数据整合和交付**, **第三阶段：分钟数据采集（NAS就绪后）**
+
+### Community 430 - "Community 430"
+Cohesion: 0.4
+Nodes (5): 📊 资源需求总结, **本地存储资源**, **计算资源**, **时间资源**, **NAS存储资源**
+
+### Community 431 - "Community 431"
+Cohesion: 0.4
+Nodes (4): 🎯 任务完成总结报告, **完成时间线**, 📋 任务概览, **核心任务完成情况**
+
+### Community 432 - "Community 432"
+Cohesion: 0.4
+Nodes (5): 3.1 提示词结构设计, 3.1.1 标准提示词结构, 3.1.2 设计原因, 3. Oh-My-Codex 提示词设计分析, code:xml (---)
+
+### Community 433 - "Community 433"
+Cohesion: 0.4
+Nodes (5): 5.6 消息传递格式, 5.6.1 Analyst消息格式, 5.6.2 Critic消息格式, code:markdown (## Analyst Review: 添加用户删除功能), code:markdown (**VERDICT: REJECT**)
+
+### Community 434 - "Community 434"
+Cohesion: 0.4
+Nodes (5): **1. A股市场特点**, **2. 价值投资在A股的挑战**, **3. 价值投资在A股的机会**, **4. 适应A股的调整策略**, **🎯 在A股市场的应用**
+
+### Community 435 - "Community 435"
+Cohesion: 0.4
+Nodes (5): **⚖️ 风险评估框架**, **1. 经营风险**, **2. 财务风险**, **3. 市场风险**, **4. 风险控制策略**
+
+### Community 436 - "Community 436"
+Cohesion: 0.4
+Nodes (5): **1. 买入决策标准**, **🚀 投资决策框架**, **2. 持有决策标准**, **3. 卖出决策标准**, **4. 仓位管理策略**
+
+### Community 437 - "Community 437"
+Cohesion: 0.4
+Nodes (5): **1. 绝对收益指标**, **📊 绩效评估框架**, **2. 风险调整收益指标**, **3. 风险指标**, **4. 归因分析**
+
+### Community 438 - "Community 438"
+Cohesion: 0.4
+Nodes (5): **2. 研究方法论**, **2.1 研究框架**, **2.2 数据来源**, **2.3 研究设计**, **2.4 评价指标**
+
+### Community 439 - "Community 439"
+Cohesion: 0.4
+Nodes (5): 4.1 交易成本分析, 4.2 流动性分析, 4.3 Tick数据高频特征, 4.4 T+1制度影响, 第四部分：A股市场微观结构研究
+
+### Community 440 - "Community 440"
+Cohesion: 0.4
+Nodes (5): 第五部分：实证研究方案, 5.1 数据准备, 5.2 回测框架, 5.3 绩效评估指标, 5.4 风险控制
+
+### Community 441 - "Community 441"
+Cohesion: 0.4
+Nodes (5): 2.1 趋势跟踪因子, 移动平均线系列, 动量因子, 布林带（Bollinger Bands）, MACD系列
+
+### Community 442 - "Community 442"
+Cohesion: 0.4
+Nodes (5): 方法原理, 优点, 缺点, 1.5 KDJ选股, A股适应性评价
+
+### Community 447 - "Community 447"
+Cohesion: 0.5
+Nodes (4): 4.7 数据完整性验证, 4.7.1 验证结果示例, 4.7.2 验证内容, code:python ({)
+
+### Community 448 - "Community 448"
+Cohesion: 0.5
+Nodes (4): 1.4.3 策略2：布林带下轨+趋势策略, code:python (1. 股价触及或跌破布林带下轨（超卖）), code:python (1. 收盘价站上布林带中轨（回归均值）), code:python (bb_period = 20           # 布林带周期)
+
+### Community 449 - "Community 449"
+Cohesion: 0.5
+Nodes (4): 1.4.7 使用方法, code:bash (cd /Users/chufeng/.openclaw/workspace-pangtong/sanguo_quant_), code:python (from technical_selection_strategies_backtest import *), code:python (data = pd.DataFrame({)
+
+### Community 450 - "Community 450"
+Cohesion: 0.5
+Nodes (4): 1.4.4 策略3：唐奇安通道突破策略, code:python (1. 收盘价跌破10日唐奇安通道下轨), code:python (channel_period = 20.     # 突破检测周期), code:python (1. 收盘价突破20日唐奇安通道上轨)
+
+### Community 451 - "Community 451"
+Cohesion: 0.5
+Nodes (4): **2.5 投资策略设计**, **2.5.1 三层配置策略**, **2.5.2 实施步骤**, code:block2 (基础配置 (70%)：综合得分选股)
+
+### Community 452 - "Community 452"
+Cohesion: 0.5
+Nodes (4): **2.6 风险控制方法**, **2.6.1 个股风险控制**, **2.6.2 组合风险控制**, **2.6.3 市场风险控制**
+
+### Community 453 - "Community 453"
+Cohesion: 0.5
+Nodes (4): **2.4 估值模型研究与应用**, **2.4.1 绝对估值模型**, **2.4.2 相对估值模型**, **2.4.3 综合估值模型**
+
+### Community 454 - "Community 454"
+Cohesion: 0.5
+Nodes (4): **3.3 图表形态分析**, **3.3.1 反转形态**, **3.3.2 持续形态**, **3.3.3 特殊形态**
+
+### Community 455 - "Community 455"
+Cohesion: 0.5
+Nodes (4): **3.6 技术分析风险管理**, **3.6.1 信号确认机制**, **3.6.2 止损设置方法**, **3.6.3 仓位管理策略**
+
+### Community 456 - "Community 456"
+Cohesion: 0.5
+Nodes (4): 10.1 数据规模, 10.2 数据库大小, 10.3 下载时间预估, 十、性能预估
+
+### Community 457 - "Community 457"
+Cohesion: 0.5
+Nodes (4): 八、测试与验证, 8.1 单元测试, 8.2 完整流程测试, 8.3 数据验证项
+
+### Community 458 - "Community 458"
+Cohesion: 0.5
+Nodes (4): 15.1 完成情况, 15.2 代码质量, 15.3 项目价值, 十五、总结
+
+### Community 459 - "Community 459"
+Cohesion: 0.5
+Nodes (4): 七、性能优化验证（静态分析）, 7.1 批量写入, 7.2 事务控制, 7.3 索引优化
+
+### Community 460 - "Community 460"
+Cohesion: 0.5
+Nodes (4): 八、错误处理验证（静态分析）, 8.1 异常捕获, 8.2 重试机制, 8.3 容错设计
+
+### Community 461 - "Community 461"
+Cohesion: 0.5
+Nodes (4): 短期执行（1周内）, 中期执行（1个月内）, 十一、下一步行动, 立即执行（网络恢复后）
+
+### Community 462 - "Community 462"
+Cohesion: 0.5
+Nodes (4): 三、代码质量验证, 3.1 代码结构, 3.2 文档完整性, 3.3 最佳实践
+
+### Community 463 - "Community 463"
+Cohesion: 0.5
+Nodes (4): 📊 回测计划, 回测周期, 回测参数, 绩效指标
+
+### Community 464 - "Community 464"
+Cohesion: 0.5
+Nodes (4): 📞 沟通协调, 定期会议, 沟通渠道, 交付物要求
+
+### Community 465 - "Community 465"
+Cohesion: 0.5
+Nodes (4): 📋 应急响应检查清单, 响应前检查, 响应中检查, 响应后检查
+
+### Community 466 - "Community 466"
+Cohesion: 0.5
+Nodes (4): 选择建议, 个人使用/测试, 企业使用/生产环境, 需要支付宝
+
+### Community 467 - "Community 467"
+Cohesion: 0.5
+Nodes (4): 十三、结论与建议, 13.1 可行性总结, 13.2 核心收益, 13.3 最终推荐
+
+### Community 468 - "Community 468"
+Cohesion: 0.5
+Nodes (4): 六、网络访问方案, 6.1 访问方式对比, 6.2 Mac mini访问体验, 6.3 网络安全建议
+
+### Community 469 - "Community 469"
+Cohesion: 0.5
+Nodes (4): 💰 资源需求, 计算资源, 软件资源, 数据源成本
+
+### Community 470 - "Community 470"
+Cohesion: 0.5
+Nodes (4): ⏱️ 时间预估, 乐观估计, 保守估计, 分阶段时间
+
+### Community 471 - "Community 471"
+Cohesion: 0.5
+Nodes (4): 📈 风险评估, 高风险, 中风险, 低风险
+
+### Community 472 - "Community 472"
+Cohesion: 0.5
+Nodes (4): 🎯 建议方案, 推荐方案：分步实施，优先验证, 数据采集策略, 技术选型建议
+
+### Community 473 - "Community 473"
+Cohesion: 0.5
+Nodes (4): 📋 数据质量保证, 完整性检查, 准确性验证, 更新机制
+
+### Community 474 - "Community 474"
+Cohesion: 0.5
+Nodes (4): 项目概况, 架构分析, 适配我们需求的可能性, 方案一：Network-AI（多代理协调层）
+
+### Community 475 - "Community 475"
+Cohesion: 0.5
+Nodes (4): 1. 开发优先级, 2. 测试策略, 3. 优化建议, 📋 实施建议
+
+### Community 476 - "Community 476"
+Cohesion: 0.5
+Nodes (4): 1. 回测周期, 2. 回测参数, 📈 回测设计, 3. 绩效指标
+
+### Community 477 - "Community 477"
+Cohesion: 0.5
+Nodes (4): ✅ 已完成, 🔄 进行中 (赵云负责), ⏳ 待开始, 8. 当前状态
+
+### Community 478 - "Community 478"
+Cohesion: 0.5
+Nodes (4): 1. 收益目标, 📈 预期效果, 2. 风险控制目标, 3. 稳定性目标
+
+### Community 479 - "Community 479"
+Cohesion: 0.5
+Nodes (4): 3. 动态加权层, 3.1 权重调整机制, 3.2 动态参数, code:block2 (IF 市场估值处于历史低位)
+
+### Community 480 - "Community 480"
+Cohesion: 0.5
+Nodes (4): 1. 事前风控, 🛡️ 风险控制, 2. 事中风控, 3. 事后风控
+
+### Community 481 - "Community 481"
+Cohesion: 0.5
+Nodes (4): 📋 分工建议, 赵云 (数据工程将军), 量化研究团队, 开发团队
+
+### Community 482 - "Community 482"
+Cohesion: 0.5
+Nodes (4): 4. 择时层, 4.1 估值择时, 4.2 仓位管理, code:block3 (仓位 = 基础仓位 × 估值调整系数 × 趋势确认系数)
+
+### Community 483 - "Community 483"
+Cohesion: 0.5
+Nodes (4): 1. 数据资源, 🧮 资源需求, 2. 计算资源, 3. 开发资源
+
+### Community 484 - "Community 484"
+Cohesion: 0.5
+Nodes (4): 长期策略（1年以上）, 短期策略（1-3个月）, 七、实施建议, 中期策略（3-12个月）
+
+### Community 485 - "Community 485"
+Cohesion: 0.5
+Nodes (4): **1. 基本概念**, **2. 核心原则**, **🎯 价值投资核心理念**, **3. 主要流派**
+
+### Community 486 - "Community 486"
+Cohesion: 0.5
+Nodes (4): **🏢 行业分析框架**, **1. 行业生命周期分析**, **2. 行业竞争结构分析**, **3. 行业关键成功因素**
+
+### Community 487 - "Community 487"
+Cohesion: 0.5
+Nodes (4): **1. 数据获取工具**, **🔧 研究工具和方法**, **2. 分析计算工具**, **3. 研究方法**
+
+### Community 488 - "Community 488"
+Cohesion: 0.5
+Nodes (4): **3.1 数据来源**, **3.2 价值信号**, **3.3 应用方法**, **3. 专利和技术数据**
+
+### Community 489 - "Community 489"
+Cohesion: 0.5
+Nodes (4): **1. 社交媒体情绪数据**, **1.1 数据来源**, **1.2 价值信号**, **1.3 应用方法**
+
+### Community 490 - "Community 490"
+Cohesion: 0.5
+Nodes (4): **1. 学术价值**, **2. 实践价值**, **🎯 研究价值**, **3. 社会价值**
+
+### Community 491 - "Community 491"
+Cohesion: 0.5
+Nodes (4): **1. 技术挑战**, **2. 业务挑战**, **📋 挑战和解决方案**, **3. 解决方案**
+
+### Community 492 - "Community 492"
+Cohesion: 0.5
+Nodes (4): **2. 机器学习应用**, **2.1 价值信号识别**, **2.2 估值模型优化**, **2.3 风险预测和控制**
+
+### Community 493 - "Community 493"
+Cohesion: 0.5
+Nodes (4): **1. 数据准备和处理**, **1.1 多模态数据整合**, **1.2 数据预处理**, code:block1 (文本数据)
+
+### Community 494 - "Community 494"
+Cohesion: 0.5
+Nodes (4): **🎯 研究概述**, **研究时间**, **研究目标**, **研究意义**
+
+### Community 495 - "Community 495"
+Cohesion: 0.5
+Nodes (4): **🎯 调研概述**, **调研时间**, **调研目标**, **调研范围**
+
+### Community 496 - "Community 496"
+Cohesion: 0.5
+Nodes (4): **🚀 第七部分：实施路线图**, **7.1 短期计划（3月21日-28日）**, **7.2 中期计划（3月29日-4月12日）**, **7.3 长期计划（4月13日-17日）**
+
+### Community 497 - "Community 497"
+Cohesion: 0.5
+Nodes (4): 成交量突破, 2.4 成交量因子, OBV（能量潮）, VWAP（成交量加权平均价）
+
+### Community 498 - "Community 498"
+Cohesion: 0.5
+Nodes (4): 八、总结和建议, 8.1 推荐选股方法排名, 8.2 实施建议, 8.3 下一步研究
+
+### Community 502 - "Community 502"
+Cohesion: 0.67
+Nodes (3): 短期（1-2周）, 中期（1个月）, 十二、下一步计划
+
+### Community 504 - "Community 504"
+Cohesion: 0.67
+Nodes (3): 四、数据格式映射, 4.1 akshare → vn.py 字段映射, 4.2 交易所映射
+
+### Community 505 - "Community 505"
+Cohesion: 0.67
+Nodes (3): 14.1 风险识别, 14.2 对策实施, 十四、风险与对策
+
+### Community 506 - "Community 506"
+Cohesion: 0.67
+Nodes (3): 📝 相关文档, 核心文档, 外部文档
+
+### Community 507 - "Community 507"
+Cohesion: 0.67
+Nodes (3): 数据结构, 基础信息数据字段, 日线数据字段
+
+## Knowledge Gaps
+- **3419 isolated node(s):** `初始化批量下载器          Args:             db_path: 数据库路径             progress_file: 进度`, `更新进度          Args:             code: 股票代码             status: 状态 'success' | 'f`, `批量下载          Args:             start_date: 开始日期             end_date: 结束日期`, `akshare数据转vn.py SQLite数据库适配器`, `初始化适配器          Args:             db_path: vn.py SQLite数据库路径` (+3414 more)
+  These have ≤1 connection - possible missing edges or undocumented components.
+- **48 thin communities (<3 nodes) omitted from report** — run `graphify query` to explore isolated nodes.
+
+## Suggested Questions
+_Questions this graph is uniquely positioned to answer:_
+
+- **Why does `BaseStructuredFactor` connect `Community 249` to `Community 113`, `Community 278`, `Community 279`, `Community 121`, `Community 282`, `Community 443`?**
+  _High betweenness centrality (0.005) - this node is a cross-community bridge._
+- **Why does `StructuredDynamicMultiFactorStrategy` connect `Community 93` to `Community 281`, `Community 444`, `Community 278`, `Community 207`?**
+  _High betweenness centrality (0.005) - this node is a cross-community bridge._
+- **Why does `MultiFactorDynamicStrategy` connect `Community 99` to `Community 41`, `Community 106`, `Community 207`, `Community 81`, `Community 309`, `Community 29`?**
+  _High betweenness centrality (0.003) - this node is a cross-community bridge._
+- **Are the 16 inferred relationships involving `RealtimeRiskPanel` (e.g. with `RealTimeRiskCalculator` and `RiskMetrics`) actually correct?**
+  _`RealtimeRiskPanel` has 16 INFERRED edges - model-reasoned connections that need verification._
+- **Are the 8 inferred relationships involving `RealTimeRiskMonitor` (e.g. with `RiskMetrics` and `RealTimeRiskCalculator`) actually correct?**
+  _`RealTimeRiskMonitor` has 8 INFERRED edges - model-reasoned connections that need verification._
+- **Are the 20 inferred relationships involving `RiskController` (e.g. with `BaseFactor` and `PEFactor`) actually correct?**
+  _`RiskController` has 20 INFERRED edges - model-reasoned connections that need verification._
+- **What connects `初始化批量下载器          Args:             db_path: 数据库路径             progress_file: 进度`, `更新进度          Args:             code: 股票代码             status: 状态 'success' | 'f`, `批量下载          Args:             start_date: 开始日期             end_date: 结束日期` to the rest of the system?**
+  _3419 weakly-connected nodes found - possible documentation gaps or missing edges._
\ No newline at end of file
diff --git a/graphify-out/cache/ast/022bcaca28a6413d02afdf7b1174016c5f0c1c77c9e4a97c409cd77b5a9b1be7.json b/graphify-out/cache/ast/022bcaca28a6413d02afdf7b1174016c5f0c1c77c9e4a97c409cd77b5a9b1be7.json
new file mode 100644
index 000000000..fb647fe27
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+++ b/graphify-out/cache/ast/022bcaca28a6413d02afdf7b1174016c5f0c1c77c9e4a97c409cd77b5a9b1be7.json
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\ No newline at end of file
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"archive_final_five_generals_multi_factor_stock_selection_report_codeblock_8", "label": "code:python (bb_period = 20           # \u5e03\u6797\u5e26\u5468\u671f)", "file_type": "document", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/archive/FINAL_FIVE_GENERALS_MULTI_FACTOR_STOCK_SELECTION_REPORT.md", "source_location": "L145"}, {"id": "archive_final_five_generals_multi_factor_stock_selection_report_1_4_4_3", "label": "1.4.4 \u7b56\u75653\uff1a\u5510\u5947\u5b89\u901a\u9053\u7a81\u7834\u7b56\u7565", "file_type": "document", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/archive/FINAL_FIVE_GENERALS_MULTI_FACTOR_STOCK_SELECTION_REPORT.md", "source_location": "L157"}, {"id": "archive_final_five_generals_multi_factor_stock_selection_report_codeblock_9", "label": "code:python (1. \u6536\u76d8\u4ef7\u7a81\u783420\u65e5\u5510\u5947\u5b89\u901a\u9053\u4e0a\u8f68)", "file_type": "document", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/archive/FINAL_FIVE_GENERALS_MULTI_FACTOR_STOCK_SELECTION_REPORT.md", "source_location": "L163"}, {"id": "archive_final_five_generals_multi_factor_stock_selection_report_codeblock_10", "label": "code:python (1. \u6536\u76d8\u4ef7\u8dcc\u783410\u65e5\u5510\u5947\u5b89\u901a\u9053\u4e0b\u8f68)", "file_type": "document", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/archive/FINAL_FIVE_GENERALS_MULTI_FACTOR_STOCK_SELECTION_REPORT.md", "source_location": "L169"}, {"id": "archive_final_five_generals_multi_factor_stock_selection_report_codeblock_11", "label": "code:python (channel_period = 20.     # \u7a81\u7834\u68c0\u6d4b\u5468\u671f)", "file_type": "document", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/archive/FINAL_FIVE_GENERALS_MULTI_FACTOR_STOCK_SELECTION_REPORT.md", "source_location": "L175"}, {"id": "archive_final_five_generals_multi_factor_stock_selection_report_1_4_5", "label": "1.4.5 \u6280\u672f\u6307\u6807\u8ba1\u7b97\u5668", "file_type": "document", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/archive/FINAL_FIVE_GENERALS_MULTI_FACTOR_STOCK_SELECTION_REPORT.md", "source_location": "L187"}, {"id": "archive_final_five_generals_multi_factor_stock_selection_report_codeblock_12", "label": "code:python (# \u79fb\u52a8\u5e73\u5747)", "file_type": "document", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/archive/FINAL_FIVE_GENERALS_MULTI_FACTOR_STOCK_SELECTION_REPORT.md", "source_location": "L191"}, {"id": "archive_final_five_generals_multi_factor_stock_selection_report_1_4_6", "label": "1.4.6 \u56de\u6d4b\u5f15\u64ce\u8bf4\u660e", "file_type": "document", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/archive/FINAL_FIVE_GENERALS_MULTI_FACTOR_STOCK_SELECTION_REPORT.md", "source_location": "L213"}, {"id": "archive_final_five_generals_multi_factor_stock_selection_report_codeblock_13", "label": "code:python (BacktestEngine(initial_capital=100000.0)  # \u521d\u59cb\u8d44\u91d1)", "file_type": "document", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/archive/FINAL_FIVE_GENERALS_MULTI_FACTOR_STOCK_SELECTION_REPORT.md", "source_location": "L226"}, {"id": "archive_final_five_generals_multi_factor_stock_selection_report_codeblock_14", "label": "code:python (result = engine.backtest(data, strategy, strategy_name))", "file_type": "document", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/archive/FINAL_FIVE_GENERALS_MULTI_FACTOR_STOCK_SELECTION_REPORT.md", "source_location": "L231"}, {"id": "archive_final_five_generals_multi_factor_stock_selection_report_codeblock_15", "label": "code:python (result.total_return      # \u603b\u6536\u76ca\u7387)", "file_type": "document", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/archive/FINAL_FIVE_GENERALS_MULTI_FACTOR_STOCK_SELECTION_REPORT.md", "source_location": "L236"}, {"id": "archive_final_five_generals_multi_factor_stock_selection_report_1_4_7", "label": "1.4.7 \u4f7f\u7528\u65b9\u6cd5", "file_type": "document", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/archive/FINAL_FIVE_GENERALS_MULTI_FACTOR_STOCK_SELECTION_REPORT.md", "source_location": "L251"}, {"id": "archive_final_five_generals_multi_factor_stock_selection_report_codeblock_16", "label": "code:bash (cd /Users/chufeng/.openclaw/workspace-pangtong/sanguo_quant_)", "file_type": "document", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/archive/FINAL_FIVE_GENERALS_MULTI_FACTOR_STOCK_SELECTION_REPORT.md", "source_location": "L254"}, {"id": "archive_final_five_generals_multi_factor_stock_selection_report_codeblock_17", "label": "code:python (from technical_selection_strategies_backtest import *)", "file_type": "document", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/archive/FINAL_FIVE_GENERALS_MULTI_FACTOR_STOCK_SELECTION_REPORT.md", "source_location": "L260"}, {"id": "archive_final_five_generals_multi_factor_stock_selection_report_codeblock_18", "label": "code:python (data = pd.DataFrame({)", "file_type": "document", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/archive/FINAL_FIVE_GENERALS_MULTI_FACTOR_STOCK_SELECTION_REPORT.md", "source_location": "L309"}, {"id": "archive_final_five_generals_multi_factor_stock_selection_report_1_4_8", "label": "1.4.8 \u4ee3\u7801\u8d28\u91cf\u4fdd\u8bc1", "file_type": "document", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/archive/FINAL_FIVE_GENERALS_MULTI_FACTOR_STOCK_SELECTION_REPORT.md", "source_location": "L321"}, {"id": "archive_final_five_generals_multi_factor_stock_selection_report_1_4_9", "label": "1.4.9 \u6d4b\u8bd5\u793a\u4f8b\u8f93\u51fa", "file_type": "document", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/archive/FINAL_FIVE_GENERALS_MULTI_FACTOR_STOCK_SELECTION_REPORT.md", "source_location": "L338"}, {"id": "archive_final_five_generals_multi_factor_stock_selection_report_codeblock_19", "label": "code:block19 (============================================================)", "file_type": "document", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/archive/FINAL_FIVE_GENERALS_MULTI_FACTOR_STOCK_SELECTION_REPORT.md", "source_location": "L342"}, {"id": "archive_final_five_generals_multi_factor_stock_selection_report_1_4_10", "label": "1.4.10 \u540e\u7eed\u6539\u8fdb\u5efa\u8bae", "file_type": "document", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/archive/FINAL_FIVE_GENERALS_MULTI_FACTOR_STOCK_SELECTION_REPORT.md", "source_location": "L365"}, {"id": "archive_final_five_generals_multi_factor_stock_selection_report_376", "label": "\u7b2c\u4e8c\u90e8\u5206\uff1a\u4ef7\u503c+\u6280\u672f\u7efc\u5408\u9009\u80a1\uff08\u5173\u7fbd\uff0c\u98ce\u9669\u7ba1\u7406\u89c6\u89d2\uff09", "file_type": "document", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/archive/FINAL_FIVE_GENERALS_MULTI_FACTOR_STOCK_SELECTION_REPORT.md", "source_location": "L376"}, {"id": "archive_final_five_generals_multi_factor_stock_selection_report_2_1", "label": "2.1 \u4ee3\u7801\u5b9e\u73b0\u4e0e\u67b6\u6784\u8bbe\u8ba1", "file_type": "document", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/archive/FINAL_FIVE_GENERALS_MULTI_FACTOR_STOCK_SELECTION_REPORT.md", "source_location": "L378"}, {"id": "archive_final_five_generals_multi_factor_stock_selection_report_codeblock_20", "label": "code:block20 (GuanYuValueTechStrategy (\u4e3b\u7b56\u7565\u7c7b))", "file_type": "document", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/archive/FINAL_FIVE_GENERALS_MULTI_FACTOR_STOCK_SELECTION_REPORT.md", "source_location": "L383"}, {"id": "archive_final_five_generals_multi_factor_stock_selection_report_codeblock_21", "label": "code:block21 (1. \u4ef7\u503c\u7b5b\u9009 (ValueFilter))", "file_type": "document", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/archive/FINAL_FIVE_GENERALS_MULTI_FACTOR_STOCK_SELECTION_REPORT.md", "source_location": "L392"}, {"id": "archive_final_five_generals_multi_factor_stock_selection_report_2_2", "label": "2.2 \u4e09\u79cd\u9009\u80a1\u65b9\u6cd5\u5bf9\u6bd4", "file_type": "document", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/archive/FINAL_FIVE_GENERALS_MULTI_FACTOR_STOCK_SELECTION_REPORT.md", "source_location": "L413"}, {"id": "archive_final_five_generals_multi_factor_stock_selection_report_2_3", "label": "2.3 \u6838\u5fc3\u6a21\u5757\u5b9e\u73b0\u7ec6\u8282", "file_type": "document", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/archive/FINAL_FIVE_GENERALS_MULTI_FACTOR_STOCK_SELECTION_REPORT.md", "source_location": "L421"}, {"id": "archive_final_five_generals_multi_factor_stock_selection_report_2_3_1_riskprofile", "label": "2.3.1 RiskProfile - \u98ce\u9669\u504f\u597d\u914d\u7f6e", "file_type": "document", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/archive/FINAL_FIVE_GENERALS_MULTI_FACTOR_STOCK_SELECTION_REPORT.md", "source_location": "L423"}, {"id": "archive_final_five_generals_multi_factor_stock_selection_report_codeblock_22", "label": "code:python (class RiskProfile:)", "file_type": "document", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/archive/FINAL_FIVE_GENERALS_MULTI_FACTOR_STOCK_SELECTION_REPORT.md", "source_location": "L425"}, {"id": "archive_final_five_generals_multi_factor_stock_selection_report_codeblock_23", "label": "code:python (from guanyu_value_tech_strategy import RiskProfile)", "file_type": "document", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/archive/FINAL_FIVE_GENERALS_MULTI_FACTOR_STOCK_SELECTION_REPORT.md", "source_location": "L464"}, {"id": "archive_final_five_generals_multi_factor_stock_selection_report_2_3_2_valuefilter", "label": "2.3.2 ValueFilter - \u4ef7\u503c\u7b5b\u9009\u5668", "file_type": "document", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/archive/FINAL_FIVE_GENERALS_MULTI_FACTOR_STOCK_SELECTION_REPORT.md", "source_location": "L472"}, {"id": "archive_final_five_generals_multi_factor_stock_selection_report_codeblock_24", "label": "code:python (# \u6392\u9664\u6761\u4ef6\uff1a)", "file_type": "document", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/archive/FINAL_FIVE_GENERALS_MULTI_FACTOR_STOCK_SELECTION_REPORT.md", "source_location": "L481"}, {"id": "archive_final_five_generals_multi_factor_stock_selection_report_codeblock_25", "label": "code:python (# \u7b5b\u9009\u6761\u4ef6\uff1a)", "file_type": "document", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/archive/FINAL_FIVE_GENERALS_MULTI_FACTOR_STOCK_SELECTION_REPORT.md", "source_location": "L490"}, {"id": "archive_final_five_generals_multi_factor_stock_selection_report_codeblock_26", "label": "code:python (# \u5f85\u8865\u5145\u8d22\u52a1\u6570\u636e\u63a5\u53e3)", "file_type": "document", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/archive/FINAL_FIVE_GENERALS_MULTI_FACTOR_STOCK_SELECTION_REPORT.md", "source_location": "L497"}, {"id": "archive_final_five_generals_multi_factor_stock_selection_report_codeblock_27", "label": "code:python (from guanyu_value_tech_strategy import ValueFilter)", "file_type": "document", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/archive/FINAL_FIVE_GENERALS_MULTI_FACTOR_STOCK_SELECTION_REPORT.md", "source_location": "L506"}, {"id": "archive_final_five_generals_multi_factor_stock_selection_report_2_3_3_technicalfilter", "label": "2.3.3 TechnicalFilter - \u6280\u672f\u4fe1\u53f7\u8fc7\u6ee4\u5668", "file_type": "document", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/archive/FINAL_FIVE_GENERALS_MULTI_FACTOR_STOCK_SELECTION_REPORT.md", "source_location": "L516"}, {"id": "archive_final_five_generals_multi_factor_stock_selection_report_codeblock_28", "label": "code:python (# True Range = max(\u6700\u9ad8-\u6700\u4f4e, |\u6700\u9ad8-\u6628\u6536|, |\u6700\u4f4e-\u6628\u6536|))", "file_type": "document", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/archive/FINAL_FIVE_GENERALS_MULTI_FACTOR_STOCK_SELECTION_REPORT.md", "source_location": "L525"}, {"id": "archive_final_five_generals_multi_factor_stock_selection_report_codeblock_29", "label": "code:python (# \u6761\u4ef61\uff1a\u6700\u65b0\u6536\u76d8\u4ef7 >= 20\u65e5\u5747\u7ebf)", "file_type": "document", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/archive/FINAL_FIVE_GENERALS_MULTI_FACTOR_STOCK_SELECTION_REPORT.md", "source_location": "L531"}, {"id": "archive_final_five_generals_multi_factor_stock_selection_report_codeblock_30", "label": "code:python (# \u6761\u4ef6\uff1a\u8fd120\u5929\u6700\u5927\u56de\u64a4 <= 20%)", "file_type": "document", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/archive/FINAL_FIVE_GENERALS_MULTI_FACTOR_STOCK_SELECTION_REPORT.md", "source_location": "L537"}, {"id": "archive_final_five_generals_multi_factor_stock_selection_report_codeblock_31", "label": "code:python (# \u6761\u4ef6\uff1a\u6700\u8fd15\u5929\u6210\u4ea4\u91cf\u4e0d\u662f\u524d25\u5929\u5e73\u5747\u91cf\u76843\u500d\u4ee5\u4e0a)", "file_type": "document", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/archive/FINAL_FIVE_GENERALS_MULTI_FACTOR_STOCK_SELECTION_REPORT.md", "source_location": "L542"}, {"id": "archive_final_five_generals_multi_factor_stock_selection_report_codeblock_32", "label": "code:python (# \u6761\u4ef6\uff1aMACD\u91d1\u53c9 \u6216 MACD\u5728\u96f6\u8f74\u4e0a\u65b9)", "file_type": "document", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/archive/FINAL_FIVE_GENERALS_MULTI_FACTOR_STOCK_SELECTION_REPORT.md", "source_location": "L547"}, {"id": "archive_final_five_generals_multi_factor_stock_selection_report_codeblock_33", "label": "code:python (from guanyu_value_tech_strategy import TechnicalFilter)", "file_type": "document", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/archive/FINAL_FIVE_GENERALS_MULTI_FACTOR_STOCK_SELECTION_REPORT.md", "source_location": "L556"}, {"id": "archive_final_five_generals_multi_factor_stock_selection_report_2_3_4_positionmanager", "label": "2.3.4 PositionManager - \u4ed3\u4f4d\u7ba1\u7406\u5668", "file_type": "document", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/archive/FINAL_FIVE_GENERALS_MULTI_FACTOR_STOCK_SELECTION_REPORT.md", "source_location": "L566"}, {"id": "archive_final_five_generals_multi_factor_stock_selection_report_codeblock_34", "label": "code:python (# 1. \u786e\u4fdd\u80a1\u7968\u6570\u91cf\u5728\u5408\u7406\u8303\u56f4\uff08min_count, max_count\uff09)", "file_type": "document", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/archive/FINAL_FIVE_GENERALS_MULTI_FACTOR_STOCK_SELECTION_REPORT.md", "source_location": "L571"}, {"id": "archive_final_five_generals_multi_factor_stock_selection_report_codeblock_35", "label": "code:python (# \u5f85\u5b9e\u73b0\uff1a\u9700\u8981\u8c03\u7528 ak.stock_industry_category())", "file_type": "document", "source_file": 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new file mode 100644
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new file mode 100644
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"strategies_guanyu_value_tech_strategy_technicalfilter_calculate_atr", "label": ".calculate_atr()", "file_type": "code", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/strategies/guanyu_value_tech_strategy.py", "source_location": "L354"}, {"id": "strategies_guanyu_value_tech_strategy_technicalfilter_check_trend_up", "label": ".check_trend_up()", "file_type": "code", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/strategies/guanyu_value_tech_strategy.py", "source_location": "L378"}, {"id": "strategies_guanyu_value_tech_strategy_technicalfilter_check_recent_drawdown", "label": ".check_recent_drawdown()", "file_type": "code", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/strategies/guanyu_value_tech_strategy.py", "source_location": "L411"}, {"id": "strategies_guanyu_value_tech_strategy_technicalfilter_check_volume_surge", "label": ".check_volume_surge()", "file_type": "code", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/strategies/guanyu_value_tech_strategy.py", "source_location": "L440"}, {"id": "strategies_guanyu_value_tech_strategy_technicalfilter_check_macd_signal", "label": ".check_macd_signal()", "file_type": "code", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/strategies/guanyu_value_tech_strategy.py", "source_location": "L461"}, {"id": "strategies_guanyu_value_tech_strategy_technicalfilter_apply_stock_filter", "label": ".apply_stock_filter()", "file_type": "code", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/strategies/guanyu_value_tech_strategy.py", "source_location": "L489"}, {"id": "strategies_guanyu_value_tech_strategy_technicalfilter_apply", "label": ".apply()", "file_type": "code", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/strategies/guanyu_value_tech_strategy.py", "source_location": "L538"}, {"id": "strategies_guanyu_value_tech_strategy_positionmanager", "label": "PositionManager", "file_type": "code", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/strategies/guanyu_value_tech_strategy.py", "source_location": "L583"}, {"id": "strategies_guanyu_value_tech_strategy_positionmanager_init", "label": ".__init__()", "file_type": "code", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/strategies/guanyu_value_tech_strategy.py", "source_location": "L590"}, {"id": "strategies_guanyu_value_tech_strategy_positionmanager_calculate_position_size", "label": ".calculate_position_size()", "file_type": "code", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/strategies/guanyu_value_tech_strategy.py", "source_location": "L602"}, {"id": "strategies_guanyu_value_tech_strategy_positionmanager_check_industry_concentration", "label": ".check_industry_concentration()", "file_type": "code", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/strategies/guanyu_value_tech_strategy.py", "source_location": "L653"}, {"id": "strategies_guanyu_value_tech_strategy_positionmanager_calculate_stop_loss", "label": ".calculate_stop_loss()", "file_type": "code", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/strategies/guanyu_value_tech_strategy.py", "source_location": "L675"}, {"id": "strategies_guanyu_value_tech_strategy_positionmanager_generate_entry_orders", "label": ".generate_entry_orders()", "file_type": "code", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/strategies/guanyu_value_tech_strategy.py", "source_location": "L711"}, {"id": "strategies_guanyu_value_tech_strategy_positionmanager_check_exit_signal", "label": ".check_exit_signal()", "file_type": "code", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/strategies/guanyu_value_tech_strategy.py", "source_location": "L757"}, {"id": "strategies_guanyu_value_tech_strategy_guanyuvaluetechstrategy", "label": "GuanYuValueTechStrategy", "file_type": "code", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/strategies/guanyu_value_tech_strategy.py", "source_location": "L796"}, {"id": "strategies_guanyu_value_tech_strategy_guanyuvaluetechstrategy_init", "label": ".__init__()", "file_type": "code", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/strategies/guanyu_value_tech_strategy.py", "source_location": "L809"}, {"id": "strategies_guanyu_value_tech_strategy_guanyuvaluetechstrategy_run", "label": ".run()", "file_type": "code", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/strategies/guanyu_value_tech_strategy.py", "source_location": "L834"}, {"id": "strategies_guanyu_value_tech_strategy_guanyuvaluetechstrategy_print_orders", "label": ".print_orders()", "file_type": "code", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/strategies/guanyu_value_tech_strategy.py", "source_location": "L902"}, {"id": "strategies_guanyu_value_tech_strategy_main", "label": "main()", "file_type": "code", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/strategies/guanyu_value_tech_strategy.py", "source_location": "L928"}, {"id": "strategies_guanyu_value_tech_strategy_rationale_83", "label": "\u4ef7\u503c\u7b5b\u9009\u5668 - \u7b2c\u4e00\u6b65\uff1a\u4ef7\u503c\u7b5b\u9009\u7f29\u5c0f\u8303\u56f4     =========================================     \u98ce\u63a7\u524d\u7f6e\uff0c\u901a\u8fc7\u57fa\u672c", "file_type": "rationale", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/strategies/guanyu_value_tech_strategy.py", "source_location": "L83"}, {"id": "strategies_guanyu_value_tech_strategy_rationale_90", "label": "\u521d\u59cb\u5316\u4ef7\u503c\u7b5b\u9009\u5668                  Args:             risk_profile: \u98ce\u9669\u504f\u597d\u914d\u7f6e", "file_type": "rationale", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/strategies/guanyu_value_tech_strategy.py", "source_location": "L90"}, {"id": "strategies_guanyu_value_tech_strategy_rationale_99", "label": "\u83b7\u53d6A\u80a1\u5168\u5e02\u573a\u80a1\u7968\u5217\u8868                  Returns:             \u80a1\u7968\u5217\u8868 DataFrame", "file_type": "rationale", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/strategies/guanyu_value_tech_strategy.py", "source_location": "L99"}, {"id": "strategies_guanyu_value_tech_strategy_rationale_129", "label": "\u6392\u9664\u57fa\u672c\u98ce\u9669\u80a1\u7968\uff08\u98ce\u63a7\u524d\u7f6e\uff09                  \u6392\u9664\u6761\u4ef6\uff1a         1. ST/*ST\u80a1\u7968         2. \u4e0a\u5e02\u4e0d\u8db3180\u5929\u7684\u65b0\u80a1", "file_type": "rationale", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/strategies/guanyu_value_tech_strategy.py", "source_location": "L129"}, {"id": "strategies_guanyu_value_tech_strategy_rationale_176", "label": "\u4f30\u503c\u6307\u6807\u7b5b\u9009                  \u7b5b\u9009\u6761\u4ef6\uff1a         1. PE < pe_max\uff08\u6839\u636e\u98ce\u9669\u504f\u597d\uff09         2. PB < pb_", "file_type": "rationale", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/strategies/guanyu_value_tech_strategy.py", "source_location": "L176"}, {"id": "strategies_guanyu_value_tech_strategy_rationale_210", "label": "\u8d28\u91cf\u6307\u6807\u7b5b\u9009                            \u7b5b\u9009\u6761\u4ef6\uff1a         1. ROE > roe_min\uff08\u6839\u636e\u98ce\u9669\u504f\u597d\uff09", "file_type": "rationale", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/strategies/guanyu_value_tech_strategy.py", "source_location": "L210"}, {"id": "strategies_guanyu_value_tech_strategy_rationale_246", "label": "\u6267\u884c\u5b8c\u6574\u7684\u4ef7\u503c\u7b5b\u9009\u6d41\u7a0b                  Args:             stock_list: \u80a1\u7968\u5217\u8868\uff0c\u5982\u679c\u4e3aNone\u5219\u81ea\u52a8\u83b7\u53d6", "file_type": "rationale", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/strategies/guanyu_value_tech_strategy.py", "source_location": "L246"}, {"id": "strategies_guanyu_value_tech_strategy_rationale_287", "label": "\u6280\u672f\u4fe1\u53f7\u8fc7\u6ee4\u5668 - \u7b2c\u4e8c\u6b65\uff1a\u6280\u672f\u5206\u6790\u786e\u8ba4\u5165\u573a\u70b9     ===============================================", "file_type": "rationale", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/strategies/guanyu_value_tech_strategy.py", "source_location": "L287"}, {"id": "strategies_guanyu_value_tech_strategy_rationale_294", "label": "\u521d\u59cb\u5316\u6280\u672f\u8fc7\u6ee4\u5668                  Args:             ma_days: \u5747\u7ebf\u5929\u6570\uff0c\u9ed8\u8ba420\u65e5", "file_type": "rationale", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/strategies/guanyu_value_tech_strategy.py", "source_location": "L294"}, {"id": "strategies_guanyu_value_tech_strategy_rationale_303", "label": "\u83b7\u53d6\u80a1\u7968\u5386\u53f2\u884c\u60c5\u6570\u636e                  Args:             stock_code: \u80a1\u7968\u4ee3\u7801             days:", "file_type": "rationale", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/strategies/guanyu_value_tech_strategy.py", "source_location": "L303"}, {"id": "strategies_guanyu_value_tech_strategy_rationale_355", "label": "\u8ba1\u7b97ATR\uff08Average True Range\uff09\u6ce2\u52a8\u7387\u6307\u6807                  Args:             df: \u5386\u53f2\u6570\u636e", "file_type": "rationale", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/strategies/guanyu_value_tech_strategy.py", "source_location": "L355"}, {"id": "strategies_guanyu_value_tech_strategy_rationale_379", "label": "\u68c0\u67e5\u8d8b\u52bf\u662f\u5426\u5411\u4e0a                  \u6761\u4ef6\uff1a         1. \u80a1\u4ef7\u7ad9\u572820\u65e5\u5747\u7ebf\u4e0a         2. \u5747\u7ebf\u5411\u4e0a\u503e\u659c", "file_type": "rationale", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/strategies/guanyu_value_tech_strategy.py", "source_location": "L379"}, {"id": "strategies_guanyu_value_tech_strategy_rationale_412", "label": "\u68c0\u67e5\u8fd1\u671f\u662f\u5426\u6709\u8fc7\u5ea6\u4e0b\u8dcc                  \u6761\u4ef6\uff1a         \u8fd1\u4e00\u4e2a\u6708\u8dcc\u5e45\u4e0d\u8d85\u8fc720%                  Args:", "file_type": "rationale", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/strategies/guanyu_value_tech_strategy.py", "source_location": "L412"}, {"id": "strategies_guanyu_value_tech_strategy_rationale_441", "label": "\u68c0\u67e5\u662f\u5426\u6709\u6781\u7aef\u653e\u91cf\uff08\u4e3b\u529b\u51fa\u8d27\u4fe1\u53f7\uff09                  \u6761\u4ef6\uff1a         \u6392\u9664\u6781\u7aef\u653e\u91cf\u60c5\u51b5", "file_type": "rationale", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/strategies/guanyu_value_tech_strategy.py", "source_location": "L441"}, {"id": "strategies_guanyu_value_tech_strategy_rationale_462", "label": "\u68c0\u67e5MACD\u4fe1\u53f7\uff08\u53ef\u9009\u589e\u5f3a\u4fe1\u53f7\uff09                  \u6761\u4ef6\uff1a         MACD\u91d1\u53c9\u6216MACD\u5728\u96f6\u8f74\u4e0a\u65b9", "file_type": "rationale", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/strategies/guanyu_value_tech_strategy.py", "source_location": "L462"}, {"id": "strategies_guanyu_value_tech_strategy_rationale_490", "label": "\u5bf9\u5355\u53ea\u80a1\u7968\u5e94\u7528\u6280\u672f\u8fc7\u6ee4                  Args:             stock_code: \u80a1\u7968\u4ee3\u7801             stoc", "file_type": "rationale", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/strategies/guanyu_value_tech_strategy.py", "source_location": "L490"}, {"id": "strategies_guanyu_value_tech_strategy_rationale_539", "label": "\u5bf9\u5019\u9009\u80a1\u7968\u6279\u91cf\u5e94\u7528\u6280\u672f\u8fc7\u6ee4                  Args:             candidate_stocks: \u5019\u9009\u80a1\u7968\u5217\u8868", "file_type": "rationale", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/strategies/guanyu_value_tech_strategy.py", "source_location": "L539"}, {"id": "strategies_guanyu_value_tech_strategy_rationale_584", "label": "\u4ed3\u4f4d\u7ba1\u7406\u5668 - \u7b2c\u4e09\u6b65\uff1a\u4ed3\u4f4d\u63a7\u5236\u548c\u52a8\u6001\u6b62\u635f     ==========================================     \u63a7\u5236\u5355\u7968\u4ed3\u4f4d\u3001", "file_type": "rationale", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/strategies/guanyu_value_tech_strategy.py", "source_location": "L584"}, {"id": "strategies_guanyu_value_tech_strategy_rationale_591", "label": "\u521d\u59cb\u5316\u4ed3\u4f4d\u7ba1\u7406\u5668                  Args:             risk_profile: \u98ce\u9669\u504f\u597d\u914d\u7f6e             tot", "file_type": "rationale", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/strategies/guanyu_value_tech_strategy.py", "source_location": "L591"}, {"id": "strategies_guanyu_value_tech_strategy_rationale_603", "label": "\u8ba1\u7b97\u5355\u7968\u4ed3\u4f4d\u5927\u5c0f                  \u89c4\u5219\uff1a         1. \u5355\u7968\u6700\u5927\u4ed3\u4f4d\u4e0d\u8d85\u8fc7\u98ce\u9669\u504f\u597d\u9650\u5236         2. \u6839\u636e\u80a1\u7968\u6570\u91cf\u52a8\u6001\u8c03\u6574\uff0c\u786e", "file_type": "rationale", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/strategies/guanyu_value_tech_strategy.py", "source_location": "L603"}, {"id": "strategies_guanyu_value_tech_strategy_rationale_654", "label": "\u68c0\u67e5\u884c\u4e1a\u96c6\u4e2d\u5ea6\u662f\u5426\u8d85\u6807                  Args:             positions: \u6301\u4ed3\u5217\u8868", "file_type": "rationale", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/strategies/guanyu_value_tech_strategy.py", "source_location": "L654"}, {"id": "strategies_guanyu_value_tech_strategy_rationale_677", "label": "\u8ba1\u7b97\u6b62\u635f\u4ef7\u683c                  \u65b9\u6cd5\uff1a         1. ma_method: \u6536\u76d8\u4ef7\u8dcc\u783420\u65e5\u5747\u7ebf         2. atr_meth", "file_type": "rationale", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/strategies/guanyu_value_tech_strategy.py", "source_location": "L677"}, {"id": "strategies_guanyu_value_tech_strategy_rationale_712", "label": "\u751f\u6210\u5165\u573a\u8ba2\u5355                  Args:             selected_stocks: \u9009\u4e2d\u7684\u80a1\u7968\u5217\u8868", "file_type": "rationale", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/strategies/guanyu_value_tech_strategy.py", "source_location": "L712"}, {"id": "strategies_guanyu_value_tech_strategy_rationale_760", "label": "\u68c0\u67e5\u51fa\u573a\u4fe1\u53f7                  \u51fa\u573a\u6761\u4ef6\uff1a         1. \u6b62\u635f\uff1a\u4ef7\u683c\u8dcc\u7834\u6b62\u635f\u4ef7         2. \u5747\u7ebf\u6b62\u635f\uff1a\u6536\u76d8\u4ef7\u8dcc\u783420\u65e5\u5747\u7ebf", "file_type": "rationale", "source_file": 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new file mode 100644
index 000000000..d953169b1
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"\u68c0\u67e5\u662f\u5426\u89e6\u53d1\u6b62\u635f         :return: (\u662f\u5426\u89e6\u53d1, \u5f53\u524d\u4ef7\u683c\u76f8\u5bf9\u7a81\u7834\u4f4e\u70b9\u8dcc\u5e45)", "file_type": "rationale", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/strategies/pure-breakout-20260327/risk_control_breakout.py", "source_location": "L53"}, {"id": "pure_breakout_20260327_risk_control_breakout_rationale_66", "label": "\u5355\u65e5\u66b4\u8dcc\u5f3a\u5236\u51cf\u4ed3\uff1a\u5355\u65e5\u66b4\u8dcc\u8d85\u8fc77%\u5f3a\u5236\u51cf\u4ed3", "file_type": "rationale", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/strategies/pure-breakout-20260327/risk_control_breakout.py", "source_location": "L66"}, {"id": "pure_breakout_20260327_risk_control_breakout_rationale_69", "label": "\u521d\u59cb\u5316         :param crash_threshold: \u66b4\u8dcc\u9608\u503c\uff08%\uff09\uff0c\u9ed8\u8ba4-7%         :param reduce_ratio: \u51cf", "file_type": "rationale", 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"/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/guanyu-risk/research/factors-strategy-risk-control-20260327/risk_control.py", "source_location": "L42"}, {"id": "factors_strategy_risk_control_20260327_risk_control_rationale_49", "label": "\u68c0\u67e5\u662f\u5426\u89e6\u53d1\u6b62\u635f         :return: True = \u9700\u8981\u6b62\u635f\uff0cFalse = \u6301\u6709", "file_type": "rationale", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/guanyu-risk/research/factors-strategy-risk-control-20260327/risk_control.py", "source_location": "L49"}, {"id": "factors_strategy_risk_control_20260327_risk_control_rationale_68", "label": "\u6574\u4f53\u56de\u64a4\u5206\u7ea7\u98ce\u63a7     10%\u56de\u64a4 \u2192 \u964d\u4ed350%     20%\u56de\u64a4 \u2192 \u964d\u4ed375%     25%\u56de\u64a4 \u2192 \u6e05\u4ed3\u4f11\u606f", "file_type": "rationale", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/guanyu-risk/research/factors-strategy-risk-control-20260327/risk_control.py", "source_location": "L68"}, {"id": "factors_strategy_risk_control_20260327_risk_control_rationale_78", "label": "\u521d\u59cb\u5316\u5206\u7ea7\u98ce\u63a7         :param drawdown_levels: \u56de\u64a4\u9608\u503c         :param reduce_ratios: \u5bf9\u5e94\u964d\u4ed3\u6bd4", "file_type": "rationale", "source_file": "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/guanyu-risk/research/factors-strategy-risk-control-20260327/risk_control.py", "source_location": "L78"}, {"id": "factors_strategy_risk_control_20260327_risk_control_rationale_95", "label": "\u83b7\u53d6\u76ee\u6807\u4ed3\u4f4d\u6bd4\u4f8b         :return: \u76ee\u6807\u4ed3\u4f4d\u5360\u5f53\u524d\u603b\u8d44\u91d1\u7684\u6bd4\u4f8b", "file_type": "rationale", "source_file": 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new file mode 100644
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+      "file_type": "rationale",
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+    },
+    {
+      "label": "\u9a8c\u8bc1\u6570\u636e\u5e93\u6570\u636e\u5b8c\u6574\u6027          Returns:             \u9a8c\u8bc1\u7ed3\u679c",
+      "file_type": "rationale",
+      "source_file": "archive/zhaoyun-data-old-backup-20240325/akshare_vnpy_adapter.py",
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+      "community": 18,
+      "norm_label": "\u9a8c\u8bc1\u6570\u636e\u5e93\u6570\u636e\u5b8c\u6574\u6027          returns:             \u9a8c\u8bc1\u7ed3\u679c"
+    },
+    {
+      "label": "test_guanyu_strategy.py",
+      "file_type": "code",
+      "source_file": "strategies/test_guanyu_strategy.py",
+      "source_location": "L1",
+      "id": "strategies_test_guanyu_strategy_py",
+      "community": 347,
+      "norm_label": "test_guanyu_strategy.py"
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+    {
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+      "file_type": "code",
+      "source_file": "strategies/test_guanyu_strategy.py",
+      "source_location": "L17",
+      "id": "strategies_test_guanyu_strategy_test_imports",
+      "community": 347,
+      "norm_label": "test_imports()"
+    },
+    {
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+      "file_type": "code",
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+      "source_location": "L50",
+      "id": "strategies_test_guanyu_strategy_test_strategy_import",
+      "community": 347,
+      "norm_label": "test_strategy_import()"
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+    {
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+      "file_type": "code",
+      "source_file": "strategies/test_guanyu_strategy.py",
+      "source_location": "L83",
+      "id": "strategies_test_guanyu_strategy_test_strategy_initialization",
+      "community": 347,
+      "norm_label": "test_strategy_initialization()"
+    },
+    {
+      "label": "test_data_connection()",
+      "file_type": "code",
+      "source_file": "strategies/test_guanyu_strategy.py",
+      "source_location": "L124",
+      "id": "strategies_test_guanyu_strategy_test_data_connection",
+      "community": 347,
+      "norm_label": "test_data_connection()"
+    },
+    {
+      "label": "main()",
+      "file_type": "code",
+      "source_file": "strategies/test_guanyu_strategy.py",
+      "source_location": "L149",
+      "id": "strategies_test_guanyu_strategy_main",
+      "community": 347,
+      "norm_label": "main()"
+    },
+    {
+      "label": "guanyu_value_tech_strategy.py",
+      "file_type": "code",
+      "source_file": "strategies/guanyu_value_tech_strategy.py",
+      "source_location": "L1",
+      "id": "strategies_guanyu_value_tech_strategy_py",
+      "community": 248,
+      "norm_label": "guanyu_value_tech_strategy.py"
+    },
+    {
+      "label": "RiskProfile",
+      "file_type": "code",
+      "source_file": "strategies/guanyu_value_tech_strategy.py",
+      "source_location": "L32",
+      "id": "strategies_guanyu_value_tech_strategy_riskprofile",
+      "community": 248,
+      "norm_label": "riskprofile"
+    },
+    {
+      "label": "get_profile()",
+      "file_type": "code",
+      "source_file": "strategies/guanyu_value_tech_strategy.py",
+      "source_location": "L72",
+      "id": "strategies_guanyu_value_tech_strategy_get_profile",
+      "community": 306,
+      "norm_label": "get_profile()"
+    },
+    {
+      "label": "ValueFilter",
+      "file_type": "code",
+      "source_file": "strategies/guanyu_value_tech_strategy.py",
+      "source_location": "L82",
+      "id": "strategies_guanyu_value_tech_strategy_valuefilter",
+      "community": 168,
+      "norm_label": "valuefilter"
+    },
+    {
+      "label": ".__init__()",
+      "file_type": "code",
+      "source_file": "strategies/guanyu_value_tech_strategy.py",
+      "source_location": "L89",
+      "id": "strategies_guanyu_value_tech_strategy_valuefilter_init",
+      "community": 306,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": ".get_stock_list()",
+      "file_type": "code",
+      "source_file": "strategies/guanyu_value_tech_strategy.py",
+      "source_location": "L98",
+      "id": "strategies_guanyu_value_tech_strategy_valuefilter_get_stock_list",
+      "community": 168,
+      "norm_label": ".get_stock_list()"
+    },
+    {
+      "label": ".filter_basic_risks()",
+      "file_type": "code",
+      "source_file": "strategies/guanyu_value_tech_strategy.py",
+      "source_location": "L128",
+      "id": "strategies_guanyu_value_tech_strategy_valuefilter_filter_basic_risks",
+      "community": 168,
+      "norm_label": ".filter_basic_risks()"
+    },
+    {
+      "label": ".filter_valuation_metrics()",
+      "file_type": "code",
+      "source_file": "strategies/guanyu_value_tech_strategy.py",
+      "source_location": "L175",
+      "id": "strategies_guanyu_value_tech_strategy_valuefilter_filter_valuation_metrics",
+      "community": 168,
+      "norm_label": ".filter_valuation_metrics()"
+    },
+    {
+      "label": ".filter_quality_metrics()",
+      "file_type": "code",
+      "source_file": "strategies/guanyu_value_tech_strategy.py",
+      "source_location": "L209",
+      "id": "strategies_guanyu_value_tech_strategy_valuefilter_filter_quality_metrics",
+      "community": 168,
+      "norm_label": ".filter_quality_metrics()"
+    },
+    {
+      "label": ".apply()",
+      "file_type": "code",
+      "source_file": "strategies/guanyu_value_tech_strategy.py",
+      "source_location": "L245",
+      "id": "strategies_guanyu_value_tech_strategy_valuefilter_apply",
+      "community": 168,
+      "norm_label": ".apply()"
+    },
+    {
+      "label": "TechnicalFilter",
+      "file_type": "code",
+      "source_file": "strategies/guanyu_value_tech_strategy.py",
+      "source_location": "L286",
+      "id": "strategies_guanyu_value_tech_strategy_technicalfilter",
+      "community": 84,
+      "norm_label": "technicalfilter"
+    },
+    {
+      "label": ".__init__()",
+      "file_type": "code",
+      "source_file": "strategies/guanyu_value_tech_strategy.py",
+      "source_location": "L293",
+      "id": "strategies_guanyu_value_tech_strategy_technicalfilter_init",
+      "community": 84,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": ".get_stock_history()",
+      "file_type": "code",
+      "source_file": "strategies/guanyu_value_tech_strategy.py",
+      "source_location": "L302",
+      "id": "strategies_guanyu_value_tech_strategy_technicalfilter_get_stock_history",
+      "community": 84,
+      "norm_label": ".get_stock_history()"
+    },
+    {
+      "label": ".calculate_ma()",
+      "file_type": "code",
+      "source_file": "strategies/guanyu_value_tech_strategy.py",
+      "source_location": "L350",
+      "id": "strategies_guanyu_value_tech_strategy_technicalfilter_calculate_ma",
+      "community": 84,
+      "norm_label": ".calculate_ma()"
+    },
+    {
+      "label": ".calculate_atr()",
+      "file_type": "code",
+      "source_file": "strategies/guanyu_value_tech_strategy.py",
+      "source_location": "L354",
+      "id": "strategies_guanyu_value_tech_strategy_technicalfilter_calculate_atr",
+      "community": 84,
+      "norm_label": ".calculate_atr()"
+    },
+    {
+      "label": ".check_trend_up()",
+      "file_type": "code",
+      "source_file": "strategies/guanyu_value_tech_strategy.py",
+      "source_location": "L378",
+      "id": "strategies_guanyu_value_tech_strategy_technicalfilter_check_trend_up",
+      "community": 84,
+      "norm_label": ".check_trend_up()"
+    },
+    {
+      "label": ".check_recent_drawdown()",
+      "file_type": "code",
+      "source_file": "strategies/guanyu_value_tech_strategy.py",
+      "source_location": "L411",
+      "id": "strategies_guanyu_value_tech_strategy_technicalfilter_check_recent_drawdown",
+      "community": 84,
+      "norm_label": ".check_recent_drawdown()"
+    },
+    {
+      "label": ".check_volume_surge()",
+      "file_type": "code",
+      "source_file": "strategies/guanyu_value_tech_strategy.py",
+      "source_location": "L440",
+      "id": "strategies_guanyu_value_tech_strategy_technicalfilter_check_volume_surge",
+      "community": 84,
+      "norm_label": ".check_volume_surge()"
+    },
+    {
+      "label": ".check_macd_signal()",
+      "file_type": "code",
+      "source_file": "strategies/guanyu_value_tech_strategy.py",
+      "source_location": "L461",
+      "id": "strategies_guanyu_value_tech_strategy_technicalfilter_check_macd_signal",
+      "community": 84,
+      "norm_label": ".check_macd_signal()"
+    },
+    {
+      "label": ".apply_stock_filter()",
+      "file_type": "code",
+      "source_file": "strategies/guanyu_value_tech_strategy.py",
+      "source_location": "L489",
+      "id": "strategies_guanyu_value_tech_strategy_technicalfilter_apply_stock_filter",
+      "community": 84,
+      "norm_label": ".apply_stock_filter()"
+    },
+    {
+      "label": ".apply()",
+      "file_type": "code",
+      "source_file": "strategies/guanyu_value_tech_strategy.py",
+      "source_location": "L538",
+      "id": "strategies_guanyu_value_tech_strategy_technicalfilter_apply",
+      "community": 84,
+      "norm_label": ".apply()"
+    },
+    {
+      "label": "PositionManager",
+      "file_type": "code",
+      "source_file": "strategies/guanyu_value_tech_strategy.py",
+      "source_location": "L583",
+      "id": "strategies_guanyu_value_tech_strategy_positionmanager",
+      "community": 169,
+      "norm_label": "positionmanager"
+    },
+    {
+      "label": ".__init__()",
+      "file_type": "code",
+      "source_file": "strategies/guanyu_value_tech_strategy.py",
+      "source_location": "L590",
+      "id": "strategies_guanyu_value_tech_strategy_positionmanager_init",
+      "community": 306,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": ".calculate_position_size()",
+      "file_type": "code",
+      "source_file": "strategies/guanyu_value_tech_strategy.py",
+      "source_location": "L602",
+      "id": "strategies_guanyu_value_tech_strategy_positionmanager_calculate_position_size",
+      "community": 169,
+      "norm_label": ".calculate_position_size()"
+    },
+    {
+      "label": ".check_industry_concentration()",
+      "file_type": "code",
+      "source_file": "strategies/guanyu_value_tech_strategy.py",
+      "source_location": "L653",
+      "id": "strategies_guanyu_value_tech_strategy_positionmanager_check_industry_concentration",
+      "community": 169,
+      "norm_label": ".check_industry_concentration()"
+    },
+    {
+      "label": ".calculate_stop_loss()",
+      "file_type": "code",
+      "source_file": "strategies/guanyu_value_tech_strategy.py",
+      "source_location": "L675",
+      "id": "strategies_guanyu_value_tech_strategy_positionmanager_calculate_stop_loss",
+      "community": 169,
+      "norm_label": ".calculate_stop_loss()"
+    },
+    {
+      "label": ".generate_entry_orders()",
+      "file_type": "code",
+      "source_file": "strategies/guanyu_value_tech_strategy.py",
+      "source_location": "L711",
+      "id": "strategies_guanyu_value_tech_strategy_positionmanager_generate_entry_orders",
+      "community": 169,
+      "norm_label": ".generate_entry_orders()"
+    },
+    {
+      "label": ".check_exit_signal()",
+      "file_type": "code",
+      "source_file": "strategies/guanyu_value_tech_strategy.py",
+      "source_location": "L757",
+      "id": "strategies_guanyu_value_tech_strategy_positionmanager_check_exit_signal",
+      "community": 169,
+      "norm_label": ".check_exit_signal()"
+    },
+    {
+      "label": "GuanYuValueTechStrategy",
+      "file_type": "code",
+      "source_file": "strategies/guanyu_value_tech_strategy.py",
+      "source_location": "L796",
+      "id": "strategies_guanyu_value_tech_strategy_guanyuvaluetechstrategy",
+      "community": 248,
+      "norm_label": "guanyuvaluetechstrategy"
+    },
+    {
+      "label": ".__init__()",
+      "file_type": "code",
+      "source_file": "strategies/guanyu_value_tech_strategy.py",
+      "source_location": "L809",
+      "id": "strategies_guanyu_value_tech_strategy_guanyuvaluetechstrategy_init",
+      "community": 306,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": ".run()",
+      "file_type": "code",
+      "source_file": "strategies/guanyu_value_tech_strategy.py",
+      "source_location": "L834",
+      "id": "strategies_guanyu_value_tech_strategy_guanyuvaluetechstrategy_run",
+      "community": 248,
+      "norm_label": ".run()"
+    },
+    {
+      "label": ".print_orders()",
+      "file_type": "code",
+      "source_file": "strategies/guanyu_value_tech_strategy.py",
+      "source_location": "L902",
+      "id": "strategies_guanyu_value_tech_strategy_guanyuvaluetechstrategy_print_orders",
+      "community": 248,
+      "norm_label": ".print_orders()"
+    },
+    {
+      "label": "main()",
+      "file_type": "code",
+      "source_file": "strategies/guanyu_value_tech_strategy.py",
+      "source_location": "L928",
+      "id": "strategies_guanyu_value_tech_strategy_main",
+      "community": 248,
+      "norm_label": "main()"
+    },
+    {
+      "label": "\u4ef7\u503c\u7b5b\u9009\u5668 - \u7b2c\u4e00\u6b65\uff1a\u4ef7\u503c\u7b5b\u9009\u7f29\u5c0f\u8303\u56f4     =========================================     \u98ce\u63a7\u524d\u7f6e\uff0c\u901a\u8fc7\u57fa\u672c",
+      "file_type": "rationale",
+      "source_file": "strategies/guanyu_value_tech_strategy.py",
+      "source_location": "L83",
+      "id": "strategies_guanyu_value_tech_strategy_rationale_83",
+      "community": 168,
+      "norm_label": "\u4ef7\u503c\u7b5b\u9009\u5668 - \u7b2c\u4e00\u6b65:\u4ef7\u503c\u7b5b\u9009\u7f29\u5c0f\u8303\u56f4     =========================================     \u98ce\u63a7\u524d\u7f6e,\u901a\u8fc7\u57fa\u672c"
+    },
+    {
+      "label": "\u521d\u59cb\u5316\u4ef7\u503c\u7b5b\u9009\u5668                  Args:             risk_profile: \u98ce\u9669\u504f\u597d\u914d\u7f6e",
+      "file_type": "rationale",
+      "source_file": "strategies/guanyu_value_tech_strategy.py",
+      "source_location": "L90",
+      "id": "strategies_guanyu_value_tech_strategy_rationale_90",
+      "community": 306,
+      "norm_label": "\u521d\u59cb\u5316\u4ef7\u503c\u7b5b\u9009\u5668                  args:             risk_profile: \u98ce\u9669\u504f\u597d\u914d\u7f6e"
+    },
+    {
+      "label": "\u83b7\u53d6A\u80a1\u5168\u5e02\u573a\u80a1\u7968\u5217\u8868                  Returns:             \u80a1\u7968\u5217\u8868 DataFrame",
+      "file_type": "rationale",
+      "source_file": "strategies/guanyu_value_tech_strategy.py",
+      "source_location": "L99",
+      "id": "strategies_guanyu_value_tech_strategy_rationale_99",
+      "community": 168,
+      "norm_label": "\u83b7\u53d6a\u80a1\u5168\u5e02\u573a\u80a1\u7968\u5217\u8868                  returns:             \u80a1\u7968\u5217\u8868 dataframe"
+    },
+    {
+      "label": "\u6392\u9664\u57fa\u672c\u98ce\u9669\u80a1\u7968\uff08\u98ce\u63a7\u524d\u7f6e\uff09                  \u6392\u9664\u6761\u4ef6\uff1a         1. ST/*ST\u80a1\u7968         2. \u4e0a\u5e02\u4e0d\u8db3180\u5929\u7684\u65b0\u80a1",
+      "file_type": "rationale",
+      "source_file": "strategies/guanyu_value_tech_strategy.py",
+      "source_location": "L129",
+      "id": "strategies_guanyu_value_tech_strategy_rationale_129",
+      "community": 168,
+      "norm_label": "\u6392\u9664\u57fa\u672c\u98ce\u9669\u80a1\u7968(\u98ce\u63a7\u524d\u7f6e)                  \u6392\u9664\u6761\u4ef6:         1. st/*st\u80a1\u7968         2. \u4e0a\u5e02\u4e0d\u8db3180\u5929\u7684\u65b0\u80a1"
+    },
+    {
+      "label": "\u4f30\u503c\u6307\u6807\u7b5b\u9009                  \u7b5b\u9009\u6761\u4ef6\uff1a         1. PE < pe_max\uff08\u6839\u636e\u98ce\u9669\u504f\u597d\uff09         2. PB < pb_",
+      "file_type": "rationale",
+      "source_file": "strategies/guanyu_value_tech_strategy.py",
+      "source_location": "L176",
+      "id": "strategies_guanyu_value_tech_strategy_rationale_176",
+      "community": 168,
+      "norm_label": "\u4f30\u503c\u6307\u6807\u7b5b\u9009                  \u7b5b\u9009\u6761\u4ef6:         1. pe < pe_max(\u6839\u636e\u98ce\u9669\u504f\u597d)         2. pb < pb_"
+    },
+    {
+      "label": "\u8d28\u91cf\u6307\u6807\u7b5b\u9009                            \u7b5b\u9009\u6761\u4ef6\uff1a         1. ROE > roe_min\uff08\u6839\u636e\u98ce\u9669\u504f\u597d\uff09",
+      "file_type": "rationale",
+      "source_file": "strategies/guanyu_value_tech_strategy.py",
+      "source_location": "L210",
+      "id": "strategies_guanyu_value_tech_strategy_rationale_210",
+      "community": 168,
+      "norm_label": "\u8d28\u91cf\u6307\u6807\u7b5b\u9009                            \u7b5b\u9009\u6761\u4ef6:         1. roe > roe_min(\u6839\u636e\u98ce\u9669\u504f\u597d)"
+    },
+    {
+      "label": "\u6267\u884c\u5b8c\u6574\u7684\u4ef7\u503c\u7b5b\u9009\u6d41\u7a0b                  Args:             stock_list: \u80a1\u7968\u5217\u8868\uff0c\u5982\u679c\u4e3aNone\u5219\u81ea\u52a8\u83b7\u53d6",
+      "file_type": "rationale",
+      "source_file": "strategies/guanyu_value_tech_strategy.py",
+      "source_location": "L246",
+      "id": "strategies_guanyu_value_tech_strategy_rationale_246",
+      "community": 168,
+      "norm_label": "\u6267\u884c\u5b8c\u6574\u7684\u4ef7\u503c\u7b5b\u9009\u6d41\u7a0b                  args:             stock_list: \u80a1\u7968\u5217\u8868,\u5982\u679c\u4e3anone\u5219\u81ea\u52a8\u83b7\u53d6"
+    },
+    {
+      "label": "\u6280\u672f\u4fe1\u53f7\u8fc7\u6ee4\u5668 - \u7b2c\u4e8c\u6b65\uff1a\u6280\u672f\u5206\u6790\u786e\u8ba4\u5165\u573a\u70b9     ===============================================",
+      "file_type": "rationale",
+      "source_file": "strategies/guanyu_value_tech_strategy.py",
+      "source_location": "L287",
+      "id": "strategies_guanyu_value_tech_strategy_rationale_287",
+      "community": 84,
+      "norm_label": "\u6280\u672f\u4fe1\u53f7\u8fc7\u6ee4\u5668 - \u7b2c\u4e8c\u6b65:\u6280\u672f\u5206\u6790\u786e\u8ba4\u5165\u573a\u70b9     ==============================================="
+    },
+    {
+      "label": "\u521d\u59cb\u5316\u6280\u672f\u8fc7\u6ee4\u5668                  Args:             ma_days: \u5747\u7ebf\u5929\u6570\uff0c\u9ed8\u8ba420\u65e5",
+      "file_type": "rationale",
+      "source_file": "strategies/guanyu_value_tech_strategy.py",
+      "source_location": "L294",
+      "id": "strategies_guanyu_value_tech_strategy_rationale_294",
+      "community": 84,
+      "norm_label": "\u521d\u59cb\u5316\u6280\u672f\u8fc7\u6ee4\u5668                  args:             ma_days: \u5747\u7ebf\u5929\u6570,\u9ed8\u8ba420\u65e5"
+    },
+    {
+      "label": "\u83b7\u53d6\u80a1\u7968\u5386\u53f2\u884c\u60c5\u6570\u636e                  Args:             stock_code: \u80a1\u7968\u4ee3\u7801             days:",
+      "file_type": "rationale",
+      "source_file": "strategies/guanyu_value_tech_strategy.py",
+      "source_location": "L303",
+      "id": "strategies_guanyu_value_tech_strategy_rationale_303",
+      "community": 84,
+      "norm_label": "\u83b7\u53d6\u80a1\u7968\u5386\u53f2\u884c\u60c5\u6570\u636e                  args:             stock_code: \u80a1\u7968\u4ee3\u7801             days:"
+    },
+    {
+      "label": "\u8ba1\u7b97ATR\uff08Average True Range\uff09\u6ce2\u52a8\u7387\u6307\u6807                  Args:             df: \u5386\u53f2\u6570\u636e",
+      "file_type": "rationale",
+      "source_file": "strategies/guanyu_value_tech_strategy.py",
+      "source_location": "L355",
+      "id": "strategies_guanyu_value_tech_strategy_rationale_355",
+      "community": 84,
+      "norm_label": "\u8ba1\u7b97atr(average true range)\u6ce2\u52a8\u7387\u6307\u6807                  args:             df: \u5386\u53f2\u6570\u636e"
+    },
+    {
+      "label": "\u68c0\u67e5\u8d8b\u52bf\u662f\u5426\u5411\u4e0a                  \u6761\u4ef6\uff1a         1. \u80a1\u4ef7\u7ad9\u572820\u65e5\u5747\u7ebf\u4e0a         2. \u5747\u7ebf\u5411\u4e0a\u503e\u659c",
+      "file_type": "rationale",
+      "source_file": "strategies/guanyu_value_tech_strategy.py",
+      "source_location": "L379",
+      "id": "strategies_guanyu_value_tech_strategy_rationale_379",
+      "community": 84,
+      "norm_label": "\u68c0\u67e5\u8d8b\u52bf\u662f\u5426\u5411\u4e0a                  \u6761\u4ef6:         1. \u80a1\u4ef7\u7ad9\u572820\u65e5\u5747\u7ebf\u4e0a         2. \u5747\u7ebf\u5411\u4e0a\u503e\u659c"
+    },
+    {
+      "label": "\u68c0\u67e5\u8fd1\u671f\u662f\u5426\u6709\u8fc7\u5ea6\u4e0b\u8dcc                  \u6761\u4ef6\uff1a         \u8fd1\u4e00\u4e2a\u6708\u8dcc\u5e45\u4e0d\u8d85\u8fc720%                  Args:",
+      "file_type": "rationale",
+      "source_file": "strategies/guanyu_value_tech_strategy.py",
+      "source_location": "L412",
+      "id": "strategies_guanyu_value_tech_strategy_rationale_412",
+      "community": 84,
+      "norm_label": "\u68c0\u67e5\u8fd1\u671f\u662f\u5426\u6709\u8fc7\u5ea6\u4e0b\u8dcc                  \u6761\u4ef6:         \u8fd1\u4e00\u4e2a\u6708\u8dcc\u5e45\u4e0d\u8d85\u8fc720%                  args:"
+    },
+    {
+      "label": "\u68c0\u67e5\u662f\u5426\u6709\u6781\u7aef\u653e\u91cf\uff08\u4e3b\u529b\u51fa\u8d27\u4fe1\u53f7\uff09                  \u6761\u4ef6\uff1a         \u6392\u9664\u6781\u7aef\u653e\u91cf\u60c5\u51b5",
+      "file_type": "rationale",
+      "source_file": "strategies/guanyu_value_tech_strategy.py",
+      "source_location": "L441",
+      "id": "strategies_guanyu_value_tech_strategy_rationale_441",
+      "community": 84,
+      "norm_label": "\u68c0\u67e5\u662f\u5426\u6709\u6781\u7aef\u653e\u91cf(\u4e3b\u529b\u51fa\u8d27\u4fe1\u53f7)                  \u6761\u4ef6:         \u6392\u9664\u6781\u7aef\u653e\u91cf\u60c5\u51b5"
+    },
+    {
+      "label": "\u68c0\u67e5MACD\u4fe1\u53f7\uff08\u53ef\u9009\u589e\u5f3a\u4fe1\u53f7\uff09                  \u6761\u4ef6\uff1a         MACD\u91d1\u53c9\u6216MACD\u5728\u96f6\u8f74\u4e0a\u65b9",
+      "file_type": "rationale",
+      "source_file": "strategies/guanyu_value_tech_strategy.py",
+      "source_location": "L462",
+      "id": "strategies_guanyu_value_tech_strategy_rationale_462",
+      "community": 84,
+      "norm_label": "\u68c0\u67e5macd\u4fe1\u53f7(\u53ef\u9009\u589e\u5f3a\u4fe1\u53f7)                  \u6761\u4ef6:         macd\u91d1\u53c9\u6216macd\u5728\u96f6\u8f74\u4e0a\u65b9"
+    },
+    {
+      "label": "\u5bf9\u5355\u53ea\u80a1\u7968\u5e94\u7528\u6280\u672f\u8fc7\u6ee4                  Args:             stock_code: \u80a1\u7968\u4ee3\u7801             stoc",
+      "file_type": "rationale",
+      "source_file": "strategies/guanyu_value_tech_strategy.py",
+      "source_location": "L490",
+      "id": "strategies_guanyu_value_tech_strategy_rationale_490",
+      "community": 84,
+      "norm_label": "\u5bf9\u5355\u53ea\u80a1\u7968\u5e94\u7528\u6280\u672f\u8fc7\u6ee4                  args:             stock_code: \u80a1\u7968\u4ee3\u7801             stoc"
+    },
+    {
+      "label": "\u5bf9\u5019\u9009\u80a1\u7968\u6279\u91cf\u5e94\u7528\u6280\u672f\u8fc7\u6ee4                  Args:             candidate_stocks: \u5019\u9009\u80a1\u7968\u5217\u8868",
+      "file_type": "rationale",
+      "source_file": "strategies/guanyu_value_tech_strategy.py",
+      "source_location": "L539",
+      "id": "strategies_guanyu_value_tech_strategy_rationale_539",
+      "community": 84,
+      "norm_label": "\u5bf9\u5019\u9009\u80a1\u7968\u6279\u91cf\u5e94\u7528\u6280\u672f\u8fc7\u6ee4                  args:             candidate_stocks: \u5019\u9009\u80a1\u7968\u5217\u8868"
+    },
+    {
+      "label": "\u4ed3\u4f4d\u7ba1\u7406\u5668 - \u7b2c\u4e09\u6b65\uff1a\u4ed3\u4f4d\u63a7\u5236\u548c\u52a8\u6001\u6b62\u635f     ==========================================     \u63a7\u5236\u5355\u7968\u4ed3\u4f4d\u3001",
+      "file_type": "rationale",
+      "source_file": "strategies/guanyu_value_tech_strategy.py",
+      "source_location": "L584",
+      "id": "strategies_guanyu_value_tech_strategy_rationale_584",
+      "community": 169,
+      "norm_label": "\u4ed3\u4f4d\u7ba1\u7406\u5668 - \u7b2c\u4e09\u6b65:\u4ed3\u4f4d\u63a7\u5236\u548c\u52a8\u6001\u6b62\u635f     ==========================================     \u63a7\u5236\u5355\u7968\u4ed3\u4f4d\u3001"
+    },
+    {
+      "label": "\u521d\u59cb\u5316\u4ed3\u4f4d\u7ba1\u7406\u5668                  Args:             risk_profile: \u98ce\u9669\u504f\u597d\u914d\u7f6e             tot",
+      "file_type": "rationale",
+      "source_file": "strategies/guanyu_value_tech_strategy.py",
+      "source_location": "L591",
+      "id": "strategies_guanyu_value_tech_strategy_rationale_591",
+      "community": 306,
+      "norm_label": "\u521d\u59cb\u5316\u4ed3\u4f4d\u7ba1\u7406\u5668                  args:             risk_profile: \u98ce\u9669\u504f\u597d\u914d\u7f6e             tot"
+    },
+    {
+      "label": "\u8ba1\u7b97\u5355\u7968\u4ed3\u4f4d\u5927\u5c0f                  \u89c4\u5219\uff1a         1. \u5355\u7968\u6700\u5927\u4ed3\u4f4d\u4e0d\u8d85\u8fc7\u98ce\u9669\u504f\u597d\u9650\u5236         2. \u6839\u636e\u80a1\u7968\u6570\u91cf\u52a8\u6001\u8c03\u6574\uff0c\u786e",
+      "file_type": "rationale",
+      "source_file": "strategies/guanyu_value_tech_strategy.py",
+      "source_location": "L603",
+      "id": "strategies_guanyu_value_tech_strategy_rationale_603",
+      "community": 169,
+      "norm_label": "\u8ba1\u7b97\u5355\u7968\u4ed3\u4f4d\u5927\u5c0f                  \u89c4\u5219:         1. \u5355\u7968\u6700\u5927\u4ed3\u4f4d\u4e0d\u8d85\u8fc7\u98ce\u9669\u504f\u597d\u9650\u5236         2. \u6839\u636e\u80a1\u7968\u6570\u91cf\u52a8\u6001\u8c03\u6574,\u786e"
+    },
+    {
+      "label": "\u68c0\u67e5\u884c\u4e1a\u96c6\u4e2d\u5ea6\u662f\u5426\u8d85\u6807                  Args:             positions: \u6301\u4ed3\u5217\u8868",
+      "file_type": "rationale",
+      "source_file": "strategies/guanyu_value_tech_strategy.py",
+      "source_location": "L654",
+      "id": "strategies_guanyu_value_tech_strategy_rationale_654",
+      "community": 169,
+      "norm_label": "\u68c0\u67e5\u884c\u4e1a\u96c6\u4e2d\u5ea6\u662f\u5426\u8d85\u6807                  args:             positions: \u6301\u4ed3\u5217\u8868"
+    },
+    {
+      "label": "\u8ba1\u7b97\u6b62\u635f\u4ef7\u683c                  \u65b9\u6cd5\uff1a         1. ma_method: \u6536\u76d8\u4ef7\u8dcc\u783420\u65e5\u5747\u7ebf         2. atr_meth",
+      "file_type": "rationale",
+      "source_file": "strategies/guanyu_value_tech_strategy.py",
+      "source_location": "L677",
+      "id": "strategies_guanyu_value_tech_strategy_rationale_677",
+      "community": 169,
+      "norm_label": "\u8ba1\u7b97\u6b62\u635f\u4ef7\u683c                  \u65b9\u6cd5:         1. ma_method: \u6536\u76d8\u4ef7\u8dcc\u783420\u65e5\u5747\u7ebf         2. atr_meth"
+    },
+    {
+      "label": "\u751f\u6210\u5165\u573a\u8ba2\u5355                  Args:             selected_stocks: \u9009\u4e2d\u7684\u80a1\u7968\u5217\u8868",
+      "file_type": "rationale",
+      "source_file": "strategies/guanyu_value_tech_strategy.py",
+      "source_location": "L712",
+      "id": "strategies_guanyu_value_tech_strategy_rationale_712",
+      "community": 169,
+      "norm_label": "\u751f\u6210\u5165\u573a\u8ba2\u5355                  args:             selected_stocks: \u9009\u4e2d\u7684\u80a1\u7968\u5217\u8868"
+    },
+    {
+      "label": "\u68c0\u67e5\u51fa\u573a\u4fe1\u53f7                  \u51fa\u573a\u6761\u4ef6\uff1a         1. \u6b62\u635f\uff1a\u4ef7\u683c\u8dcc\u7834\u6b62\u635f\u4ef7         2. \u5747\u7ebf\u6b62\u635f\uff1a\u6536\u76d8\u4ef7\u8dcc\u783420\u65e5\u5747\u7ebf",
+      "file_type": "rationale",
+      "source_file": "strategies/guanyu_value_tech_strategy.py",
+      "source_location": "L760",
+      "id": "strategies_guanyu_value_tech_strategy_rationale_760",
+      "community": 169,
+      "norm_label": "\u68c0\u67e5\u51fa\u573a\u4fe1\u53f7                  \u51fa\u573a\u6761\u4ef6:         1. \u6b62\u635f:\u4ef7\u683c\u8dcc\u7834\u6b62\u635f\u4ef7         2. \u5747\u7ebf\u6b62\u635f:\u6536\u76d8\u4ef7\u8dcc\u783420\u65e5\u5747\u7ebf"
+    },
+    {
+      "label": "\u5173\u7fbd - \u4ef7\u503c+\u6280\u672f\u7efc\u5408\u9009\u7b56\u7565\uff08\u4e3b\u7b56\u7565\uff09     =====================================          \u5b8c\u6574\u6d41\u7a0b\uff1a",
+      "file_type": "rationale",
+      "source_file": "strategies/guanyu_value_tech_strategy.py",
+      "source_location": "L797",
+      "id": "strategies_guanyu_value_tech_strategy_rationale_797",
+      "community": 248,
+      "norm_label": "\u5173\u7fbd - \u4ef7\u503c+\u6280\u672f\u7efc\u5408\u9009\u7b56\u7565(\u4e3b\u7b56\u7565)     =====================================          \u5b8c\u6574\u6d41\u7a0b:"
+    },
+    {
+      "label": "\u521d\u59cb\u5316\u7b56\u7565                  Args:             risk_profile: \u98ce\u9669\u504f\u597d ('conservative', 'ba",
+      "file_type": "rationale",
+      "source_file": "strategies/guanyu_value_tech_strategy.py",
+      "source_location": "L810",
+      "id": "strategies_guanyu_value_tech_strategy_rationale_810",
+      "community": 306,
+      "norm_label": "\u521d\u59cb\u5316\u7b56\u7565                  args:             risk_profile: \u98ce\u9669\u504f\u597d ('conservative', 'ba"
+    },
+    {
+      "label": "\u8fd0\u884c\u5b8c\u6574\u7b56\u7565                  Returns:             \u7b56\u7565\u6267\u884c\u7ed3\u679c",
+      "file_type": "rationale",
+      "source_file": "strategies/guanyu_value_tech_strategy.py",
+      "source_location": "L835",
+      "id": "strategies_guanyu_value_tech_strategy_rationale_835",
+      "community": 248,
+      "norm_label": "\u8fd0\u884c\u5b8c\u6574\u7b56\u7565                  returns:             \u7b56\u7565\u6267\u884c\u7ed3\u679c"
+    },
+    {
+      "label": "\u6253\u5370\u8ba2\u5355\u8be6\u60c5                  Args:             orders: \u8ba2\u5355\u5217\u8868",
+      "file_type": "rationale",
+      "source_file": "strategies/guanyu_value_tech_strategy.py",
+      "source_location": "L903",
+      "id": "strategies_guanyu_value_tech_strategy_rationale_903",
+      "community": 248,
+      "norm_label": "\u6253\u5370\u8ba2\u5355\u8be6\u60c5                  args:             orders: \u8ba2\u5355\u5217\u8868"
+    },
+    {
+      "label": "guanyu_config.py",
+      "file_type": "code",
+      "source_file": "strategies/guanyu_config.py",
+      "source_location": "L1",
+      "id": "strategies_guanyu_config_py",
+      "community": 509,
+      "norm_label": "guanyu_config.py"
+    },
+    {
+      "label": "get_default_config()",
+      "file_type": "code",
+      "source_file": "strategies/guanyu_config.py",
+      "source_location": "L98",
+      "id": "strategies_guanyu_config_get_default_config",
+      "community": 509,
+      "norm_label": "get_default_config()"
+    },
+    {
+      "label": "structural_market_risk.py",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/structural_market_risk.py",
+      "source_location": "L1",
+      "id": "strategies_pure_breakout_20260327_structural_market_risk_py",
+      "community": 120,
+      "norm_label": "structural_market_risk.py"
+    },
+    {
+      "label": "SectorInfo",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/structural_market_risk.py",
+      "source_location": "L18",
+      "id": "pure_breakout_20260327_structural_market_risk_sectorinfo",
+      "community": 120,
+      "norm_label": "sectorinfo"
+    },
+    {
+      "label": "StructuredMarketTiming",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/structural_market_risk.py",
+      "source_location": "L28",
+      "id": "pure_breakout_20260327_structural_market_risk_structuredmarkettiming",
+      "community": 120,
+      "norm_label": "structuredmarkettiming"
+    },
+    {
+      "label": ".__init__()",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/structural_market_risk.py",
+      "source_location": "L31",
+      "id": "pure_breakout_20260327_structural_market_risk_structuredmarkettiming_init",
+      "community": 120,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": ".timing_sector()",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/structural_market_risk.py",
+      "source_location": "L41",
+      "id": "pure_breakout_20260327_structural_market_risk_structuredmarkettiming_timing_sector",
+      "community": 120,
+      "norm_label": ".timing_sector()"
+    },
+    {
+      "label": "SectorConcentrationRisk",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/structural_market_risk.py",
+      "source_location": "L79",
+      "id": "pure_breakout_20260327_structural_market_risk_sectorconcentrationrisk",
+      "community": 120,
+      "norm_label": "sectorconcentrationrisk"
+    },
+    {
+      "label": ".__init__()",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/structural_market_risk.py",
+      "source_location": "L82",
+      "id": "pure_breakout_20260327_structural_market_risk_sectorconcentrationrisk_init",
+      "community": 120,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": ".check_concentration()",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/structural_market_risk.py",
+      "source_location": "L90",
+      "id": "pure_breakout_20260327_structural_market_risk_sectorconcentrationrisk_check_concentration",
+      "community": 120,
+      "norm_label": ".check_concentration()"
+    },
+    {
+      "label": "HotSectorNewsRiskAdjust",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/structural_market_risk.py",
+      "source_location": "L125",
+      "id": "pure_breakout_20260327_structural_market_risk_hotsectornewsriskadjust",
+      "community": 120,
+      "norm_label": "hotsectornewsriskadjust"
+    },
+    {
+      "label": ".__init__()",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/structural_market_risk.py",
+      "source_location": "L128",
+      "id": "pure_breakout_20260327_structural_market_risk_hotsectornewsriskadjust_init",
+      "community": 120,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": ".adjust_risk_score()",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/structural_market_risk.py",
+      "source_location": "L134",
+      "id": "pure_breakout_20260327_structural_market_risk_hotsectornewsriskadjust_adjust_risk_score",
+      "community": 120,
+      "norm_label": ".adjust_risk_score()"
+    },
+    {
+      "label": "get_structural_risk_report()",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/structural_market_risk.py",
+      "source_location": "L144",
+      "id": "pure_breakout_20260327_structural_market_risk_get_structural_risk_report",
+      "community": 120,
+      "norm_label": "get_structural_risk_report()"
+    },
+    {
+      "label": "\u7ed3\u6784\u5316\u884c\u60c5\u62e9\u65f6\u98ce\u63a7\u6a21\u5757 \u4e13\u95e8\u5904\u7406A\u80a1\u7ed3\u6784\u5316\u884c\u60c5\u4e0b\u7684\u677f\u5757\u96c6\u4e2d\u5ea6\u98ce\u9669\u548c\u62e9\u65f6\u4fe1\u53f7  \u529f\u80fd\uff1a 1. \u62e9\u65f6\uff1a\u5355\u677f\u5757\u8fde\u7eed\u5927\u6da8\u63d0\u9192\u98ce\u9669\uff0c\u8fde\u7eed\u5927\u8dcc\u63d0\u793a\u4f4e\u5438 2. \u98ce\u63a7\uff1a\u63a7\u5236\u677f\u5757",
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+      "source_file": "strategies/pure-breakout-20260327/structural_market_risk.py",
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+    },
+    {
+      "label": "\u677f\u5757\u62e9\u65f6         \u8fd4\u56de\uff1a(\u4fe1\u53f7\u7c7b\u578b, \u5efa\u8bae, \u98ce\u9669\u589e\u91cf\u8bc4\u5206)         \u4fe1\u53f7\u7c7b\u578b: bull/bear/neutral",
+      "file_type": "rationale",
+      "source_file": "strategies/pure-breakout-20260327/structural_market_risk.py",
+      "source_location": "L42",
+      "id": "pure_breakout_20260327_structural_market_risk_rationale_42",
+      "community": 120,
+      "norm_label": "\u677f\u5757\u62e9\u65f6         \u8fd4\u56de:(\u4fe1\u53f7\u7c7b\u578b, \u5efa\u8bae, \u98ce\u9669\u589e\u91cf\u8bc4\u5206)         \u4fe1\u53f7\u7c7b\u578b: bull/bear/neutral"
+    },
+    {
+      "label": "\u70ed\u70b9\u677f\u5757\u6d88\u606f\u98ce\u9669\u8c03\u6574\uff0c\u70ed\u70b9\u66f4\u5bb9\u6613\u5229\u597d\u51fa\u5c3d\uff0c\u7075\u654f\u5ea6\u63d0\u9ad8",
+      "file_type": "rationale",
+      "source_file": "strategies/pure-breakout-20260327/structural_market_risk.py",
+      "source_location": "L126",
+      "id": "pure_breakout_20260327_structural_market_risk_rationale_126",
+      "community": 120,
+      "norm_label": "\u70ed\u70b9\u677f\u5757\u6d88\u606f\u98ce\u9669\u8c03\u6574,\u70ed\u70b9\u66f4\u5bb9\u6613\u5229\u597d\u51fa\u5c3d,\u7075\u654f\u5ea6\u63d0\u9ad8"
+    },
+    {
+      "label": "__init__.py",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/__init__.py",
+      "source_location": "L1",
+      "id": "strategies_pure_breakout_20260327_init_py",
+      "community": 510,
+      "norm_label": "__init__.py"
+    },
+    {
+      "label": "\u7eaf\u7a81\u7834\u91cf\u5316\u7b56\u7565 - N\u65e5\u65b0\u9ad8\u653e\u91cf\u7a81\u7834\u4e70\u5165 - \u4e25\u683c\u6b62\u635f\u6b62\u76c8",
+      "file_type": "rationale",
+      "source_file": "strategies/pure-breakout-20260327/__init__.py",
+      "source_location": "L1",
+      "id": "pure_breakout_20260327_init_rationale_1",
+      "community": 510,
+      "norm_label": "\u7eaf\u7a81\u7834\u91cf\u5316\u7b56\u7565 - n\u65e5\u65b0\u9ad8\u653e\u91cf\u7a81\u7834\u4e70\u5165 - \u4e25\u683c\u6b62\u635f\u6b62\u76c8"
+    },
+    {
+      "label": "risk_control_breakout.py",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/risk_control_breakout.py",
+      "source_location": "L1",
+      "id": "strategies_pure_breakout_20260327_risk_control_breakout_py",
+      "community": 35,
+      "norm_label": "risk_control_breakout.py"
+    },
+    {
+      "label": "BreakoutStock",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/risk_control_breakout.py",
+      "source_location": "L19",
+      "id": "pure_breakout_20260327_risk_control_breakout_breakoutstock",
+      "community": 35,
+      "norm_label": "breakoutstock"
+    },
+    {
+      "label": "PortfolioInfo",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/risk_control_breakout.py",
+      "source_location": "L35",
+      "id": "pure_breakout_20260327_risk_control_breakout_portfolioinfo",
+      "community": 35,
+      "norm_label": "portfolioinfo"
+    },
+    {
+      "label": "BreakoutSingleStopLoss",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/risk_control_breakout.py",
+      "source_location": "L42",
+      "id": "pure_breakout_20260327_risk_control_breakout_breakoutsinglestoploss",
+      "community": 35,
+      "norm_label": "breakoutsinglestoploss"
+    },
+    {
+      "label": ".__init__()",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/risk_control_breakout.py",
+      "source_location": "L45",
+      "id": "pure_breakout_20260327_risk_control_breakout_breakoutsinglestoploss_init",
+      "community": 35,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": ".check_stop_loss()",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/risk_control_breakout.py",
+      "source_location": "L52",
+      "id": "pure_breakout_20260327_risk_control_breakout_breakoutsinglestoploss_check_stop_loss",
+      "community": 35,
+      "norm_label": ".check_stop_loss()"
+    },
+    {
+      "label": "SingleDayCrashReduce",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/risk_control_breakout.py",
+      "source_location": "L65",
+      "id": "pure_breakout_20260327_risk_control_breakout_singledaycrashreduce",
+      "community": 35,
+      "norm_label": "singledaycrashreduce"
+    },
+    {
+      "label": ".__init__()",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/risk_control_breakout.py",
+      "source_location": "L68",
+      "id": "pure_breakout_20260327_risk_control_breakout_singledaycrashreduce_init",
+      "community": 35,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": ".check_crash()",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/risk_control_breakout.py",
+      "source_location": "L77",
+      "id": "pure_breakout_20260327_risk_control_breakout_singledaycrashreduce_check_crash",
+      "community": 35,
+      "norm_label": ".check_crash()"
+    },
+    {
+      "label": ".get_target_position()",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/risk_control_breakout.py",
+      "source_location": "L82",
+      "id": "pure_breakout_20260327_risk_control_breakout_singledaycrashreduce_get_target_position",
+      "community": 35,
+      "norm_label": ".get_target_position()"
+    },
+    {
+      "label": "PortfolioDrawdownControl",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/risk_control_breakout.py",
+      "source_location": "L87",
+      "id": "pure_breakout_20260327_risk_control_breakout_portfoliodrawdowncontrol",
+      "community": 35,
+      "norm_label": "portfoliodrawdowncontrol"
+    },
+    {
+      "label": ".__init__()",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/risk_control_breakout.py",
+      "source_location": "L94",
+      "id": "pure_breakout_20260327_risk_control_breakout_portfoliodrawdowncontrol_init",
+      "community": 35,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": ".calculate_drawdown()",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/risk_control_breakout.py",
+      "source_location": "L111",
+      "id": "pure_breakout_20260327_risk_control_breakout_portfoliodrawdowncontrol_calculate_drawdown",
+      "community": 35,
+      "norm_label": ".calculate_drawdown()"
+    },
+    {
+      "label": ".get_target_position_ratio()",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/risk_control_breakout.py",
+      "source_location": "L117",
+      "id": "pure_breakout_20260327_risk_control_breakout_portfoliodrawdowncontrol_get_target_position_ratio",
+      "community": 35,
+      "norm_label": ".get_target_position_ratio()"
+    },
+    {
+      "label": ".need_adjust()",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/risk_control_breakout.py",
+      "source_location": "L128",
+      "id": "pure_breakout_20260327_risk_control_breakout_portfoliodrawdowncontrol_need_adjust",
+      "community": 35,
+      "norm_label": ".need_adjust()"
+    },
+    {
+      "label": "BreakoutPreTradeFilter",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/risk_control_breakout.py",
+      "source_location": "L140",
+      "id": "pure_breakout_20260327_risk_control_breakout_breakoutpretradefilter",
+      "community": 35,
+      "norm_label": "breakoutpretradefilter"
+    },
+    {
+      "label": ".__init__()",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/risk_control_breakout.py",
+      "source_location": "L143",
+      "id": "pure_breakout_20260327_risk_control_breakout_breakoutpretradefilter_init",
+      "community": 35,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": ".filter_stock()",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/risk_control_breakout.py",
+      "source_location": "L150",
+      "id": "pure_breakout_20260327_risk_control_breakout_breakoutpretradefilter_filter_stock",
+      "community": 35,
+      "norm_label": ".filter_stock()"
+    },
+    {
+      "label": ".filter_universe()",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/risk_control_breakout.py",
+      "source_location": "L172",
+      "id": "pure_breakout_20260327_risk_control_breakout_breakoutpretradefilter_filter_universe",
+      "community": 35,
+      "norm_label": ".filter_universe()"
+    },
+    {
+      "label": "BreakoutRiskController",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/risk_control_breakout.py",
+      "source_location": "L182",
+      "id": "pure_breakout_20260327_risk_control_breakout_breakoutriskcontroller",
+      "community": 35,
+      "norm_label": "breakoutriskcontroller"
+    },
+    {
+      "label": ".__init__()",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/risk_control_breakout.py",
+      "source_location": "L185",
+      "id": "pure_breakout_20260327_risk_control_breakout_breakoutriskcontroller_init",
+      "community": 35,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": ".pre_trade_check()",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/risk_control_breakout.py",
+      "source_location": "L191",
+      "id": "pure_breakout_20260327_risk_control_breakout_breakoutriskcontroller_pre_trade_check",
+      "community": 35,
+      "norm_label": ".pre_trade_check()"
+    },
+    {
+      "label": ".post_trade_check()",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/risk_control_breakout.py",
+      "source_location": "L211",
+      "id": "pure_breakout_20260327_risk_control_breakout_breakoutriskcontroller_post_trade_check",
+      "community": 35,
+      "norm_label": ".post_trade_check()"
+    },
+    {
+      "label": ".get_risk_report()",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/risk_control_breakout.py",
+      "source_location": "L262",
+      "id": "pure_breakout_20260327_risk_control_breakout_breakoutriskcontroller_get_risk_report",
+      "community": 35,
+      "norm_label": ".get_risk_report()"
+    },
+    {
+      "label": "\u7eaf\u7a81\u7834\u7b56\u7565\u98ce\u63a7\u6a21\u5757 \u529f\u80fd\uff1a 1. \u5355\u7968\u6b62\u635f\uff1a\u8dcc\u7834\u7a81\u7834\u65e5\u6700\u4f4e\u4ef75% \u2192 \u6b62\u635f\u5356\u51fa 2. \u5355\u65e5\u66b4\u8dcc\u8d85\u8fc77% \u2192 \u5f3a\u5236\u51cf\u4ed3 3. \u5168\u4ed3\u56de\u64a4\u63a7\u5236\uff1a\u6574\u4f53\u56de\u64a4\u8d85\u8fc710%\u964d\u4ed3",
+      "file_type": "rationale",
+      "source_file": "strategies/pure-breakout-20260327/risk_control_breakout.py",
+      "source_location": "L1",
+      "id": "pure_breakout_20260327_risk_control_breakout_rationale_1",
+      "community": 35,
+      "norm_label": "\u7eaf\u7a81\u7834\u7b56\u7565\u98ce\u63a7\u6a21\u5757 \u529f\u80fd: 1. \u5355\u7968\u6b62\u635f:\u8dcc\u7834\u7a81\u7834\u65e5\u6700\u4f4e\u4ef75% \u2192 \u6b62\u635f\u5356\u51fa 2. \u5355\u65e5\u66b4\u8dcc\u8d85\u8fc77% \u2192 \u5f3a\u5236\u51cf\u4ed3 3. \u5168\u4ed3\u56de\u64a4\u63a7\u5236:\u6574\u4f53\u56de\u64a4\u8d85\u8fc710%\u964d\u4ed3"
+    },
+    {
+      "label": "\u521d\u59cb\u5316         :param trigger_pct: \u8dcc\u7834\u7a81\u7834\u65e5\u6700\u4f4e\u4ef7\u591a\u5c11\u6bd4\u4f8b\u89e6\u53d1\u6b62\u635f\uff0c\u9ed8\u8ba45%",
+      "file_type": "rationale",
+      "source_file": "strategies/pure-breakout-20260327/risk_control_breakout.py",
+      "source_location": "L46",
+      "id": "pure_breakout_20260327_risk_control_breakout_rationale_46",
+      "community": 35,
+      "norm_label": "\u521d\u59cb\u5316         :param trigger_pct: \u8dcc\u7834\u7a81\u7834\u65e5\u6700\u4f4e\u4ef7\u591a\u5c11\u6bd4\u4f8b\u89e6\u53d1\u6b62\u635f,\u9ed8\u8ba45%"
+    },
+    {
+      "label": "\u68c0\u67e5\u662f\u5426\u89e6\u53d1\u6b62\u635f         :return: (\u662f\u5426\u89e6\u53d1, \u5f53\u524d\u4ef7\u683c\u76f8\u5bf9\u7a81\u7834\u4f4e\u70b9\u8dcc\u5e45)",
+      "file_type": "rationale",
+      "source_file": "strategies/pure-breakout-20260327/risk_control_breakout.py",
+      "source_location": "L53",
+      "id": "pure_breakout_20260327_risk_control_breakout_rationale_53",
+      "community": 35,
+      "norm_label": "\u68c0\u67e5\u662f\u5426\u89e6\u53d1\u6b62\u635f         :return: (\u662f\u5426\u89e6\u53d1, \u5f53\u524d\u4ef7\u683c\u76f8\u5bf9\u7a81\u7834\u4f4e\u70b9\u8dcc\u5e45)"
+    },
+    {
+      "label": "\u5355\u65e5\u66b4\u8dcc\u5f3a\u5236\u51cf\u4ed3\uff1a\u5355\u65e5\u66b4\u8dcc\u8d85\u8fc77%\u5f3a\u5236\u51cf\u4ed3",
+      "file_type": "rationale",
+      "source_file": "strategies/pure-breakout-20260327/risk_control_breakout.py",
+      "source_location": "L66",
+      "id": "pure_breakout_20260327_risk_control_breakout_rationale_66",
+      "community": 35,
+      "norm_label": "\u5355\u65e5\u66b4\u8dcc\u5f3a\u5236\u51cf\u4ed3:\u5355\u65e5\u66b4\u8dcc\u8d85\u8fc77%\u5f3a\u5236\u51cf\u4ed3"
+    },
+    {
+      "label": "\u521d\u59cb\u5316         :param crash_threshold: \u66b4\u8dcc\u9608\u503c\uff08%\uff09\uff0c\u9ed8\u8ba4-7%         :param reduce_ratio: \u51cf",
+      "file_type": "rationale",
+      "source_file": "strategies/pure-breakout-20260327/risk_control_breakout.py",
+      "source_location": "L69",
+      "id": "pure_breakout_20260327_risk_control_breakout_rationale_69",
+      "community": 35,
+      "norm_label": "\u521d\u59cb\u5316         :param crash_threshold: \u66b4\u8dcc\u9608\u503c(%),\u9ed8\u8ba4-7%         :param reduce_ratio: \u51cf"
+    },
+    {
+      "label": "\u5168\u4ed3\u56de\u64a4\u63a7\u5236     \u6574\u4f53\u56de\u64a4 > 10% \u2192 \u964d\u4ed3\u523050%     \u6574\u4f53\u56de\u64a4 > 20% \u2192 \u6e05\u534a\u4ed3\uff0c\u4fdd\u755925%",
+      "file_type": "rationale",
+      "source_file": "strategies/pure-breakout-20260327/risk_control_breakout.py",
+      "source_location": "L88",
+      "id": "pure_breakout_20260327_risk_control_breakout_rationale_88",
+      "community": 35,
+      "norm_label": "\u5168\u4ed3\u56de\u64a4\u63a7\u5236     \u6574\u4f53\u56de\u64a4 > 10% \u2192 \u964d\u4ed3\u523050%     \u6574\u4f53\u56de\u64a4 > 20% \u2192 \u6e05\u534a\u4ed3,\u4fdd\u755925%"
+    },
+    {
+      "label": "\u521d\u59cb\u5316         :param drawdown_1: \u4e00\u7ea7\u56de\u64a4\u9608\u503c         :param drawdown_2: \u4e8c\u7ea7\u56de\u64a4\u9608\u503c",
+      "file_type": "rationale",
+      "source_file": "strategies/pure-breakout-20260327/risk_control_breakout.py",
+      "source_location": "L99",
+      "id": "pure_breakout_20260327_risk_control_breakout_rationale_99",
+      "community": 35,
+      "norm_label": "\u521d\u59cb\u5316         :param drawdown_1: \u4e00\u7ea7\u56de\u64a4\u9608\u503c         :param drawdown_2: \u4e8c\u7ea7\u56de\u64a4\u9608\u503c"
+    },
+    {
+      "label": "\u521d\u59cb\u5316         :param min_avg_volume: \u6700\u5c0f\u65e5\u5747\u6210\u4ea4\u989d\uff08\u4ebf\uff09\uff0c\u9ed8\u8ba45000\u4e07",
+      "file_type": "rationale",
+      "source_file": "strategies/pure-breakout-20260327/risk_control_breakout.py",
+      "source_location": "L144",
+      "id": "pure_breakout_20260327_risk_control_breakout_rationale_144",
+      "community": 35,
+      "norm_label": "\u521d\u59cb\u5316         :param min_avg_volume: \u6700\u5c0f\u65e5\u5747\u6210\u4ea4\u989d(\u4ebf),\u9ed8\u8ba45000\u4e07"
+    },
+    {
+      "label": "\u5f00\u4ed3\u524d\u8fc7\u6ee4         :return: (\u662f\u5426\u53ef\u4ee5\u5f00\u4ed3, \u4e0d\u901a\u8fc7\u539f\u56e0)",
+      "file_type": "rationale",
+      "source_file": "strategies/pure-breakout-20260327/risk_control_breakout.py",
+      "source_location": "L151",
+      "id": "pure_breakout_20260327_risk_control_breakout_rationale_151",
+      "community": 35,
+      "norm_label": "\u5f00\u4ed3\u524d\u8fc7\u6ee4         :return: (\u662f\u5426\u53ef\u4ee5\u5f00\u4ed3, \u4e0d\u901a\u8fc7\u539f\u56e0)"
+    },
+    {
+      "label": "\u5f00\u4ed3\u524d\u68c0\u67e5         :return: (\u662f\u5426\u5141\u8bb8\u5f00\u4ed3, \u539f\u56e0)",
+      "file_type": "rationale",
+      "source_file": "strategies/pure-breakout-20260327/risk_control_breakout.py",
+      "source_location": "L192",
+      "id": "pure_breakout_20260327_risk_control_breakout_rationale_192",
+      "community": 35,
+      "norm_label": "\u5f00\u4ed3\u524d\u68c0\u67e5         :return: (\u662f\u5426\u5141\u8bb8\u5f00\u4ed3, \u539f\u56e0)"
+    },
+    {
+      "label": "\u6536\u76d8\u540e\u68c0\u67e5\uff0c\u627e\u51fa\u9700\u8981\u6b62\u635f\u51cf\u4ed3\u7684\u6807\u7684         :return: \u98ce\u63a7\u68c0\u67e5\u7ed3\u679c",
+      "file_type": "rationale",
+      "source_file": "strategies/pure-breakout-20260327/risk_control_breakout.py",
+      "source_location": "L212",
+      "id": "pure_breakout_20260327_risk_control_breakout_rationale_212",
+      "community": 35,
+      "norm_label": "\u6536\u76d8\u540e\u68c0\u67e5,\u627e\u51fa\u9700\u8981\u6b62\u635f\u51cf\u4ed3\u7684\u6807\u7684         :return: \u98ce\u63a7\u68c0\u67e5\u7ed3\u679c"
+    },
+    {
+      "label": "main_strategy.py",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/main_strategy.py",
+      "source_location": "L1",
+      "id": "strategies_pure_breakout_20260327_main_strategy_py",
+      "community": 85,
+      "norm_label": "main_strategy.py"
+    },
+    {
+      "label": "PureBreakoutStrategy",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/main_strategy.py",
+      "source_location": "L14",
+      "id": "pure_breakout_20260327_main_strategy_purebreakoutstrategy",
+      "community": 85,
+      "norm_label": "purebreakoutstrategy"
+    },
+    {
+      "label": "CtaTemplate",
+      "file_type": "code",
+      "source_file": "",
+      "source_location": "",
+      "id": "ctatemplate",
+      "community": 207,
+      "norm_label": "ctatemplate"
+    },
+    {
+      "label": ".__init__()",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/main_strategy.py",
+      "source_location": "L42",
+      "id": "pure_breakout_20260327_main_strategy_purebreakoutstrategy_init",
+      "community": 85,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": ".on_init()",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/main_strategy.py",
+      "source_location": "L66",
+      "id": "pure_breakout_20260327_main_strategy_purebreakoutstrategy_on_init",
+      "community": 85,
+      "norm_label": ".on_init()"
+    },
+    {
+      "label": ".on_start()",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/main_strategy.py",
+      "source_location": "L71",
+      "id": "pure_breakout_20260327_main_strategy_purebreakoutstrategy_on_start",
+      "community": 85,
+      "norm_label": ".on_start()"
+    },
+    {
+      "label": ".on_stop()",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/main_strategy.py",
+      "source_location": "L75",
+      "id": "pure_breakout_20260327_main_strategy_purebreakoutstrategy_on_stop",
+      "community": 85,
+      "norm_label": ".on_stop()"
+    },
+    {
+      "label": ".on_bar()",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/main_strategy.py",
+      "source_location": "L79",
+      "id": "pure_breakout_20260327_main_strategy_purebreakoutstrategy_on_bar",
+      "community": 85,
+      "norm_label": ".on_bar()"
+    },
+    {
+      "label": "._update_holding()",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/main_strategy.py",
+      "source_location": "L98",
+      "id": "pure_breakout_20260327_main_strategy_purebreakoutstrategy_update_holding",
+      "community": 85,
+      "norm_label": "._update_holding()"
+    },
+    {
+      "label": "._check_exit()",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/main_strategy.py",
+      "source_location": "L107",
+      "id": "pure_breakout_20260327_main_strategy_purebreakoutstrategy_check_exit",
+      "community": 85,
+      "norm_label": "._check_exit()"
+    },
+    {
+      "label": "._check_entry()",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/main_strategy.py",
+      "source_location": "L137",
+      "id": "pure_breakout_20260327_main_strategy_purebreakoutstrategy_check_entry",
+      "community": 85,
+      "norm_label": "._check_entry()"
+    },
+    {
+      "label": "._is_new_high()",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/main_strategy.py",
+      "source_location": "L157",
+      "id": "pure_breakout_20260327_main_strategy_purebreakoutstrategy_is_new_high",
+      "community": 85,
+      "norm_label": "._is_new_high()"
+    },
+    {
+      "label": "._is_volume_enough()",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/main_strategy.py",
+      "source_location": "L170",
+      "id": "pure_breakout_20260327_main_strategy_purebreakoutstrategy_is_volume_enough",
+      "community": 85,
+      "norm_label": "._is_volume_enough()"
+    },
+    {
+      "label": ".calculate_ma()",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/main_strategy.py",
+      "source_location": "L183",
+      "id": "pure_breakout_20260327_main_strategy_purebreakoutstrategy_calculate_ma",
+      "community": 85,
+      "norm_label": ".calculate_ma()"
+    },
+    {
+      "label": ".calculate_current_total_position()",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/main_strategy.py",
+      "source_location": "L192",
+      "id": "pure_breakout_20260327_main_strategy_purebreakoutstrategy_calculate_current_total_position",
+      "community": 85,
+      "norm_label": ".calculate_current_total_position()"
+    },
+    {
+      "label": "._enter_position()",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/main_strategy.py",
+      "source_location": "L206",
+      "id": "pure_breakout_20260327_main_strategy_purebreakoutstrategy_enter_position",
+      "community": 85,
+      "norm_label": "._enter_position()"
+    },
+    {
+      "label": "._exit_position()",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/main_strategy.py",
+      "source_location": "L238",
+      "id": "pure_breakout_20260327_main_strategy_purebreakoutstrategy_exit_position",
+      "community": 85,
+      "norm_label": "._exit_position()"
+    },
+    {
+      "label": ".get_bars()",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/main_strategy.py",
+      "source_location": "L262",
+      "id": "pure_breakout_20260327_main_strategy_purebreakoutstrategy_get_bars",
+      "community": 85,
+      "norm_label": ".get_bars()"
+    },
+    {
+      "label": ".get_last_bar()",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/main_strategy.py",
+      "source_location": "L267",
+      "id": "pure_breakout_20260327_main_strategy_purebreakoutstrategy_get_last_bar",
+      "community": 85,
+      "norm_label": ".get_last_bar()"
+    },
+    {
+      "label": ".get_position()",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/main_strategy.py",
+      "source_location": "L274",
+      "id": "pure_breakout_20260327_main_strategy_purebreakoutstrategy_get_position",
+      "community": 85,
+      "norm_label": ".get_position()"
+    },
+    {
+      "label": "\u7eaf\u7a81\u7834\u91cf\u5316\u7b56\u7565 \u903b\u8f91: N\u65e5\u65b0\u9ad8\u653e\u91cf\u7a81\u7834\u4e70\u5165\uff0c\u4e25\u683c\u6b62\u635f\u6b62\u76c8\u5356\u51fa",
+      "file_type": "rationale",
+      "source_file": "strategies/pure-breakout-20260327/main_strategy.py",
+      "source_location": "L1",
+      "id": "pure_breakout_20260327_main_strategy_rationale_1",
+      "community": 85,
+      "norm_label": "\u7eaf\u7a81\u7834\u91cf\u5316\u7b56\u7565 \u903b\u8f91: n\u65e5\u65b0\u9ad8\u653e\u91cf\u7a81\u7834\u4e70\u5165,\u4e25\u683c\u6b62\u635f\u6b62\u76c8\u5356\u51fa"
+    },
+    {
+      "label": "\u7eaf\u7a81\u7834\u7b56\u7565     - \u7a81\u7834N\u65e5\u65b0\u9ad8 + \u653e\u91cf\u4e70\u5165     - \u4e25\u683c\u6b62\u635f\uff08\u8dcc\u7834\u7a81\u7834\u6700\u4f4e\u4ef75%\uff09     - \u8ddf\u8e2a\u6b62\u76c8\uff08\u4ece\u9ad8\u70b9\u56de\u843d10%\uff09     - \u5747\u7ebf\u6b62\u76c8\uff08",
+      "file_type": "rationale",
+      "source_file": "strategies/pure-breakout-20260327/main_strategy.py",
+      "source_location": "L15",
+      "id": "pure_breakout_20260327_main_strategy_rationale_15",
+      "community": 85,
+      "norm_label": "\u7eaf\u7a81\u7834\u7b56\u7565     - \u7a81\u7834n\u65e5\u65b0\u9ad8 + \u653e\u91cf\u4e70\u5165     - \u4e25\u683c\u6b62\u635f(\u8dcc\u7834\u7a81\u7834\u6700\u4f4e\u4ef75%)     - \u8ddf\u8e2a\u6b62\u76c8(\u4ece\u9ad8\u70b9\u56de\u843d10%)     - \u5747\u7ebf\u6b62\u76c8("
+    },
+    {
+      "label": "main_strategy_single_file.py",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/main_strategy_single_file.py",
+      "source_location": "L1",
+      "id": "strategies_pure_breakout_20260327_main_strategy_single_file_py",
+      "community": 207,
+      "norm_label": "main_strategy_single_file.py"
+    },
+    {
+      "label": "PureBreakoutStrategy",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/main_strategy_single_file.py",
+      "source_location": "L13",
+      "id": "pure_breakout_20260327_main_strategy_single_file_purebreakoutstrategy",
+      "community": 207,
+      "norm_label": "purebreakoutstrategy"
+    },
+    {
+      "label": ".__init__()",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/main_strategy_single_file.py",
+      "source_location": "L38",
+      "id": "pure_breakout_20260327_main_strategy_single_file_purebreakoutstrategy_init",
+      "community": 207,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": ".on_init()",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/main_strategy_single_file.py",
+      "source_location": "L58",
+      "id": "pure_breakout_20260327_main_strategy_single_file_purebreakoutstrategy_on_init",
+      "community": 207,
+      "norm_label": ".on_init()"
+    },
+    {
+      "label": ".on_start()",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/main_strategy_single_file.py",
+      "source_location": "L62",
+      "id": "pure_breakout_20260327_main_strategy_single_file_purebreakoutstrategy_on_start",
+      "community": 207,
+      "norm_label": ".on_start()"
+    },
+    {
+      "label": ".on_stop()",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/main_strategy_single_file.py",
+      "source_location": "L65",
+      "id": "pure_breakout_20260327_main_strategy_single_file_purebreakoutstrategy_on_stop",
+      "community": 207,
+      "norm_label": ".on_stop()"
+    },
+    {
+      "label": ".on_bar()",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/main_strategy_single_file.py",
+      "source_location": "L68",
+      "id": "pure_breakout_20260327_main_strategy_single_file_purebreakoutstrategy_on_bar",
+      "community": 207,
+      "norm_label": ".on_bar()"
+    },
+    {
+      "label": "._need_rebalance()",
+      "file_type": "code",
+      "source_file": "strategies/pure-breakout-20260327/main_strategy_single_file.py",
+      "source_location": "L148",
+      "id": "pure_breakout_20260327_main_strategy_single_file_purebreakoutstrategy_need_rebalance",
+      "community": 207,
+      "norm_label": "._need_rebalance()"
+    },
+    {
+      "label": "\u7eaf\u7a81\u7834\u7b56\u7565     - N\u65e5\u65b0\u9ad8\u653e\u91cf\u7a81\u7834\u4e70\u5165     - \u6b62\u635f\uff1a\u8dcc\u7834\u7a81\u7834\u65e5\u6700\u4f4e\u4ef7\u7684-5%     - \u8ddf\u8e2a\u6b62\u76c8\uff1a\u4ece\u4e70\u5165\u540e\u9ad8\u70b9\u56de\u843d10%\u6b62\u76c8     - \u5747\u7ebf\u6b62\u76c8",
+      "file_type": "rationale",
+      "source_file": "strategies/pure-breakout-20260327/main_strategy_single_file.py",
+      "source_location": "L14",
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+      "label": "InternationalLinkageMonitor",
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+      "norm_label": "risk_control.py"
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+      "id": "structured_dynamic_factors_20260327_risk_control_risklevel",
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+      "norm_label": "risklevel"
+    },
+    {
+      "label": "Sentiment",
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+      "source_location": "L26",
+      "id": "structured_dynamic_factors_20260327_risk_control_sentiment",
+      "community": 74,
+      "norm_label": "sentiment"
+    },
+    {
+      "label": "IndividualStockRisk",
+      "file_type": "code",
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+      "source_location": "L37",
+      "id": "structured_dynamic_factors_20260327_risk_control_individualstockrisk",
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+      "norm_label": "individualstockrisk"
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+      "label": "SectorInfo",
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+      "source_file": "strategies/structured-dynamic-factors-20260327/risk_control.py",
+      "source_location": "L76",
+      "id": "structured_dynamic_factors_20260327_risk_control_sectorinfo",
+      "community": 74,
+      "norm_label": "sectorinfo"
+    },
+    {
+      "label": "OverallRiskResult",
+      "file_type": "code",
+      "source_file": "strategies/structured-dynamic-factors-20260327/risk_control.py",
+      "source_location": "L87",
+      "id": "structured_dynamic_factors_20260327_risk_control_overallriskresult",
+      "community": 74,
+      "norm_label": "overallriskresult"
+    },
+    {
+      "label": "RiskConfig",
+      "file_type": "code",
+      "source_file": "strategies/structured-dynamic-factors-20260327/risk_control.py",
+      "source_location": "L101",
+      "id": "structured_dynamic_factors_20260327_risk_control_riskconfig",
+      "community": 74,
+      "norm_label": "riskconfig"
+    },
+    {
+      "label": "IndividualRiskAssessor",
+      "file_type": "code",
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+      "id": "structured_dynamic_factors_20260327_risk_control_individualriskassessor",
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+      "norm_label": "individualriskassessor"
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+      "norm_label": ".__init__()"
+    },
+    {
+      "label": ".assess_base_five_dimension()",
+      "file_type": "code",
+      "source_file": "strategies/structured-dynamic-factors-20260327/risk_control.py",
+      "source_location": "L154",
+      "id": "structured_dynamic_factors_20260327_risk_control_individualriskassessor_assess_base_five_dimension",
+      "community": 74,
+      "norm_label": ".assess_base_five_dimension()"
+    },
+    {
+      "label": ".assess_news_risk()",
+      "file_type": "code",
+      "source_file": "strategies/structured-dynamic-factors-20260327/risk_control.py",
+      "source_location": "L164",
+      "id": "structured_dynamic_factors_20260327_risk_control_individualriskassessor_assess_news_risk",
+      "community": 74,
+      "norm_label": ".assess_news_risk()"
+    },
+    {
+      "label": "StructuralSectorTiming",
+      "file_type": "code",
+      "source_file": "strategies/structured-dynamic-factors-20260327/risk_control.py",
+      "source_location": "L237",
+      "id": "structured_dynamic_factors_20260327_risk_control_structuralsectortiming",
+      "community": 74,
+      "norm_label": "structuralsectortiming"
+    },
+    {
+      "label": ".__init__()",
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+      "source_location": "L240",
+      "id": "structured_dynamic_factors_20260327_risk_control_structuralsectortiming_init",
+      "community": 74,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": ".timing_single_sector()",
+      "file_type": "code",
+      "source_file": "strategies/structured-dynamic-factors-20260327/risk_control.py",
+      "source_location": "L243",
+      "id": "structured_dynamic_factors_20260327_risk_control_structuralsectortiming_timing_single_sector",
+      "community": 74,
+      "norm_label": ".timing_single_sector()"
+    },
+    {
+      "label": "SectorConcentrationControl",
+      "file_type": "code",
+      "source_file": "strategies/structured-dynamic-factors-20260327/risk_control.py",
+      "source_location": "L278",
+      "id": "structured_dynamic_factors_20260327_risk_control_sectorconcentrationcontrol",
+      "community": 74,
+      "norm_label": "sectorconcentrationcontrol"
+    },
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+      "label": ".__init__()",
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+      "source_location": "L281",
+      "id": "structured_dynamic_factors_20260327_risk_control_sectorconcentrationcontrol_init",
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+      "norm_label": ".__init__()"
+    },
+    {
+      "label": ".check_concentration()",
+      "file_type": "code",
+      "source_file": "strategies/structured-dynamic-factors-20260327/risk_control.py",
+      "source_location": "L284",
+      "id": "structured_dynamic_factors_20260327_risk_control_sectorconcentrationcontrol_check_concentration",
+      "community": 74,
+      "norm_label": ".check_concentration()"
+    },
+    {
+      "label": "StructuredDynamicFactorsRiskControl",
+      "file_type": "code",
+      "source_file": "strategies/structured-dynamic-factors-20260327/risk_control.py",
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+      "community": 74,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": ".assess_stock()",
+      "file_type": "code",
+      "source_file": "strategies/structured-dynamic-factors-20260327/risk_control.py",
+      "source_location": "L328",
+      "id": "structured_dynamic_factors_20260327_risk_control_structureddynamicfactorsriskcontrol_assess_stock",
+      "community": 74,
+      "norm_label": ".assess_stock()"
+    },
+    {
+      "label": ".assess_portfolio()",
+      "file_type": "code",
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+      "source_location": "L365",
+      "id": "structured_dynamic_factors_20260327_risk_control_structureddynamicfactorsriskcontrol_assess_portfolio",
+      "community": 74,
+      "norm_label": ".assess_portfolio()"
+    },
+    {
+      "label": ".get_risk_report()",
+      "file_type": "code",
+      "source_file": "strategies/structured-dynamic-factors-20260327/risk_control.py",
+      "source_location": "L423",
+      "id": "structured_dynamic_factors_20260327_risk_control_structureddynamicfactorsriskcontrol_get_risk_report",
+      "community": 74,
+      "norm_label": ".get_risk_report()"
+    },
+    {
+      "label": ".get_sector_timing_report()",
+      "file_type": "code",
+      "source_file": "strategies/structured-dynamic-factors-20260327/risk_control.py",
+      "source_location": "L453",
+      "id": "structured_dynamic_factors_20260327_risk_control_structureddynamicfactorsriskcontrol_get_sector_timing_report",
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+      "norm_label": ".get_sector_timing_report()"
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+    {
+      "label": "risk_warning_execution.py",
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+      "norm_label": "risk_warning_execution.py"
+    },
+    {
+      "label": "WarningLevel",
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+      "id": "structured_dynamic_factors_20260327_risk_warning_execution_warninglevel",
+      "community": 52,
+      "norm_label": "warninglevel"
+    },
+    {
+      "label": "WarningMessage",
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+      "norm_label": "riskwarningconfig"
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+    {
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+      "id": "structured_dynamic_factors_20260327_risk_warning_execution_individualriskwarning",
+      "community": 52,
+      "norm_label": "individualriskwarning"
+    },
+    {
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+      "file_type": "code",
+      "source_file": "strategies/structured-dynamic-factors-20260327/risk_warning_execution.py",
+      "source_location": "L70",
+      "id": "structured_dynamic_factors_20260327_risk_warning_execution_individualriskwarning_init",
+      "community": 52,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": ".evaluate()",
+      "file_type": "code",
+      "source_file": "strategies/structured-dynamic-factors-20260327/risk_warning_execution.py",
+      "source_location": "L73",
+      "id": "structured_dynamic_factors_20260327_risk_warning_execution_individualriskwarning_evaluate",
+      "community": 52,
+      "norm_label": ".evaluate()"
+    },
+    {
+      "label": ".calculate_target_position()",
+      "file_type": "code",
+      "source_file": "strategies/structured-dynamic-factors-20260327/risk_warning_execution.py",
+      "source_location": "L84",
+      "id": "structured_dynamic_factors_20260327_risk_warning_execution_individualriskwarning_calculate_target_position",
+      "community": 52,
+      "norm_label": ".calculate_target_position()"
+    },
+    {
+      "label": "SectorRiskWarning",
+      "file_type": "code",
+      "source_file": "strategies/structured-dynamic-factors-20260327/risk_warning_execution.py",
+      "source_location": "L98",
+      "id": "structured_dynamic_factors_20260327_risk_warning_execution_sectorriskwarning",
+      "community": 52,
+      "norm_label": "sectorriskwarning"
+    },
+    {
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+      "source_location": "L101",
+      "id": "structured_dynamic_factors_20260327_risk_warning_execution_sectorriskwarning_init",
+      "community": 52,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": ".evaluate()",
+      "file_type": "code",
+      "source_file": "strategies/structured-dynamic-factors-20260327/risk_warning_execution.py",
+      "source_location": "L104",
+      "id": "structured_dynamic_factors_20260327_risk_warning_execution_sectorriskwarning_evaluate",
+      "community": 52,
+      "norm_label": ".evaluate()"
+    },
+    {
+      "label": ".get_target_ratio()",
+      "file_type": "code",
+      "source_file": "strategies/structured-dynamic-factors-20260327/risk_warning_execution.py",
+      "source_location": "L114",
+      "id": "structured_dynamic_factors_20260327_risk_warning_execution_sectorriskwarning_get_target_ratio",
+      "community": 52,
+      "norm_label": ".get_target_ratio()"
+    },
+    {
+      "label": "PortfolioRiskWarning",
+      "file_type": "code",
+      "source_file": "strategies/structured-dynamic-factors-20260327/risk_warning_execution.py",
+      "source_location": "L126",
+      "id": "structured_dynamic_factors_20260327_risk_warning_execution_portfolioriskwarning",
+      "community": 52,
+      "norm_label": "portfolioriskwarning"
+    },
+    {
+      "label": ".__init__()",
+      "file_type": "code",
+      "source_file": "strategies/structured-dynamic-factors-20260327/risk_warning_execution.py",
+      "source_location": "L129",
+      "id": "structured_dynamic_factors_20260327_risk_warning_execution_portfolioriskwarning_init",
+      "community": 52,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": ".evaluate()",
+      "file_type": "code",
+      "source_file": "strategies/structured-dynamic-factors-20260327/risk_warning_execution.py",
+      "source_location": "L132",
+      "id": "structured_dynamic_factors_20260327_risk_warning_execution_portfolioriskwarning_evaluate",
+      "community": 52,
+      "norm_label": ".evaluate()"
+    },
+    {
+      "label": ".get_overall_target_ratio()",
+      "file_type": "code",
+      "source_file": "strategies/structured-dynamic-factors-20260327/risk_warning_execution.py",
+      "source_location": "L142",
+      "id": "structured_dynamic_factors_20260327_risk_warning_execution_portfolioriskwarning_get_overall_target_ratio",
+      "community": 52,
+      "norm_label": ".get_overall_target_ratio()"
+    },
+    {
+      "label": "RiskWarningSystem",
+      "file_type": "code",
+      "source_file": "strategies/structured-dynamic-factors-20260327/risk_warning_execution.py",
+      "source_location": "L154",
+      "id": "structured_dynamic_factors_20260327_risk_warning_execution_riskwarningsystem",
+      "community": 52,
+      "norm_label": "riskwarningsystem"
+    },
+    {
+      "label": ".__init__()",
+      "file_type": "code",
+      "source_file": "strategies/structured-dynamic-factors-20260327/risk_warning_execution.py",
+      "source_location": "L157",
+      "id": "structured_dynamic_factors_20260327_risk_warning_execution_riskwarningsystem_init",
+      "community": 52,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": ".register_execution_callback()",
+      "file_type": "code",
+      "source_file": "strategies/structured-dynamic-factors-20260327/risk_warning_execution.py",
+      "source_location": "L165",
+      "id": "structured_dynamic_factors_20260327_risk_warning_execution_riskwarningsystem_register_execution_callback",
+      "community": 52,
+      "norm_label": ".register_execution_callback()"
+    },
+    {
+      "label": ".evaluate_stock()",
+      "file_type": "code",
+      "source_file": "strategies/structured-dynamic-factors-20260327/risk_warning_execution.py",
+      "source_location": "L169",
+      "id": "structured_dynamic_factors_20260327_risk_warning_execution_riskwarningsystem_evaluate_stock",
+      "community": 52,
+      "norm_label": ".evaluate_stock()"
+    },
+    {
+      "label": ".evaluate_sector()",
+      "file_type": "code",
+      "source_file": "strategies/structured-dynamic-factors-20260327/risk_warning_execution.py",
+      "source_location": "L200",
+      "id": "structured_dynamic_factors_20260327_risk_warning_execution_riskwarningsystem_evaluate_sector",
+      "community": 52,
+      "norm_label": ".evaluate_sector()"
+    },
+    {
+      "label": ".evaluate_portfolio()",
+      "file_type": "code",
+      "source_file": "strategies/structured-dynamic-factors-20260327/risk_warning_execution.py",
+      "source_location": "L230",
+      "id": "structured_dynamic_factors_20260327_risk_warning_execution_riskwarningsystem_evaluate_portfolio",
+      "community": 52,
+      "norm_label": ".evaluate_portfolio()"
+    },
+    {
+      "label": ".get_pending_warnings()",
+      "file_type": "code",
+      "source_file": "strategies/structured-dynamic-factors-20260327/risk_warning_execution.py",
+      "source_location": "L257",
+      "id": "structured_dynamic_factors_20260327_risk_warning_execution_riskwarningsystem_get_pending_warnings",
+      "community": 52,
+      "norm_label": ".get_pending_warnings()"
+    },
+    {
+      "label": ".mark_executed()",
+      "file_type": "code",
+      "source_file": "strategies/structured-dynamic-factors-20260327/risk_warning_execution.py",
+      "source_location": "L261",
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+      "norm_label": ".get_risk_alerts()"
+    },
+    {
+      "label": ".get_rotation_report()",
+      "file_type": "code",
+      "source_file": "strategies/structured-dynamic-factors-20260327/policy_news_parser.py",
+      "source_location": "L285",
+      "id": "structured_dynamic_factors_20260327_policy_news_parser_policyrotationmodule_get_rotation_report",
+      "community": 90,
+      "norm_label": ".get_rotation_report()"
+    },
+    {
+      "label": "\u653f\u7b56\u6d88\u606f\u89e3\u6790\u6a21\u5757 \u529f\u80fd\uff1a 1. \u653f\u7b56\u6d88\u606f\u5206\u7c7b\uff08\u8d27\u5e01/\u8d22\u653f/\u4ea7\u4e1a/\u76d1\u7ba1\uff09 2. \u653f\u7b56\u529b\u5ea6\u5206\u7ea7 3. \u53d7\u76ca\u677f\u5757\u8bc6\u522b 4. \u653f\u7b56\u9a71\u52a8\u8f6e\u52a8\u4fe1\u53f7\u751f\u6210 5. \u5229\u7a7a\u653f\u7b56\u9884\u8b66",
+      "file_type": "rationale",
+      "source_file": "strategies/structured-dynamic-factors-20260327/policy_news_parser.py",
+      "source_location": "L1",
+      "id": "structured_dynamic_factors_20260327_policy_news_parser_rationale_1",
+      "community": 89,
+      "norm_label": "\u653f\u7b56\u6d88\u606f\u89e3\u6790\u6a21\u5757 \u529f\u80fd: 1. \u653f\u7b56\u6d88\u606f\u5206\u7c7b(\u8d27\u5e01/\u8d22\u653f/\u4ea7\u4e1a/\u76d1\u7ba1) 2. \u653f\u7b56\u529b\u5ea6\u5206\u7ea7 3. \u53d7\u76ca\u677f\u5757\u8bc6\u522b 4. \u653f\u7b56\u9a71\u52a8\u8f6e\u52a8\u4fe1\u53f7\u751f\u6210 5. \u5229\u7a7a\u653f\u7b56\u9884\u8b66"
+    },
+    {
+      "label": "\u68c0\u67e5\u653f\u7b56\u98ce\u9669         \u8fd4\u56de\uff1a(\u662f\u5426\u9ad8\u98ce\u9669, \u98ce\u9669\u7b49\u7ea7 1~3, \u539f\u56e0)",
+      "file_type": "rationale",
+      "source_file": "strategies/structured-dynamic-factors-20260327/policy_news_parser.py",
+      "source_location": "L241",
+      "id": "structured_dynamic_factors_20260327_policy_news_parser_rationale_241",
+      "community": 90,
+      "norm_label": "\u68c0\u67e5\u653f\u7b56\u98ce\u9669         \u8fd4\u56de:(\u662f\u5426\u9ad8\u98ce\u9669, \u98ce\u9669\u7b49\u7ea7 1~3, \u539f\u56e0)"
+    },
+    {
+      "label": "tech_timing_signal.py",
+      "file_type": "code",
+      "source_file": "strategies/structured-dynamic-factors-20260327/strategies/tech_timing_signal.py",
+      "source_location": "L1",
+      "id": "strategies_structured_dynamic_factors_20260327_strategies_tech_timing_signal_py",
+      "community": 136,
+      "norm_label": "tech_timing_signal.py"
+    },
+    {
+      "label": "TechnicalTimingSignals",
+      "file_type": "code",
+      "source_file": "strategies/structured-dynamic-factors-20260327/strategies/tech_timing_signal.py",
+      "source_location": "L15",
+      "id": "strategies_tech_timing_signal_technicaltimingsignals",
+      "community": 98,
+      "norm_label": "technicaltimingsignals"
+    },
+    {
+      "label": ".__init__()",
+      "file_type": "code",
+      "source_file": "strategies/structured-dynamic-factors-20260327/strategies/tech_timing_signal.py",
+      "source_location": "L18",
+      "id": "strategies_tech_timing_signal_technicaltimingsignals_init",
+      "community": 98,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": ".ma_bullish()",
+      "file_type": "code",
+      "source_file": "strategies/structured-dynamic-factors-20260327/strategies/tech_timing_signal.py",
+      "source_location": "L21",
+      "id": "strategies_tech_timing_signal_technicaltimingsignals_ma_bullish",
+      "community": 98,
+      "norm_label": ".ma_bullish()"
+    },
+    {
+      "label": ".ma_bearish()",
+      "file_type": "code",
+      "source_file": "strategies/structured-dynamic-factors-20260327/strategies/tech_timing_signal.py",
+      "source_location": "L41",
+      "id": "strategies_tech_timing_signal_technicaltimingsignals_ma_bearish",
+      "community": 98,
+      "norm_label": ".ma_bearish()"
+    },
+    {
+      "label": ".above_ma()",
+      "file_type": "code",
+      "source_file": "strategies/structured-dynamic-factors-20260327/strategies/tech_timing_signal.py",
+      "source_location": "L46",
+      "id": "strategies_tech_timing_signal_technicaltimingsignals_above_ma",
+      "community": 98,
+      "norm_label": ".above_ma()"
+    },
+    {
+      "label": ".macd_signal()",
+      "file_type": "code",
+      "source_file": "strategies/structured-dynamic-factors-20260327/strategies/tech_timing_signal.py",
+      "source_location": "L54",
+      "id": "strategies_tech_timing_signal_technicaltimingsignals_macd_signal",
+      "community": 98,
+      "norm_label": ".macd_signal()"
+    },
+    {
+      "label": ".bollinger_signal()",
+      "file_type": "code",
+      "source_file": "strategies/structured-dynamic-factors-20260327/strategies/tech_timing_signal.py",
+      "source_location": "L85",
+      "id": "strategies_tech_timing_signal_technicaltimingsignals_bollinger_signal",
+      "community": 98,
+      "norm_label": ".bollinger_signal()"
+    },
+    {
+      "label": ".rsi_signal()",
+      "file_type": "code",
+      "source_file": "strategies/structured-dynamic-factors-20260327/strategies/tech_timing_signal.py",
+      "source_location": "L112",
+      "id": "strategies_tech_timing_signal_technicaltimingsignals_rsi_signal",
+      "community": 98,
+      "norm_label": ".rsi_signal()"
+    },
+    {
+      "label": ".kdj_signal()",
+      "file_type": "code",
+      "source_file": "strategies/structured-dynamic-factors-20260327/strategies/tech_timing_signal.py",
+      "source_location": "L143",
+      "id": "strategies_tech_timing_signal_technicaltimingsignals_kdj_signal",
+      "community": 98,
+      "norm_label": ".kdj_signal()"
+    },
+    {
+      "label": ".combine_signals()",
+      "file_type": "code",
+      "source_file": "strategies/structured-dynamic-factors-20260327/strategies/tech_timing_signal.py",
+      "source_location": "L180",
+      "id": "strategies_tech_timing_signal_technicaltimingsignals_combine_signals",
+      "community": 98,
+      "norm_label": ".combine_signals()"
+    },
+    {
+      "label": ".filter_stocks_by_timing()",
+      "file_type": "code",
+      "source_file": "strategies/structured-dynamic-factors-20260327/strategies/tech_timing_signal.py",
+      "source_location": "L200",
+      "id": "strategies_tech_timing_signal_technicaltimingsignals_filter_stocks_by_timing",
+      "community": 98,
+      "norm_label": ".filter_stocks_by_timing()"
+    },
+    {
+      "label": "\u6280\u672f\u62e9\u65f6\u4fe1\u53f7\u7cfb\u7edf \u652f\u6301\u591a\u79cd\u6280\u672f\u62e9\u65f6\u4fe1\u53f7\uff1a - \u5747\u7ebf\u591a\u5934\u6392\u5217 - MACD\u91d1\u53c9/\u6b7b\u53c9 - \u7a81\u7834\u5e03\u6797\u5e26\u4e0a\u8f68/\u8dcc\u7834\u4e0b\u8f68 - RSI\u8d85\u4e70\u8d85\u5356 - KDJ\u91d1\u53c9/\u6b7b\u53c9",
+      "file_type": "rationale",
+      "source_file": "strategies/structured-dynamic-factors-20260327/strategies/tech_timing_signal.py",
+      "source_location": "L1",
+      "id": "strategies_tech_timing_signal_rationale_1",
+      "community": 136,
+      "norm_label": "\u6280\u672f\u62e9\u65f6\u4fe1\u53f7\u7cfb\u7edf \u652f\u6301\u591a\u79cd\u6280\u672f\u62e9\u65f6\u4fe1\u53f7: - \u5747\u7ebf\u591a\u5934\u6392\u5217 - macd\u91d1\u53c9/\u6b7b\u53c9 - \u7a81\u7834\u5e03\u6797\u5e26\u4e0a\u8f68/\u8dcc\u7834\u4e0b\u8f68 - rsi\u8d85\u4e70\u8d85\u5356 - kdj\u91d1\u53c9/\u6b7b\u53c9"
+    },
+    {
+      "label": "\u5747\u7ebf\u591a\u5934\u6392\u5217         \u77ed\u671f\u5747\u7ebf\u4e0a\u7a7f\u4e2d\u671f\uff0c\u4e2d\u671f\u5747\u7ebf\u4e0a\u7a7f\u957f\u671f \u2192 \u591a\u5934\u4fe1\u53f7         \u8fd4\u56de: bool Series\uff0cTrue=\u591a\u5934",
+      "file_type": "rationale",
+      "source_file": "strategies/structured-dynamic-factors-20260327/strategies/tech_timing_signal.py",
+      "source_location": "L22",
+      "id": "strategies_tech_timing_signal_rationale_22",
+      "community": 98,
+      "norm_label": "\u5747\u7ebf\u591a\u5934\u6392\u5217         \u77ed\u671f\u5747\u7ebf\u4e0a\u7a7f\u4e2d\u671f,\u4e2d\u671f\u5747\u7ebf\u4e0a\u7a7f\u957f\u671f \u2192 \u591a\u5934\u4fe1\u53f7         \u8fd4\u56de: bool series,true=\u591a\u5934"
+    },
+    {
+      "label": "MACD\u91d1\u53c9\u6b7b\u53c9\u4fe1\u53f7         \u8fd4\u56de: (golden_cross, death_cross)",
+      "file_type": "rationale",
+      "source_file": "strategies/structured-dynamic-factors-20260327/strategies/tech_timing_signal.py",
+      "source_location": "L61",
+      "id": "strategies_tech_timing_signal_rationale_61",
+      "community": 98,
+      "norm_label": "macd\u91d1\u53c9\u6b7b\u53c9\u4fe1\u53f7         \u8fd4\u56de: (golden_cross, death_cross)"
+    },
+    {
+      "label": "\u5e03\u6797\u5e26\u4fe1\u53f7         \u8fd4\u56de: (break_upper, break_lower)         \u7a81\u7834\u4e0a\u8f68 \u2192 \u770b\u591a\uff0c\u8dcc\u7834\u4e0b\u8f68 \u2192 \u770b\u7a7a",
+      "file_type": "rationale",
+      "source_file": "strategies/structured-dynamic-factors-20260327/strategies/tech_timing_signal.py",
+      "source_location": "L91",
+      "id": "strategies_tech_timing_signal_rationale_91",
+      "community": 98,
+      "norm_label": "\u5e03\u6797\u5e26\u4fe1\u53f7         \u8fd4\u56de: (break_upper, break_lower)         \u7a81\u7834\u4e0a\u8f68 \u2192 \u770b\u591a,\u8dcc\u7834\u4e0b\u8f68 \u2192 \u770b\u7a7a"
+    },
+    {
+      "label": "RSI\u4fe1\u53f7         \u8fd4\u56de: (oversold_buy, overbought_sell)         RSI\u8d85\u5356( < 30)\u4e70\u5165\uff0c\u8d85\u4e70( > 7",
+      "file_type": "rationale",
+      "source_file": "strategies/structured-dynamic-factors-20260327/strategies/tech_timing_signal.py",
+      "source_location": "L119",
+      "id": "strategies_tech_timing_signal_rationale_119",
+      "community": 98,
+      "norm_label": "rsi\u4fe1\u53f7         \u8fd4\u56de: (oversold_buy, overbought_sell)         rsi\u8d85\u5356( < 30)\u4e70\u5165,\u8d85\u4e70( > 7"
+    },
+    {
+      "label": "KDJ\u91d1\u53c9\u6b7b\u53c9         \u8fd4\u56de: (golden_cross, death_cross)",
+      "file_type": "rationale",
+      "source_file": "strategies/structured-dynamic-factors-20260327/strategies/tech_timing_signal.py",
+      "source_location": "L150",
+      "id": "strategies_tech_timing_signal_rationale_150",
+      "community": 98,
+      "norm_label": "kdj\u91d1\u53c9\u6b7b\u53c9         \u8fd4\u56de: (golden_cross, death_cross)"
+    },
+    {
+      "label": "\u7ec4\u5408\u591a\u4e2a\u6280\u672f\u4fe1\u53f7\uff0c\u591a\u5934\u4fe1\u53f7\u8d8a\u591a\uff0c\u5f97\u5206\u8d8a\u9ad8         \u6700\u7ec8\u8fd4\u56de\u662f\u5426\u770b\u591a",
+      "file_type": "rationale",
+      "source_file": "strategies/structured-dynamic-factors-20260327/strategies/tech_timing_signal.py",
+      "source_location": "L181",
+      "id": "strategies_tech_timing_signal_rationale_181",
+      "community": 98,
+      "norm_label": "\u7ec4\u5408\u591a\u4e2a\u6280\u672f\u4fe1\u53f7,\u591a\u5934\u4fe1\u53f7\u8d8a\u591a,\u5f97\u5206\u8d8a\u9ad8         \u6700\u7ec8\u8fd4\u56de\u662f\u5426\u770b\u591a"
+    },
+    {
+      "label": "\u6839\u636e\u6280\u672f\u62e9\u65f6\u8fc7\u6ee4\u5019\u9009\u80a1\u7968         \u53ea\u4fdd\u7559\u591a\u5934\u4fe1\u53f7\u5f97\u5206\u8d85\u8fc7\u9608\u503c\u7684",
+      "file_type": "rationale",
+      "source_file": "strategies/structured-dynamic-factors-20260327/strategies/tech_timing_signal.py",
+      "source_location": "L206",
+      "id": "strategies_tech_timing_signal_rationale_206",
+      "community": 98,
+      "norm_label": "\u6839\u636e\u6280\u672f\u62e9\u65f6\u8fc7\u6ee4\u5019\u9009\u80a1\u7968         \u53ea\u4fdd\u7559\u591a\u5934\u4fe1\u53f7\u5f97\u5206\u8d85\u8fc7\u9608\u503c\u7684"
+    },
+    {
+      "label": "__init__.py",
+      "file_type": "code",
+      "source_file": "strategies/structured-dynamic-factors-20260327/strategies/__init__.py",
+      "source_location": "L1",
+      "id": "strategies_structured_dynamic_factors_20260327_strategies_init_py",
+      "community": 136,
+      "norm_label": "__init__.py"
+    },
+    {
+      "label": "market_regime_weight.py",
+      "file_type": "code",
+      "source_file": "strategies/structured-dynamic-factors-20260327/strategies/market_regime_weight.py",
+      "source_location": "L1",
+      "id": "strategies_structured_dynamic_factors_20260327_strategies_market_regime_weight_py",
+      "community": 136,
+      "norm_label": "market_regime_weight.py"
+    },
+    {
+      "label": "MarketRegimeWeightAllocator",
+      "file_type": "code",
+      "source_file": "strategies/structured-dynamic-factors-20260327/strategies/market_regime_weight.py",
+      "source_location": "L13",
+      "id": "strategies_market_regime_weight_marketregimeweightallocator",
+      "community": 136,
+      "norm_label": "marketregimeweightallocator"
+    },
+    {
+      "label": ".__init__()",
+      "file_type": "code",
+      "source_file": "strategies/structured-dynamic-factors-20260327/strategies/market_regime_weight.py",
+      "source_location": "L47",
+      "id": "strategies_market_regime_weight_marketregimeweightallocator_init",
+      "community": 136,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": ".classify_market_regime()",
+      "file_type": "code",
+      "source_file": "strategies/structured-dynamic-factors-20260327/strategies/market_regime_weight.py",
+      "source_location": "L53",
+      "id": "strategies_market_regime_weight_marketregimeweightallocator_classify_market_regime",
+      "community": 136,
+      "norm_label": ".classify_market_regime()"
+    },
+    {
+      "label": ".get_weights()",
+      "file_type": "code",
+      "source_file": "strategies/structured-dynamic-factors-20260327/strategies/market_regime_weight.py",
+      "source_location": "L88",
+      "id": "strategies_market_regime_weight_marketregimeweightallocator_get_weights",
+      "community": 136,
+      "norm_label": ".get_weights()"
+    },
+    {
+      "label": ".update_custom_weights()",
+      "file_type": "code",
+      "source_file": "strategies/structured-dynamic-factors-20260327/strategies/market_regime_weight.py",
+      "source_location": "L97",
+      "id": "strategies_market_regime_weight_marketregimeweightallocator_update_custom_weights",
+      "community": 136,
+      "norm_label": ".update_custom_weights()"
+    },
+    {
+      "label": ".expand_to_factor_names()",
+      "file_type": "code",
+      "source_file": "strategies/structured-dynamic-factors-20260327/strategies/market_regime_weight.py",
+      "source_location": "L111",
+      "id": "strategies_market_regime_weight_marketregimeweightallocator_expand_to_factor_names",
+      "community": 136,
+      "norm_label": ".expand_to_factor_names()"
+    },
+    {
+      "label": "\u5e02\u573a\u72b6\u6001\u52a8\u6001\u6743\u91cd\u5206\u914d \u6839\u636e\u5e02\u573a\u72b6\u6001\uff08\u725b\u5e02/\u718a\u5e02/\u9707\u8361\u5e02\uff09\u8c03\u6574\u56e0\u5b50\u6743\u91cd - \u725b\u5e02\uff1a\u63d0\u9ad8\u8d8b\u52bf\u3001\u677f\u5757\u5f3a\u5ea6\u6743\u91cd - \u718a\u5e02\uff1a\u63d0\u9ad8\u4ef7\u503c\u3001\u8d28\u91cf\u6743\u91cd - \u9707\u8361\u5e02\uff1a\u5747\u8861\u914d\u7f6e",
+      "file_type": "rationale",
+      "source_file": "strategies/structured-dynamic-factors-20260327/strategies/market_regime_weight.py",
+      "source_location": "L1",
+      "id": "strategies_market_regime_weight_rationale_1",
+      "community": 136,
+      "norm_label": "\u5e02\u573a\u72b6\u6001\u52a8\u6001\u6743\u91cd\u5206\u914d \u6839\u636e\u5e02\u573a\u72b6\u6001(\u725b\u5e02/\u718a\u5e02/\u9707\u8361\u5e02)\u8c03\u6574\u56e0\u5b50\u6743\u91cd - \u725b\u5e02:\u63d0\u9ad8\u8d8b\u52bf\u3001\u677f\u5757\u5f3a\u5ea6\u6743\u91cd - \u718a\u5e02:\u63d0\u9ad8\u4ef7\u503c\u3001\u8d28\u91cf\u6743\u91cd - \u9707\u8361\u5e02:\u5747\u8861\u914d\u7f6e"
+    },
+    {
+      "label": "\u5e02\u573a\u72b6\u6001\u6743\u91cd\u5206\u914d\u5668     \u6839\u636e\u6ce2\u52a8\u7387\u548c\u8d8b\u52bf\u5224\u65ad\u5e02\u573a\u72b6\u6001\uff0c\u81ea\u52a8\u8c03\u6574\u56e0\u5b50\u6743\u91cd",
+      "file_type": "rationale",
+      "source_file": "strategies/structured-dynamic-factors-20260327/strategies/market_regime_weight.py",
+      "source_location": "L14",
+      "id": "strategies_market_regime_weight_rationale_14",
+      "community": 136,
+      "norm_label": "\u5e02\u573a\u72b6\u6001\u6743\u91cd\u5206\u914d\u5668     \u6839\u636e\u6ce2\u52a8\u7387\u548c\u8d8b\u52bf\u5224\u65ad\u5e02\u573a\u72b6\u6001,\u81ea\u52a8\u8c03\u6574\u56e0\u5b50\u6743\u91cd"
+    },
+    {
+      "label": "\u5224\u65ad\u5e02\u573a\u72b6\u6001         \u6839\u636e: \u6700\u8fd1N\u65e5\u6da8\u8dcc\u5e45 + \u6ce2\u52a8\u7387         \u8fd4\u56de: 'bull' / 'bear' / 'range_bound'",
+      "file_type": "rationale",
+      "source_file": "strategies/structured-dynamic-factors-20260327/strategies/market_regime_weight.py",
+      "source_location": "L58",
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+      "norm_label": "sector_strength_engine.py"
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+      "label": "SectorStrengthEngine",
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+      "id": "data_sector_strength_engine_sectorstrengthengine",
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+      "id": "data_sector_strength_engine_sectorstrengthengine_init",
+      "community": 59,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": ".calculate_tech_score()",
+      "file_type": "code",
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+      "source_location": "L34",
+      "id": "data_sector_strength_engine_sectorstrengthengine_calculate_tech_score",
+      "community": 59,
+      "norm_label": ".calculate_tech_score()"
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+      "label": ".calculate_fund_score()",
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+      "community": 59,
+      "norm_label": ".calculate_basic_score()"
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+      "label": ".calculate_sentiment_score()",
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+      "source_location": "L130",
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+      "community": 59,
+      "norm_label": ".calculate_sentiment_score()"
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+    {
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+      "source_location": "L1",
+      "id": "strategies_factors_dynamic_weight_timing_20260327_structural_market_risk_py",
+      "community": 122,
+      "norm_label": "structural_market_risk.py"
+    },
+    {
+      "label": "SectorInfo",
+      "file_type": "code",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/structural_market_risk.py",
+      "source_location": "L18",
+      "id": "factors_dynamic_weight_timing_20260327_structural_market_risk_sectorinfo",
+      "community": 122,
+      "norm_label": "sectorinfo"
+    },
+    {
+      "label": "StructuredMarketTiming",
+      "file_type": "code",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/structural_market_risk.py",
+      "source_location": "L28",
+      "id": "factors_dynamic_weight_timing_20260327_structural_market_risk_structuredmarkettiming",
+      "community": 122,
+      "norm_label": "structuredmarkettiming"
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+      "source_location": "L41",
+      "id": "factors_dynamic_weight_timing_20260327_structural_market_risk_structuredmarkettiming_timing_sector",
+      "community": 122,
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+    {
+      "label": "SectorConcentrationRisk",
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+      "id": "factors_dynamic_weight_timing_20260327_structural_market_risk_sectorconcentrationrisk",
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+      "community": 122,
+      "norm_label": ".check_concentration()"
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+      "label": "HotSectorNewsRiskAdjust",
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+      "id": "factors_dynamic_weight_timing_20260327_structural_market_risk_rationale_1",
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+      "norm_label": "\u7ed3\u6784\u5316\u884c\u60c5\u62e9\u65f6\u98ce\u63a7\u6a21\u5757 \u4e13\u95e8\u5904\u7406a\u80a1\u7ed3\u6784\u5316\u884c\u60c5\u4e0b\u7684\u677f\u5757\u96c6\u4e2d\u5ea6\u98ce\u9669\u548c\u62e9\u65f6\u4fe1\u53f7  \u529f\u80fd: 1. \u62e9\u65f6:\u5355\u677f\u5757\u8fde\u7eed\u5927\u6da8\u63d0\u9192\u98ce\u9669,\u8fde\u7eed\u5927\u8dcc\u63d0\u793a\u4f4e\u5438 2. \u98ce\u63a7:\u63a7\u5236\u677f\u5757"
+    },
+    {
+      "label": "\u677f\u5757\u62e9\u65f6         \u8fd4\u56de\uff1a(\u4fe1\u53f7\u7c7b\u578b, \u5efa\u8bae, \u98ce\u9669\u589e\u91cf\u8bc4\u5206)         \u4fe1\u53f7\u7c7b\u578b: bull/bear/neutral",
+      "file_type": "rationale",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/structural_market_risk.py",
+      "source_location": "L42",
+      "id": "factors_dynamic_weight_timing_20260327_structural_market_risk_rationale_42",
+      "community": 122,
+      "norm_label": "\u677f\u5757\u62e9\u65f6         \u8fd4\u56de:(\u4fe1\u53f7\u7c7b\u578b, \u5efa\u8bae, \u98ce\u9669\u589e\u91cf\u8bc4\u5206)         \u4fe1\u53f7\u7c7b\u578b: bull/bear/neutral"
+    },
+    {
+      "label": "\u70ed\u70b9\u677f\u5757\u6d88\u606f\u98ce\u9669\u8c03\u6574\uff0c\u70ed\u70b9\u66f4\u5bb9\u6613\u5229\u597d\u51fa\u5c3d\uff0c\u7075\u654f\u5ea6\u63d0\u9ad8",
+      "file_type": "rationale",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/structural_market_risk.py",
+      "source_location": "L126",
+      "id": "factors_dynamic_weight_timing_20260327_structural_market_risk_rationale_126",
+      "community": 122,
+      "norm_label": "\u70ed\u70b9\u677f\u5757\u6d88\u606f\u98ce\u9669\u8c03\u6574,\u70ed\u70b9\u66f4\u5bb9\u6613\u5229\u597d\u51fa\u5c3d,\u7075\u654f\u5ea6\u63d0\u9ad8"
+    },
+    {
+      "label": "risk_control.py",
+      "file_type": "code",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/risk_control.py",
+      "source_location": "L1",
+      "id": "strategies_factors_dynamic_weight_timing_20260327_risk_control_py",
+      "community": 45,
+      "norm_label": "risk_control.py"
+    },
+    {
+      "label": "StockInfo",
+      "file_type": "code",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/risk_control.py",
+      "source_location": "L17",
+      "id": "factors_dynamic_weight_timing_20260327_risk_control_stockinfo",
+      "community": 45,
+      "norm_label": "stockinfo"
+    },
+    {
+      "label": "PortfolioInfo",
+      "file_type": "code",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/risk_control.py",
+      "source_location": "L30",
+      "id": "factors_dynamic_weight_timing_20260327_risk_control_portfolioinfo",
+      "community": 45,
+      "norm_label": "portfolioinfo"
+    },
+    {
+      "label": "SingleStockRiskControl",
+      "file_type": "code",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/risk_control.py",
+      "source_location": "L37",
+      "id": "factors_dynamic_weight_timing_20260327_risk_control_singlestockriskcontrol",
+      "community": 45,
+      "norm_label": "singlestockriskcontrol"
+    },
+    {
+      "label": ".__init__()",
+      "file_type": "code",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/risk_control.py",
+      "source_location": "L40",
+      "id": "factors_dynamic_weight_timing_20260327_risk_control_singlestockriskcontrol_init",
+      "community": 45,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": ".check_stop_loss()",
+      "file_type": "code",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/risk_control.py",
+      "source_location": "L47",
+      "id": "factors_dynamic_weight_timing_20260327_risk_control_singlestockriskcontrol_check_stop_loss",
+      "community": 45,
+      "norm_label": ".check_stop_loss()"
+    },
+    {
+      "label": ".get_drawdown()",
+      "file_type": "code",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/risk_control.py",
+      "source_location": "L59",
+      "id": "factors_dynamic_weight_timing_20260327_risk_control_singlestockriskcontrol_get_drawdown",
+      "community": 45,
+      "norm_label": ".get_drawdown()"
+    },
+    {
+      "label": "PortfolioDrawdownRiskControl",
+      "file_type": "code",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/risk_control.py",
+      "source_location": "L66",
+      "id": "factors_dynamic_weight_timing_20260327_risk_control_portfoliodrawdownriskcontrol",
+      "community": 45,
+      "norm_label": "portfoliodrawdownriskcontrol"
+    },
+    {
+      "label": ".__init__()",
+      "file_type": "code",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/risk_control.py",
+      "source_location": "L74",
+      "id": "factors_dynamic_weight_timing_20260327_risk_control_portfoliodrawdownriskcontrol_init",
+      "community": 45,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": ".calculate_total_drawdown()",
+      "file_type": "code",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/risk_control.py",
+      "source_location": "L87",
+      "id": "factors_dynamic_weight_timing_20260327_risk_control_portfoliodrawdownriskcontrol_calculate_total_drawdown",
+      "community": 45,
+      "norm_label": ".calculate_total_drawdown()"
+    },
+    {
+      "label": ".get_target_position_ratio()",
+      "file_type": "code",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/risk_control.py",
+      "source_location": "L93",
+      "id": "factors_dynamic_weight_timing_20260327_risk_control_portfoliodrawdownriskcontrol_get_target_position_ratio",
+      "community": 45,
+      "norm_label": ".get_target_position_ratio()"
+    },
+    {
+      "label": ".need_rebalance()",
+      "file_type": "code",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/risk_control.py",
+      "source_location": "L108",
+      "id": "factors_dynamic_weight_timing_20260327_risk_control_portfoliodrawdownriskcontrol_need_rebalance",
+      "community": 45,
+      "norm_label": ".need_rebalance()"
+    },
+    {
+      "label": "BlackSwanFilter",
+      "file_type": "code",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/risk_control.py",
+      "source_location": "L123",
+      "id": "factors_dynamic_weight_timing_20260327_risk_control_blackswanfilter",
+      "community": 45,
+      "norm_label": "blackswanfilter"
+    },
+    {
+      "label": ".__init__()",
+      "file_type": "code",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/risk_control.py",
+      "source_location": "L126",
+      "id": "factors_dynamic_weight_timing_20260327_risk_control_blackswanfilter_init",
+      "community": 45,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": ".filter_stock()",
+      "file_type": "code",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/risk_control.py",
+      "source_location": "L133",
+      "id": "factors_dynamic_weight_timing_20260327_risk_control_blackswanfilter_filter_stock",
+      "community": 45,
+      "norm_label": ".filter_stock()"
+    },
+    {
+      "label": ".filter_universe()",
+      "file_type": "code",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/risk_control.py",
+      "source_location": "L158",
+      "id": "factors_dynamic_weight_timing_20260327_risk_control_blackswanfilter_filter_universe",
+      "community": 45,
+      "norm_label": ".filter_universe()"
+    },
+    {
+      "label": "RiskController",
+      "file_type": "code",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/risk_control.py",
+      "source_location": "L168",
+      "id": "factors_dynamic_weight_timing_20260327_risk_control_riskcontroller",
+      "community": 45,
+      "norm_label": "riskcontroller"
+    },
+    {
+      "label": ".__init__()",
+      "file_type": "code",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/risk_control.py",
+      "source_location": "L171",
+      "id": "factors_dynamic_weight_timing_20260327_risk_control_riskcontroller_init",
+      "community": 45,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": ".pre_trade_check()",
+      "file_type": "code",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/risk_control.py",
+      "source_location": "L176",
+      "id": "factors_dynamic_weight_timing_20260327_risk_control_riskcontroller_pre_trade_check",
+      "community": 45,
+      "norm_label": ".pre_trade_check()"
+    },
+    {
+      "label": ".post_trade_check()",
+      "file_type": "code",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/risk_control.py",
+      "source_location": "L195",
+      "id": "factors_dynamic_weight_timing_20260327_risk_control_riskcontroller_post_trade_check",
+      "community": 45,
+      "norm_label": ".post_trade_check()"
+    },
+    {
+      "label": ".get_risk_report()",
+      "file_type": "code",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/risk_control.py",
+      "source_location": "L223",
+      "id": "factors_dynamic_weight_timing_20260327_risk_control_riskcontroller_get_risk_report",
+      "community": 45,
+      "norm_label": ".get_risk_report()"
+    },
+    {
+      "label": "\u98ce\u63a7\u6a21\u5757 - \u91cf\u5316\u7b56\u7565\u98ce\u63a7\u7cfb\u7edf \u529f\u80fd\uff1a 1. \u5355\u796815%\u6b62\u635f\u89c4\u5219 2. \u6574\u4f53\u56de\u64a4\u5206\u7ea7\u98ce\u63a7\uff0810%/20%/25% \u5206\u7ea7\u964d\u4ed3\uff09 3. \u9ed1\u5929\u9e45\u8fc7\u6ee4\uff08ST\u3001\u8dcc\u505c\u3001\u8d22\u52a1",
+      "file_type": "rationale",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/risk_control.py",
+      "source_location": "L1",
+      "id": "factors_dynamic_weight_timing_20260327_risk_control_rationale_1",
+      "community": 45,
+      "norm_label": "\u98ce\u63a7\u6a21\u5757 - \u91cf\u5316\u7b56\u7565\u98ce\u63a7\u7cfb\u7edf \u529f\u80fd: 1. \u5355\u796815%\u6b62\u635f\u89c4\u5219 2. \u6574\u4f53\u56de\u64a4\u5206\u7ea7\u98ce\u63a7(10%/20%/25% \u5206\u7ea7\u964d\u4ed3) 3. \u9ed1\u5929\u9e45\u8fc7\u6ee4(st\u3001\u8dcc\u505c\u3001\u8d22\u52a1"
+    },
+    {
+      "label": "\u521d\u59cb\u5316         :param stop_loss_pct: \u6b62\u635f\u6bd4\u4f8b\uff0c\u9ed8\u8ba415%",
+      "file_type": "rationale",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/risk_control.py",
+      "source_location": "L41",
+      "id": "factors_dynamic_weight_timing_20260327_risk_control_rationale_41",
+      "community": 45,
+      "norm_label": "\u521d\u59cb\u5316         :param stop_loss_pct: \u6b62\u635f\u6bd4\u4f8b,\u9ed8\u8ba415%"
+    },
+    {
+      "label": "\u68c0\u67e5\u662f\u5426\u89e6\u53d1\u6b62\u635f         :return: True = \u9700\u8981\u6b62\u635f\uff0cFalse = \u6301\u6709",
+      "file_type": "rationale",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/risk_control.py",
+      "source_location": "L48",
+      "id": "factors_dynamic_weight_timing_20260327_risk_control_rationale_48",
+      "community": 45,
+      "norm_label": "\u68c0\u67e5\u662f\u5426\u89e6\u53d1\u6b62\u635f         :return: true = \u9700\u8981\u6b62\u635f,false = \u6301\u6709"
+    },
+    {
+      "label": "\u6574\u4f53\u56de\u64a4\u5206\u7ea7\u98ce\u63a7     10%\u56de\u64a4 \u2192 \u964d\u4ed350%     20%\u56de\u64a4 \u2192 \u964d\u4ed375%     25%\u56de\u64a4 \u2192 \u6e05\u4ed3\u4f11\u606f",
+      "file_type": "rationale",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/risk_control.py",
+      "source_location": "L67",
+      "id": "factors_dynamic_weight_timing_20260327_risk_control_rationale_67",
+      "community": 45,
+      "norm_label": "\u6574\u4f53\u56de\u64a4\u5206\u7ea7\u98ce\u63a7     10%\u56de\u64a4 \u2192 \u964d\u4ed350%     20%\u56de\u64a4 \u2192 \u964d\u4ed375%     25%\u56de\u64a4 \u2192 \u6e05\u4ed3\u4f11\u606f"
+    },
+    {
+      "label": "\u521d\u59cb\u5316\u5206\u7ea7\u98ce\u63a7         :param drawdown_levels: \u56de\u64a4\u9608\u503c         :param reduce_ratios: \u5bf9\u5e94\u964d\u4ed3\u6bd4",
+      "file_type": "rationale",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/risk_control.py",
+      "source_location": "L77",
+      "id": "factors_dynamic_weight_timing_20260327_risk_control_rationale_77",
+      "community": 45,
+      "norm_label": "\u521d\u59cb\u5316\u5206\u7ea7\u98ce\u63a7         :param drawdown_levels: \u56de\u64a4\u9608\u503c         :param reduce_ratios: \u5bf9\u5e94\u964d\u4ed3\u6bd4"
+    },
+    {
+      "label": "\u83b7\u53d6\u76ee\u6807\u4ed3\u4f4d\u6bd4\u4f8b         :return: \u76ee\u6807\u4ed3\u4f4d\u5360\u5f53\u524d\u603b\u8d44\u91d1\u7684\u6bd4\u4f8b",
+      "file_type": "rationale",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/risk_control.py",
+      "source_location": "L94",
+      "id": "factors_dynamic_weight_timing_20260327_risk_control_rationale_94",
+      "community": 45,
+      "norm_label": "\u83b7\u53d6\u76ee\u6807\u4ed3\u4f4d\u6bd4\u4f8b         :return: \u76ee\u6807\u4ed3\u4f4d\u5360\u5f53\u524d\u603b\u8d44\u91d1\u7684\u6bd4\u4f8b"
+    },
+    {
+      "label": "\u68c0\u67e5\u662f\u5426\u9700\u8981\u964d\u4ed3         :return: (\u662f\u5426\u9700\u8981\u8c03\u6574, \u76ee\u6807\u4ed3\u4f4d\u6bd4\u4f8b)",
+      "file_type": "rationale",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/risk_control.py",
+      "source_location": "L109",
+      "id": "factors_dynamic_weight_timing_20260327_risk_control_rationale_109",
+      "community": 45,
+      "norm_label": "\u68c0\u67e5\u662f\u5426\u9700\u8981\u964d\u4ed3         :return: (\u662f\u5426\u9700\u8981\u8c03\u6574, \u76ee\u6807\u4ed3\u4f4d\u6bd4\u4f8b)"
+    },
+    {
+      "label": "\u9ed1\u5929\u9e45\u8fc7\u6ee4\uff1a\u6392\u9664ST\u3001\u8dcc\u505c\u3001\u8d22\u52a1\u9020\u5047\u3001\u4f4e\u6d41\u52a8\u6027\u7968",
+      "file_type": "rationale",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/risk_control.py",
+      "source_location": "L124",
+      "id": "factors_dynamic_weight_timing_20260327_risk_control_rationale_124",
+      "community": 45,
+      "norm_label": "\u9ed1\u5929\u9e45\u8fc7\u6ee4:\u6392\u9664st\u3001\u8dcc\u505c\u3001\u8d22\u52a1\u9020\u5047\u3001\u4f4e\u6d41\u52a8\u6027\u7968"
+    },
+    {
+      "label": "\u521d\u59cb\u5316\u8fc7\u6ee4\u5668         :param min_daily_volume: \u6700\u5c0f\u65e5\u6210\u4ea4\u989d\uff08\u4ebf\uff09\uff0c\u4f4e\u4e8e\u6b64\u6392\u9664",
+      "file_type": "rationale",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/risk_control.py",
+      "source_location": "L127",
+      "id": "factors_dynamic_weight_timing_20260327_risk_control_rationale_127",
+      "community": 45,
+      "norm_label": "\u521d\u59cb\u5316\u8fc7\u6ee4\u5668         :param min_daily_volume: \u6700\u5c0f\u65e5\u6210\u4ea4\u989d(\u4ebf),\u4f4e\u4e8e\u6b64\u6392\u9664"
+    },
+    {
+      "label": "\u8fc7\u6ee4\u4e2a\u80a1         :return: (\u662f\u5426\u901a\u8fc7\u8fc7\u6ee4, \u4e0d\u901a\u8fc7\u539f\u56e0)         True = \u53ef\u4ee5\u4e70\u5165\uff0cFalse = \u6392\u9664",
+      "file_type": "rationale",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/risk_control.py",
+      "source_location": "L134",
+      "id": "factors_dynamic_weight_timing_20260327_risk_control_rationale_134",
+      "community": 45,
+      "norm_label": "\u8fc7\u6ee4\u4e2a\u80a1         :return: (\u662f\u5426\u901a\u8fc7\u8fc7\u6ee4, \u4e0d\u901a\u8fc7\u539f\u56e0)         true = \u53ef\u4ee5\u4e70\u5165,false = \u6392\u9664"
+    },
+    {
+      "label": "\u4ea4\u6613\u524d\u68c0\u67e5\uff1a\u5f00\u4ed3\u524d\u8c03\u7528         :return: (\u662f\u5426\u5141\u8bb8\u5f00\u4ed3, \u539f\u56e0)",
+      "file_type": "rationale",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/risk_control.py",
+      "source_location": "L177",
+      "id": "factors_dynamic_weight_timing_20260327_risk_control_rationale_177",
+      "community": 45,
+      "norm_label": "\u4ea4\u6613\u524d\u68c0\u67e5:\u5f00\u4ed3\u524d\u8c03\u7528         :return: (\u662f\u5426\u5141\u8bb8\u5f00\u4ed3, \u539f\u56e0)"
+    },
+    {
+      "label": "\u6536\u76d8\u540e\u68c0\u67e5\uff1a\u6b62\u635f\u68c0\u67e5 + \u964d\u4ed3\u68c0\u67e5         :return: \u98ce\u63a7\u7ed3\u679c\uff0c\u5305\u542b\u9700\u8981\u6b62\u635f\u7684\u7968\u548c\u9700\u8981\u964d\u4ed3\u7684\u4fe1\u606f",
+      "file_type": "rationale",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/risk_control.py",
+      "source_location": "L196",
+      "id": "factors_dynamic_weight_timing_20260327_risk_control_rationale_196",
+      "community": 45,
+      "norm_label": "\u6536\u76d8\u540e\u68c0\u67e5:\u6b62\u635f\u68c0\u67e5 + \u964d\u4ed3\u68c0\u67e5         :return: \u98ce\u63a7\u7ed3\u679c,\u5305\u542b\u9700\u8981\u6b62\u635f\u7684\u7968\u548c\u9700\u8981\u964d\u4ed3\u7684\u4fe1\u606f"
+    },
+    {
+      "label": "__init__.py",
+      "file_type": "code",
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+      "source_location": "L235",
+      "id": "factors_dynamic_weight_timing_20260327_news_risk_monitor_internationallinkagemonitor_analyze",
+      "community": 3,
+      "norm_label": ".analyze()"
+    },
+    {
+      "label": "StructuralMarketRisk",
+      "file_type": "code",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/news_risk_monitor.py",
+      "source_location": "L274",
+      "id": "factors_dynamic_weight_timing_20260327_news_risk_monitor_structuralmarketrisk",
+      "community": 3,
+      "norm_label": "structuralmarketrisk"
+    },
+    {
+      "label": ".__init__()",
+      "file_type": "code",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/news_risk_monitor.py",
+      "source_location": "L281",
+      "id": "factors_dynamic_weight_timing_20260327_news_risk_monitor_structuralmarketrisk_init",
+      "community": 3,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": ".analyze_sector_risk()",
+      "file_type": "code",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/news_risk_monitor.py",
+      "source_location": "L289",
+      "id": "factors_dynamic_weight_timing_20260327_news_risk_monitor_structuralmarketrisk_analyze_sector_risk",
+      "community": 3,
+      "norm_label": ".analyze_sector_risk()"
+    },
+    {
+      "label": ".adjust_news_risk_for_hot_sector()",
+      "file_type": "code",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/news_risk_monitor.py",
+      "source_location": "L316",
+      "id": "factors_dynamic_weight_timing_20260327_news_risk_monitor_structuralmarketrisk_adjust_news_risk_for_hot_sector",
+      "community": 3,
+      "norm_label": ".adjust_news_risk_for_hot_sector()"
+    },
+    {
+      "label": "StyleConcentrationRisk",
+      "file_type": "code",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/news_risk_monitor.py",
+      "source_location": "L324",
+      "id": "factors_dynamic_weight_timing_20260327_news_risk_monitor_styleconcentrationrisk",
+      "community": 3,
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+      "id": "factors_dynamic_weight_timing_20260327_news_risk_monitor_styleconcentrationrisk_init",
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+      "norm_label": ".__init__()"
+    },
+    {
+      "label": ".analyze_style_risk()",
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+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/news_risk_monitor.py",
+      "source_location": "L330",
+      "id": "factors_dynamic_weight_timing_20260327_news_risk_monitor_styleconcentrationrisk_analyze_style_risk",
+      "community": 3,
+      "norm_label": ".analyze_style_risk()"
+    },
+    {
+      "label": "NewsRiskMonitor",
+      "file_type": "code",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/news_risk_monitor.py",
+      "source_location": "L344",
+      "id": "factors_dynamic_weight_timing_20260327_news_risk_monitor_newsriskmonitor",
+      "community": 3,
+      "norm_label": "newsriskmonitor"
+    },
+    {
+      "label": ".__init__()",
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+      "source_location": "L347",
+      "id": "factors_dynamic_weight_timing_20260327_news_risk_monitor_newsriskmonitor_init",
+      "community": 3,
+      "norm_label": ".__init__()"
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+    {
+      "label": ".analyze_stock()",
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+      "source_location": "L355",
+      "id": "factors_dynamic_weight_timing_20260327_news_risk_monitor_newsriskmonitor_analyze_stock",
+      "community": 3,
+      "norm_label": ".analyze_stock()"
+    },
+    {
+      "label": ".analyze_stocks()",
+      "file_type": "code",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/news_risk_monitor.py",
+      "source_location": "L423",
+      "id": "factors_dynamic_weight_timing_20260327_news_risk_monitor_newsriskmonitor_analyze_stocks",
+      "community": 3,
+      "norm_label": ".analyze_stocks()"
+    },
+    {
+      "label": "._get_suggestion()",
+      "file_type": "code",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/news_risk_monitor.py",
+      "source_location": "L427",
+      "id": "factors_dynamic_weight_timing_20260327_news_risk_monitor_newsriskmonitor_get_suggestion",
+      "community": 3,
+      "norm_label": "._get_suggestion()"
+    },
+    {
+      "label": ".get_risk_report()",
+      "file_type": "code",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/news_risk_monitor.py",
+      "source_location": "L444",
+      "id": "factors_dynamic_weight_timing_20260327_news_risk_monitor_newsriskmonitor_get_risk_report",
+      "community": 3,
+      "norm_label": ".get_risk_report()"
+    },
+    {
+      "label": ".get_risk_score_for_risk_system()",
+      "file_type": "code",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/news_risk_monitor.py",
+      "source_location": "L484",
+      "id": "factors_dynamic_weight_timing_20260327_news_risk_monitor_newsriskmonitor_get_risk_score_for_risk_system",
+      "community": 3,
+      "norm_label": ".get_risk_score_for_risk_system()"
+    },
+    {
+      "label": "FiveDimensionRiskAssessment",
+      "file_type": "code",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/news_risk_monitor.py",
+      "source_location": "L493",
+      "id": "factors_dynamic_weight_timing_20260327_news_risk_monitor_fivedimensionriskassessment",
+      "community": 3,
+      "norm_label": "fivedimensionriskassessment"
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+      "id": "factors_dynamic_weight_timing_20260327_news_risk_monitor_fivedimensionriskassessment_init",
+      "community": 3,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": ".calculate_total_risk()",
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+      "source_location": "L502",
+      "id": "factors_dynamic_weight_timing_20260327_news_risk_monitor_fivedimensionriskassessment_calculate_total_risk",
+      "community": 3,
+      "norm_label": ".calculate_total_risk()"
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+    },
+    {
+      "label": "multi_factor_dynamic_strategy.py",
+      "file_type": "code",
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+      "source_location": "L1",
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+      "community": 67,
+      "norm_label": "multi_factor_dynamic_strategy.py"
+    },
+    {
+      "label": "MultiFactorDynamicStrategy",
+      "file_type": "code",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/strategies/multi_factor_dynamic_strategy.py",
+      "source_location": "L24",
+      "id": "strategies_multi_factor_dynamic_strategy_multifactordynamicstrategy",
+      "community": 67,
+      "norm_label": "multifactordynamicstrategy"
+    },
+    {
+      "label": ".__init__()",
+      "file_type": "code",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/strategies/multi_factor_dynamic_strategy.py",
+      "source_location": "L57",
+      "id": "strategies_multi_factor_dynamic_strategy_multifactordynamicstrategy_init",
+      "community": 67,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": "._init_factors()",
+      "file_type": "code",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/strategies/multi_factor_dynamic_strategy.py",
+      "source_location": "L112",
+      "id": "strategies_multi_factor_dynamic_strategy_multifactordynamicstrategy_init_factors",
+      "community": 67,
+      "norm_label": "._init_factors()"
+    },
+    {
+      "label": ".on_init()",
+      "file_type": "code",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/strategies/multi_factor_dynamic_strategy.py",
+      "source_location": "L135",
+      "id": "strategies_multi_factor_dynamic_strategy_multifactordynamicstrategy_on_init",
+      "community": 67,
+      "norm_label": ".on_init()"
+    },
+    {
+      "label": ".on_start()",
+      "file_type": "code",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/strategies/multi_factor_dynamic_strategy.py",
+      "source_location": "L140",
+      "id": "strategies_multi_factor_dynamic_strategy_multifactordynamicstrategy_on_start",
+      "community": 67,
+      "norm_label": ".on_start()"
+    },
+    {
+      "label": ".on_stop()",
+      "file_type": "code",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/strategies/multi_factor_dynamic_strategy.py",
+      "source_location": "L144",
+      "id": "strategies_multi_factor_dynamic_strategy_multifactordynamicstrategy_on_stop",
+      "community": 67,
+      "norm_label": ".on_stop()"
+    },
+    {
+      "label": ".on_bar()",
+      "file_type": "code",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/strategies/multi_factor_dynamic_strategy.py",
+      "source_location": "L148",
+      "id": "strategies_multi_factor_dynamic_strategy_multifactordynamicstrategy_on_bar",
+      "community": 67,
+      "norm_label": ".on_bar()"
+    },
+    {
+      "label": "._need_rebalance()",
+      "file_type": "code",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/strategies/multi_factor_dynamic_strategy.py",
+      "source_location": "L165",
+      "id": "strategies_multi_factor_dynamic_strategy_multifactordynamicstrategy_need_rebalance",
+      "community": 67,
+      "norm_label": "._need_rebalance()"
+    },
+    {
+      "label": ".calculate_factors()",
+      "file_type": "code",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/strategies/multi_factor_dynamic_strategy.py",
+      "source_location": "L183",
+      "id": "strategies_multi_factor_dynamic_strategy_multifactordynamicstrategy_calculate_factors",
+      "community": 67,
+      "norm_label": ".calculate_factors()"
+    },
+    {
+      "label": ".select_stocks()",
+      "file_type": "code",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/strategies/multi_factor_dynamic_strategy.py",
+      "source_location": "L199",
+      "id": "strategies_multi_factor_dynamic_strategy_multifactordynamicstrategy_select_stocks",
+      "community": 67,
+      "norm_label": ".select_stocks()"
+    },
+    {
+      "label": ".calculate_weights_for_selected()",
+      "file_type": "code",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/strategies/multi_factor_dynamic_strategy.py",
+      "source_location": "L221",
+      "id": "strategies_multi_factor_dynamic_strategy_multifactordynamicstrategy_calculate_weights_for_selected",
+      "community": 67,
+      "norm_label": ".calculate_weights_for_selected()"
+    },
+    {
+      "label": ".update_dynamic_weights()",
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+      "source_location": "L271",
+      "id": "strategies_multi_factor_dynamic_strategy_multifactordynamicstrategy_update_dynamic_weights",
+      "community": 67,
+      "norm_label": ".update_dynamic_weights()"
+    },
+    {
+      "label": ".update_market_timing()",
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+      "source_location": "L294",
+      "id": "strategies_multi_factor_dynamic_strategy_multifactordynamicstrategy_update_market_timing",
+      "community": 67,
+      "norm_label": ".update_market_timing()"
+    },
+    {
+      "label": ".rebalance()",
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+      "source_location": "L308",
+      "id": "strategies_multi_factor_dynamic_strategy_multifactordynamicstrategy_rebalance",
+      "community": 67,
+      "norm_label": ".rebalance()"
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+      "label": ".get_current_market_data()",
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+      "community": 67,
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+      "community": 67,
+      "norm_label": ".calculate_forward_returns()"
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+      "source_location": "L366",
+      "id": "strategies_multi_factor_dynamic_strategy_multifactordynamicstrategy_rebalance_portfolio",
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+    },
+    {
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+      "file_type": "code",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/strategies/__init__.py",
+      "source_location": "L1",
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+      "community": 67,
+      "norm_label": "__init__.py"
+    },
+    {
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+      "file_type": "code",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/factors/sector_strength_factor.py",
+      "source_location": "L1",
+      "id": "strategies_factors_dynamic_weight_timing_20260327_factors_sector_strength_factor_py",
+      "community": 0,
+      "norm_label": "sector_strength_factor.py"
+    },
+    {
+      "label": "SectorStrengthFactor",
+      "file_type": "code",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/factors/sector_strength_factor.py",
+      "source_location": "L12",
+      "id": "factors_sector_strength_factor_sectorstrengthfactor",
+      "community": 0,
+      "norm_label": "sectorstrengthfactor"
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+      "file_type": "code",
+      "source_file": "",
+      "source_location": "",
+      "id": "basefactor",
+      "community": 0,
+      "norm_label": "basefactor"
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+    {
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+      "file_type": "code",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/factors/sector_strength_factor.py",
+      "source_location": "L18",
+      "id": "factors_sector_strength_factor_sectorstrengthfactor_init",
+      "community": 0,
+      "norm_label": ".__init__()"
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+    {
+      "label": ".calculate()",
+      "file_type": "code",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/factors/sector_strength_factor.py",
+      "source_location": "L27",
+      "id": "factors_sector_strength_factor_sectorstrengthfactor_calculate",
+      "community": 0,
+      "norm_label": ".calculate()"
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+    {
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+      "source_location": "L19",
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+      "file_type": "code",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/factors/pe_factor.py",
+      "source_location": "L1",
+      "id": "strategies_factors_dynamic_weight_timing_20260327_factors_pe_factor_py",
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+      "file_type": "code",
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+      "id": "factors_pe_factor_pefactor",
+      "community": 0,
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+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/factors/pe_factor.py",
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+      "community": 208,
+      "norm_label": "\u66f4\u65b0\u4e00\u671fic\u6570\u636e         \u53c2\u6570:             factor_scores: \u5f53\u671f\u56e0\u5b50\u5f97\u5206(\u6a2a\u622a\u9762)             forward_"
+    },
+    {
+      "label": "\u6839\u636e\u5386\u53f2IC\u8ba1\u7b97\u65b0\u6743\u91cd         IC\u8d8a\u9ad8\uff0c\u6743\u91cd\u8d8a\u5927",
+      "file_type": "rationale",
+      "source_file": "strategies/factors-dynamic-weight-timing-20260327/utils/dynamic_weight.py",
+      "source_location": "L72",
+      "id": "utils_dynamic_weight_rationale_72",
+      "community": 208,
+      "norm_label": "\u6839\u636e\u5386\u53f2ic\u8ba1\u7b97\u65b0\u6743\u91cd         ic\u8d8a\u9ad8,\u6743\u91cd\u8d8a\u5927"
+    },
+    {
+      "label": "catalog.py",
+      "file_type": "code",
+      "source_file": "data_platform/catalog.py",
+      "source_location": "L1",
+      "id": "data_platform_catalog_py",
+      "community": 86,
+      "norm_label": "catalog.py"
+    },
+    {
+      "label": "DataCatalog",
+      "file_type": "code",
+      "source_file": "data_platform/catalog.py",
+      "source_location": "L27",
+      "id": "data_platform_catalog_datacatalog",
+      "community": 86,
+      "norm_label": "datacatalog"
+    },
+    {
+      "label": ".__init__()",
+      "file_type": "code",
+      "source_file": "data_platform/catalog.py",
+      "source_location": "L39",
+      "id": "data_platform_catalog_datacatalog_init",
+      "community": 123,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": ".get_daily()",
+      "file_type": "code",
+      "source_file": "data_platform/catalog.py",
+      "source_location": "L46",
+      "id": "data_platform_catalog_datacatalog_get_daily",
+      "community": 382,
+      "norm_label": ".get_daily()"
+    },
+    {
+      "label": ".get_daily_batch()",
+      "file_type": "code",
+      "source_file": "data_platform/catalog.py",
+      "source_location": "L100",
+      "id": "data_platform_catalog_datacatalog_get_daily_batch",
+      "community": 382,
+      "norm_label": ".get_daily_batch()"
+    },
+    {
+      "label": ".get_stock_list()",
+      "file_type": "code",
+      "source_file": "data_platform/catalog.py",
+      "source_location": "L129",
+      "id": "data_platform_catalog_datacatalog_get_stock_list",
+      "community": 86,
+      "norm_label": ".get_stock_list()"
+    },
+    {
+      "label": ".get_test_data()",
+      "file_type": "code",
+      "source_file": "data_platform/catalog.py",
+      "source_location": "L152",
+      "id": "data_platform_catalog_datacatalog_get_test_data",
+      "community": 514,
+      "norm_label": ".get_test_data()"
+    },
+    {
+      "label": ".list_available()",
+      "file_type": "code",
+      "source_file": "data_platform/catalog.py",
+      "source_location": "L176",
+      "id": "data_platform_catalog_datacatalog_list_available",
+      "community": 86,
+      "norm_label": ".list_available()"
+    },
+    {
+      "label": "._detect_years()",
+      "file_type": "code",
+      "source_file": "data_platform/catalog.py",
+      "source_location": "L203",
+      "id": "data_platform_catalog_datacatalog_detect_years",
+      "community": 382,
+      "norm_label": "._detect_years()"
+    },
+    {
+      "label": "DataCatalog - \u7edf\u4e00\u6570\u636e\u8bbf\u95ee\u63a5\u53e3  \u7b56\u7565\u5f00\u53d1\u8005\u53ea\u9700\u901a\u8fc7 DataCatalog \u83b7\u53d6\u6570\u636e\uff0c \u65e0\u9700\u5173\u5fc3\u5e95\u5c42\u6587\u4ef6\u8def\u5f84\u548c\u5b58\u50a8\u683c\u5f0f\u3002  \u6838\u5fc3API\uff1a - g",
+      "file_type": "rationale",
+      "source_file": "data_platform/catalog.py",
+      "source_location": "L1",
+      "id": "data_platform_catalog_rationale_1",
+      "community": 86,
+      "norm_label": "datacatalog - \u7edf\u4e00\u6570\u636e\u8bbf\u95ee\u63a5\u53e3  \u7b56\u7565\u5f00\u53d1\u8005\u53ea\u9700\u901a\u8fc7 datacatalog \u83b7\u53d6\u6570\u636e, \u65e0\u9700\u5173\u5fc3\u5e95\u5c42\u6587\u4ef6\u8def\u5f84\u548c\u5b58\u50a8\u683c\u5f0f\u3002  \u6838\u5fc3api: - g"
+    },
+    {
+      "label": "\u7edf\u4e00\u6570\u636e\u76ee\u5f55 \u2014\u2014 \u9879\u76ee\u552f\u4e00\u6570\u636e\u5165\u53e3      Usage:         from data_platform import DataCatalog",
+      "file_type": "rationale",
+      "source_file": "data_platform/catalog.py",
+      "source_location": "L28",
+      "id": "data_platform_catalog_rationale_28",
+      "community": 86,
+      "norm_label": "\u7edf\u4e00\u6570\u636e\u76ee\u5f55 \u2014\u2014 \u9879\u76ee\u552f\u4e00\u6570\u636e\u5165\u53e3      usage:         from data_platform import datacatalog"
+    },
+    {
+      "label": "\u83b7\u53d6\u5355\u53ea\u80a1\u7968\u65e5\u7ebf\u884c\u60c5\uff08\u4ece\u672c\u5730 Parquet \u8bfb\u53d6\uff09          Args:             code: 6\u4f4d\u80a1\u7968\u4ee3\u7801\uff0c\u5982 \"600519\"",
+      "file_type": "rationale",
+      "source_file": "data_platform/catalog.py",
+      "source_location": "L53",
+      "id": "data_platform_catalog_rationale_53",
+      "community": 382,
+      "norm_label": "\u83b7\u53d6\u5355\u53ea\u80a1\u7968\u65e5\u7ebf\u884c\u60c5(\u4ece\u672c\u5730 parquet \u8bfb\u53d6)          args:             code: 6\u4f4d\u80a1\u7968\u4ee3\u7801,\u5982 \"600519\""
+    },
+    {
+      "label": "\u6279\u91cf\u83b7\u53d6\u591a\u53ea\u80a1\u7968\u65e5\u7ebf\u884c\u60c5          Args:             codes: \u80a1\u7968\u4ee3\u7801\u5217\u8868\uff0c\u5982 [\"600519\", \"000001\"]",
+      "file_type": "rationale",
+      "source_file": "data_platform/catalog.py",
+      "source_location": "L106",
+      "id": "data_platform_catalog_rationale_106",
+      "community": 382,
+      "norm_label": "\u6279\u91cf\u83b7\u53d6\u591a\u53ea\u80a1\u7968\u65e5\u7ebf\u884c\u60c5          args:             codes: \u80a1\u7968\u4ee3\u7801\u5217\u8868,\u5982 [\"600519\", \"000001\"]"
+    },
+    {
+      "label": "\u83b7\u53d6\u80a1\u7968\u57fa\u7840\u4fe1\u606f\u6216\u6307\u6570\u6210\u5206\u80a1          Args:             index: \u6307\u6570\u4ee3\u7801\uff0c\u5982 \"hs300\"\uff1bNone \u8fd4\u56de\u5168\u90e8 A \u80a1\u57fa\u7840\u4fe1",
+      "file_type": "rationale",
+      "source_file": "data_platform/catalog.py",
+      "source_location": "L130",
+      "id": "data_platform_catalog_rationale_130",
+      "community": 86,
+      "norm_label": "\u83b7\u53d6\u80a1\u7968\u57fa\u7840\u4fe1\u606f\u6216\u6307\u6570\u6210\u5206\u80a1          args:             index: \u6307\u6570\u4ee3\u7801,\u5982 \"hs300\";none \u8fd4\u56de\u5168\u90e8 a \u80a1\u57fa\u7840\u4fe1"
+    },
+    {
+      "label": "\u83b7\u53d6\u6807\u51c6\u6d4b\u8bd5\u6570\u636e\u96c6          Args:             name: \u6570\u636e\u96c6\u540d\u79f0\uff0c\u5982 \"600519\" \u6216 \"\u8d35\u5dde\u8305\u53f0\"",
+      "file_type": "rationale",
+      "source_file": "data_platform/catalog.py",
+      "source_location": "L153",
+      "id": "data_platform_catalog_rationale_153",
+      "community": 514,
+      "norm_label": "\u83b7\u53d6\u6807\u51c6\u6d4b\u8bd5\u6570\u636e\u96c6          args:             name: \u6570\u636e\u96c6\u540d\u79f0,\u5982 \"600519\" \u6216 \"\u8d35\u5dde\u8305\u53f0\""
+    },
+    {
+      "label": "strategy_base.py",
+      "file_type": "code",
+      "source_file": "data_platform/strategy_base.py",
+      "source_location": "L1",
+      "id": "data_platform_strategy_base_py",
+      "community": 282,
+      "norm_label": "strategy_base.py"
+    },
+    {
+      "label": "BaseStrategy",
+      "file_type": "code",
+      "source_file": "data_platform/strategy_base.py",
+      "source_location": "L25",
+      "id": "data_platform_strategy_base_basestrategy",
+      "community": 282,
+      "norm_label": "basestrategy"
+    },
+    {
+      "label": "generate_signals()",
+      "file_type": "code",
+      "source_file": "data_platform/strategy_base.py",
+      "source_location": "L37",
+      "id": "data_platform_strategy_base_generate_signals",
+      "community": 282,
+      "norm_label": "generate_signals()"
+    },
+    {
+      "label": "name()",
+      "file_type": "code",
+      "source_file": "data_platform/strategy_base.py",
+      "source_location": "L50",
+      "id": "data_platform_strategy_base_name",
+      "community": 282,
+      "norm_label": "name()"
+    },
+    {
+      "label": "description()",
+      "file_type": "code",
+      "source_file": "data_platform/strategy_base.py",
+      "source_location": "L55",
+      "id": "data_platform_strategy_base_description",
+      "community": 282,
+      "norm_label": "description()"
+    },
+    {
+      "label": "BaseStrategy - \u7b56\u7565\u57fa\u7c7b  \u7b56\u7565\u5f00\u53d1\u8005\u53ea\u9700\u7ee7\u627f\u6b64\u7c7b\u5e76\u5b9e\u73b0 generate_signals() \u65b9\u6cd5\u3002 \u56de\u6d4b\u5f15\u64ce\u901a\u8fc7\u7edf\u4e00\u63a5\u53e3\u8c03\u7528\u7b56\u7565\u3002  Usag",
+      "file_type": "rationale",
+      "source_file": "data_platform/strategy_base.py",
+      "source_location": "L1",
+      "id": "data_platform_strategy_base_rationale_1",
+      "community": 282,
+      "norm_label": "basestrategy - \u7b56\u7565\u57fa\u7c7b  \u7b56\u7565\u5f00\u53d1\u8005\u53ea\u9700\u7ee7\u627f\u6b64\u7c7b\u5e76\u5b9e\u73b0 generate_signals() \u65b9\u6cd5\u3002 \u56de\u6d4b\u5f15\u64ce\u901a\u8fc7\u7edf\u4e00\u63a5\u53e3\u8c03\u7528\u7b56\u7565\u3002  usag"
+    },
+    {
+      "label": "\u7b56\u7565\u57fa\u7c7b \u2014\u2014 \u6240\u6709\u56de\u6d4b\u7b56\u7565\u5fc5\u987b\u7ee7\u627f\u6b64\u7c7b      \u5b50\u7c7b\u53ea\u9700\u5b9e\u73b0 generate_signals(data) -> data_with_signals",
+      "file_type": "rationale",
+      "source_file": "data_platform/strategy_base.py",
+      "source_location": "L26",
+      "id": "data_platform_strategy_base_rationale_26",
+      "community": 282,
+      "norm_label": "\u7b56\u7565\u57fa\u7c7b \u2014\u2014 \u6240\u6709\u56de\u6d4b\u7b56\u7565\u5fc5\u987b\u7ee7\u627f\u6b64\u7c7b      \u5b50\u7c7b\u53ea\u9700\u5b9e\u73b0 generate_signals(data) -> data_with_signals"
+    },
+    {
+      "label": "\u6839\u636e\u884c\u60c5\u6570\u636e\u751f\u6210\u4ea4\u6613\u4fe1\u53f7          Args:             data: \u65e5\u7ebf\u884c\u60c5 DataFrame\uff0c\u81f3\u5c11\u5305\u542b date, open, hi",
+      "file_type": "rationale",
+      "source_file": "data_platform/strategy_base.py",
+      "source_location": "L38",
+      "id": "data_platform_strategy_base_rationale_38",
+      "community": 526,
+      "norm_label": "\u6839\u636e\u884c\u60c5\u6570\u636e\u751f\u6210\u4ea4\u6613\u4fe1\u53f7          args:             data: \u65e5\u7ebf\u884c\u60c5 dataframe,\u81f3\u5c11\u5305\u542b date, open, hi"
+    },
+    {
+      "label": "backtest_report.py",
+      "file_type": "code",
+      "source_file": "data_platform/backtest_report.py",
+      "source_location": "L1",
+      "id": "data_platform_backtest_report_py",
+      "community": 308,
+      "norm_label": "backtest_report.py"
+    },
+    {
+      "label": "BacktestReport",
+      "file_type": "code",
+      "source_file": "data_platform/backtest_report.py",
+      "source_location": "L14",
+      "id": "data_platform_backtest_report_backtestreport",
+      "community": 308,
+      "norm_label": "backtestreport"
+    },
+    {
+      "label": ".__init__()",
+      "file_type": "code",
+      "source_file": "data_platform/backtest_report.py",
+      "source_location": "L17",
+      "id": "data_platform_backtest_report_backtestreport_init",
+      "community": 308,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": ".to_text()",
+      "file_type": "code",
+      "source_file": "data_platform/backtest_report.py",
+      "source_location": "L20",
+      "id": "data_platform_backtest_report_backtestreport_to_text",
+      "community": 308,
+      "norm_label": ".to_text()"
+    },
+    {
+      "label": ".to_dict()",
+      "file_type": "code",
+      "source_file": "data_platform/backtest_report.py",
+      "source_location": "L57",
+      "id": "data_platform_backtest_report_backtestreport_to_dict",
+      "community": 308,
+      "norm_label": ".to_dict()"
+    },
+    {
+      "label": ".to_json()",
+      "file_type": "code",
+      "source_file": "data_platform/backtest_report.py",
+      "source_location": "L75",
+      "id": "data_platform_backtest_report_backtestreport_to_json",
+      "community": 308,
+      "norm_label": ".to_json()"
+    },
+    {
+      "label": "BacktestReport - \u6807\u51c6\u5316\u56de\u6d4b\u62a5\u544a  \u5c06 BacktestResult \u683c\u5f0f\u5316\u8f93\u51fa\u4e3a\u6587\u672c/JSON\u3002",
+      "file_type": "rationale",
+      "source_file": "data_platform/backtest_report.py",
+      "source_location": "L1",
+      "id": "data_platform_backtest_report_rationale_1",
+      "community": 308,
+      "norm_label": "backtestreport - \u6807\u51c6\u5316\u56de\u6d4b\u62a5\u544a  \u5c06 backtestresult \u683c\u5f0f\u5316\u8f93\u51fa\u4e3a\u6587\u672c/json\u3002"
+    },
+    {
+      "label": "test_catalog.py",
+      "file_type": "code",
+      "source_file": "data_platform/test_catalog.py",
+      "source_location": "L1",
+      "id": "data_platform_test_catalog_py",
+      "community": 86,
+      "norm_label": "test_catalog.py"
+    },
+    {
+      "label": "DummyMAStrategy",
+      "file_type": "code",
+      "source_file": "data_platform/test_catalog.py",
+      "source_location": "L23",
+      "id": "data_platform_test_catalog_dummymastrategy",
+      "community": 86,
+      "norm_label": "dummymastrategy"
+    },
+    {
+      "label": "BaseStrategy",
+      "file_type": "code",
+      "source_file": "",
+      "source_location": "",
+      "id": "basestrategy",
+      "community": 86,
+      "norm_label": "basestrategy"
+    },
+    {
+      "label": ".generate_signals()",
+      "file_type": "code",
+      "source_file": "data_platform/test_catalog.py",
+      "source_location": "L26",
+      "id": "data_platform_test_catalog_dummymastrategy_generate_signals",
+      "community": 86,
+      "norm_label": ".generate_signals()"
+    },
+    {
+      "label": "test_config()",
+      "file_type": "code",
+      "source_file": "data_platform/test_catalog.py",
+      "source_location": "L40",
+      "id": "data_platform_test_catalog_test_config",
+      "community": 123,
+      "norm_label": "test_config()"
+    },
+    {
+      "label": "test_get_daily()",
+      "file_type": "code",
+      "source_file": "data_platform/test_catalog.py",
+      "source_location": "L47",
+      "id": "data_platform_test_catalog_test_get_daily",
+      "community": 86,
+      "norm_label": "test_get_daily()"
+    },
+    {
+      "label": "test_get_daily_batch()",
+      "file_type": "code",
+      "source_file": "data_platform/test_catalog.py",
+      "source_location": "L55",
+      "id": "data_platform_test_catalog_test_get_daily_batch",
+      "community": 86,
+      "norm_label": "test_get_daily_batch()"
+    },
+    {
+      "label": "test_get_stock_list()",
+      "file_type": "code",
+      "source_file": "data_platform/test_catalog.py",
+      "source_location": "L64",
+      "id": "data_platform_test_catalog_test_get_stock_list",
+      "community": 86,
+      "norm_label": "test_get_stock_list()"
+    },
+    {
+      "label": "test_get_test_data()",
+      "file_type": "code",
+      "source_file": "data_platform/test_catalog.py",
+      "source_location": "L73",
+      "id": "data_platform_test_catalog_test_get_test_data",
+      "community": 86,
+      "norm_label": "test_get_test_data()"
+    },
+    {
+      "label": "test_list_available()",
+      "file_type": "code",
+      "source_file": "data_platform/test_catalog.py",
+      "source_location": "L80",
+      "id": "data_platform_test_catalog_test_list_available",
+      "community": 86,
+      "norm_label": "test_list_available()"
+    },
+    {
+      "label": "test_backtest_runner()",
+      "file_type": "code",
+      "source_file": "data_platform/test_catalog.py",
+      "source_location": "L87",
+      "id": "data_platform_test_catalog_test_backtest_runner",
+      "community": 86,
+      "norm_label": "test_backtest_runner()"
+    },
+    {
+      "label": "test_backtest_batch()",
+      "file_type": "code",
+      "source_file": "data_platform/test_catalog.py",
+      "source_location": "L119",
+      "id": "data_platform_test_catalog_test_backtest_batch",
+      "community": 86,
+      "norm_label": "test_backtest_batch()"
+    },
+    {
+      "label": "\u6570\u636e\u5e73\u53f0\u5b8c\u6574\u6d4b\u8bd5 - \u9a8c\u8bc1 DataCatalog + BacktestRunner  \u8fd0\u884c\u65b9\u5f0f\uff1acd sanguo_quant_live && python3",
+      "file_type": "rationale",
+      "source_file": "data_platform/test_catalog.py",
+      "source_location": "L1",
+      "id": "data_platform_test_catalog_rationale_1",
+      "community": 86,
+      "norm_label": "\u6570\u636e\u5e73\u53f0\u5b8c\u6574\u6d4b\u8bd5 - \u9a8c\u8bc1 datacatalog + backtestrunner  \u8fd0\u884c\u65b9\u5f0f:cd sanguo_quant_live && python3"
+    },
+    {
+      "label": "\u6d4b\u8bd5\u5b8c\u6574\u56de\u6d4b\u6d41\u7a0b\uff1a\u83b7\u53d6\u6570\u636e \u2192 \u7b56\u7565 \u2192 \u6a21\u62df\u4ea4\u6613 \u2192 \u62a5\u544a",
+      "file_type": "rationale",
+      "source_file": "data_platform/test_catalog.py",
+      "source_location": "L88",
+      "id": "data_platform_test_catalog_rationale_88",
+      "community": 86,
+      "norm_label": "\u6d4b\u8bd5\u5b8c\u6574\u56de\u6d4b\u6d41\u7a0b:\u83b7\u53d6\u6570\u636e \u2192 \u7b56\u7565 \u2192 \u6a21\u62df\u4ea4\u6613 \u2192 \u62a5\u544a"
+    },
+    {
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+      "source_file": "data_platform/backtest_runner.py",
+      "source_location": "L68",
+      "id": "data_platform_backtest_runner_backtestresult_summary",
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+      "norm_label": ".summary()"
+    },
+    {
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+      "source_location": "L78",
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+      "id": "data_platform_backtest_runner_backtestrunner_run_batch",
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+      "id": "data_platform_backtest_runner_backtestrunner_simulate",
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+      "id": "data_platform_backtest_runner_backtestrunner_build_result",
+      "community": 137,
+      "norm_label": "._build_result()"
+    },
+    {
+      "label": "BacktestRunner - \u56de\u6d4b\u5f15\u64ce  \u80f6\u6c34\u5c42\uff1a\u53d6\u6570\u636e \u2192 \u751f\u6210\u4fe1\u53f7 \u2192 \u6a21\u62df\u4ea4\u6613 \u2192 \u51fa\u62a5\u544a  \u81ea\u5e26\u7b80\u6613\u56de\u6d4b\u5f15\u64ce\uff0c\u4e0d\u4f9d\u8d56 vnpy\uff0c\u964d\u4f4e\u4f7f\u7528\u95e8\u69db\u3002 \u4fdd\u7559",
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+      "source_file": "data_platform/backtest_runner.py",
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+      "file_type": "code",
+      "source_file": "guanyu-risk/research/factors-strategy-risk-control-20260327/risk_control.py",
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+      "community": 29,
+      "norm_label": "risk_control.py"
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+      "source_location": "L18",
+      "id": "factors_strategy_risk_control_20260327_risk_control_stockinfo",
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+      "norm_label": "stockinfo"
+    },
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+      "id": "factors_strategy_risk_control_20260327_risk_control_portfolioinfo",
+      "community": 41,
+      "norm_label": "portfolioinfo"
+    },
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+      "community": 81,
+      "norm_label": "singlestockriskcontrol"
+    },
+    {
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+      "file_type": "code",
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+      "id": "factors_strategy_risk_control_20260327_risk_control_singlestockriskcontrol_init",
+      "community": 81,
+      "norm_label": ".__init__()"
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+    {
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+      "id": "factors_strategy_risk_control_20260327_risk_control_singlestockriskcontrol_check_stop_loss",
+      "community": 81,
+      "norm_label": ".check_stop_loss()"
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+      "file_type": "code",
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+      "source_location": "L60",
+      "id": "factors_strategy_risk_control_20260327_risk_control_singlestockriskcontrol_get_drawdown",
+      "community": 81,
+      "norm_label": ".get_drawdown()"
+    },
+    {
+      "label": "PortfolioDrawdownRiskControl",
+      "file_type": "code",
+      "source_file": "guanyu-risk/research/factors-strategy-risk-control-20260327/risk_control.py",
+      "source_location": "L67",
+      "id": "factors_strategy_risk_control_20260327_risk_control_portfoliodrawdownriskcontrol",
+      "community": 81,
+      "norm_label": "portfoliodrawdownriskcontrol"
+    },
+    {
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+      "file_type": "code",
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+      "community": 81,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": ".calculate_total_drawdown()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/research/factors-strategy-risk-control-20260327/risk_control.py",
+      "source_location": "L88",
+      "id": "factors_strategy_risk_control_20260327_risk_control_portfoliodrawdownriskcontrol_calculate_total_drawdown",
+      "community": 81,
+      "norm_label": ".calculate_total_drawdown()"
+    },
+    {
+      "label": ".get_target_position_ratio()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/research/factors-strategy-risk-control-20260327/risk_control.py",
+      "source_location": "L94",
+      "id": "factors_strategy_risk_control_20260327_risk_control_portfoliodrawdownriskcontrol_get_target_position_ratio",
+      "community": 81,
+      "norm_label": ".get_target_position_ratio()"
+    },
+    {
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+      "file_type": "code",
+      "source_file": "guanyu-risk/research/factors-strategy-risk-control-20260327/risk_control.py",
+      "source_location": "L109",
+      "id": "factors_strategy_risk_control_20260327_risk_control_portfoliodrawdownriskcontrol_need_rebalance",
+      "community": 81,
+      "norm_label": ".need_rebalance()"
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+    {
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+      "file_type": "code",
+      "source_file": "guanyu-risk/research/factors-strategy-risk-control-20260327/risk_control.py",
+      "source_location": "L124",
+      "id": "factors_strategy_risk_control_20260327_risk_control_blackswanfilter",
+      "community": 310,
+      "norm_label": "blackswanfilter"
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+    {
+      "label": ".__init__()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/research/factors-strategy-risk-control-20260327/risk_control.py",
+      "source_location": "L127",
+      "id": "factors_strategy_risk_control_20260327_risk_control_blackswanfilter_init",
+      "community": 310,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": ".filter_stock()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/research/factors-strategy-risk-control-20260327/risk_control.py",
+      "source_location": "L134",
+      "id": "factors_strategy_risk_control_20260327_risk_control_blackswanfilter_filter_stock",
+      "community": 310,
+      "norm_label": ".filter_stock()"
+    },
+    {
+      "label": ".filter_universe()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/research/factors-strategy-risk-control-20260327/risk_control.py",
+      "source_location": "L159",
+      "id": "factors_strategy_risk_control_20260327_risk_control_blackswanfilter_filter_universe",
+      "community": 310,
+      "norm_label": ".filter_universe()"
+    },
+    {
+      "label": "RiskController",
+      "file_type": "code",
+      "source_file": "guanyu-risk/research/factors-strategy-risk-control-20260327/risk_control.py",
+      "source_location": "L169",
+      "id": "factors_strategy_risk_control_20260327_risk_control_riskcontroller",
+      "community": 81,
+      "norm_label": "riskcontroller"
+    },
+    {
+      "label": ".__init__()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/research/factors-strategy-risk-control-20260327/risk_control.py",
+      "source_location": "L172",
+      "id": "factors_strategy_risk_control_20260327_risk_control_riskcontroller_init",
+      "community": 81,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": ".pre_trade_check()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/research/factors-strategy-risk-control-20260327/risk_control.py",
+      "source_location": "L177",
+      "id": "factors_strategy_risk_control_20260327_risk_control_riskcontroller_pre_trade_check",
+      "community": 81,
+      "norm_label": ".pre_trade_check()"
+    },
+    {
+      "label": ".post_trade_check()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/research/factors-strategy-risk-control-20260327/risk_control.py",
+      "source_location": "L196",
+      "id": "factors_strategy_risk_control_20260327_risk_control_riskcontroller_post_trade_check",
+      "community": 81,
+      "norm_label": ".post_trade_check()"
+    },
+    {
+      "label": ".get_risk_report()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/research/factors-strategy-risk-control-20260327/risk_control.py",
+      "source_location": "L224",
+      "id": "factors_strategy_risk_control_20260327_risk_control_riskcontroller_get_risk_report",
+      "community": 81,
+      "norm_label": ".get_risk_report()"
+    },
+    {
+      "label": "\u98ce\u63a7\u6a21\u5757 - \u91cf\u5316\u7b56\u7565\u98ce\u63a7\u7cfb\u7edf \u529f\u80fd\uff1a 1. \u5355\u796815%\u6b62\u635f\u89c4\u5219 2. \u6574\u4f53\u56de\u64a4\u5206\u7ea7\u98ce\u63a7\uff0810%/20%/25% \u5206\u7ea7\u964d\u4ed3\uff09 3. \u9ed1\u5929\u9e45\u8fc7\u6ee4\uff08ST\u3001\u8dcc\u505c\u3001\u8d22\u52a1",
+      "file_type": "rationale",
+      "source_file": "guanyu-risk/research/factors-strategy-risk-control-20260327/risk_control.py",
+      "source_location": "L1",
+      "id": "factors_strategy_risk_control_20260327_risk_control_rationale_1",
+      "community": 29,
+      "norm_label": "\u98ce\u63a7\u6a21\u5757 - \u91cf\u5316\u7b56\u7565\u98ce\u63a7\u7cfb\u7edf \u529f\u80fd: 1. \u5355\u796815%\u6b62\u635f\u89c4\u5219 2. \u6574\u4f53\u56de\u64a4\u5206\u7ea7\u98ce\u63a7(10%/20%/25% \u5206\u7ea7\u964d\u4ed3) 3. \u9ed1\u5929\u9e45\u8fc7\u6ee4(st\u3001\u8dcc\u505c\u3001\u8d22\u52a1"
+    },
+    {
+      "label": "\u521d\u59cb\u5316         :param stop_loss_pct: \u6b62\u635f\u6bd4\u4f8b\uff0c\u9ed8\u8ba415%",
+      "file_type": "rationale",
+      "source_file": "guanyu-risk/research/factors-strategy-risk-control-20260327/risk_control.py",
+      "source_location": "L42",
+      "id": "factors_strategy_risk_control_20260327_risk_control_rationale_42",
+      "community": 81,
+      "norm_label": "\u521d\u59cb\u5316         :param stop_loss_pct: \u6b62\u635f\u6bd4\u4f8b,\u9ed8\u8ba415%"
+    },
+    {
+      "label": "\u68c0\u67e5\u662f\u5426\u89e6\u53d1\u6b62\u635f         :return: True = \u9700\u8981\u6b62\u635f\uff0cFalse = \u6301\u6709",
+      "file_type": "rationale",
+      "source_file": "guanyu-risk/research/factors-strategy-risk-control-20260327/risk_control.py",
+      "source_location": "L49",
+      "id": "factors_strategy_risk_control_20260327_risk_control_rationale_49",
+      "community": 81,
+      "norm_label": "\u68c0\u67e5\u662f\u5426\u89e6\u53d1\u6b62\u635f         :return: true = \u9700\u8981\u6b62\u635f,false = \u6301\u6709"
+    },
+    {
+      "label": "\u6574\u4f53\u56de\u64a4\u5206\u7ea7\u98ce\u63a7     10%\u56de\u64a4 \u2192 \u964d\u4ed350%     20%\u56de\u64a4 \u2192 \u964d\u4ed375%     25%\u56de\u64a4 \u2192 \u6e05\u4ed3\u4f11\u606f",
+      "file_type": "rationale",
+      "source_file": "guanyu-risk/research/factors-strategy-risk-control-20260327/risk_control.py",
+      "source_location": "L68",
+      "id": "factors_strategy_risk_control_20260327_risk_control_rationale_68",
+      "community": 81,
+      "norm_label": "\u6574\u4f53\u56de\u64a4\u5206\u7ea7\u98ce\u63a7     10%\u56de\u64a4 \u2192 \u964d\u4ed350%     20%\u56de\u64a4 \u2192 \u964d\u4ed375%     25%\u56de\u64a4 \u2192 \u6e05\u4ed3\u4f11\u606f"
+    },
+    {
+      "label": "\u521d\u59cb\u5316\u5206\u7ea7\u98ce\u63a7         :param drawdown_levels: \u56de\u64a4\u9608\u503c         :param reduce_ratios: \u5bf9\u5e94\u964d\u4ed3\u6bd4",
+      "file_type": "rationale",
+      "source_file": "guanyu-risk/research/factors-strategy-risk-control-20260327/risk_control.py",
+      "source_location": "L78",
+      "id": "factors_strategy_risk_control_20260327_risk_control_rationale_78",
+      "community": 81,
+      "norm_label": "\u521d\u59cb\u5316\u5206\u7ea7\u98ce\u63a7         :param drawdown_levels: \u56de\u64a4\u9608\u503c         :param reduce_ratios: \u5bf9\u5e94\u964d\u4ed3\u6bd4"
+    },
+    {
+      "label": "\u83b7\u53d6\u76ee\u6807\u4ed3\u4f4d\u6bd4\u4f8b         :return: \u76ee\u6807\u4ed3\u4f4d\u5360\u5f53\u524d\u603b\u8d44\u91d1\u7684\u6bd4\u4f8b",
+      "file_type": "rationale",
+      "source_file": "guanyu-risk/research/factors-strategy-risk-control-20260327/risk_control.py",
+      "source_location": "L95",
+      "id": "factors_strategy_risk_control_20260327_risk_control_rationale_95",
+      "community": 81,
+      "norm_label": "\u83b7\u53d6\u76ee\u6807\u4ed3\u4f4d\u6bd4\u4f8b         :return: \u76ee\u6807\u4ed3\u4f4d\u5360\u5f53\u524d\u603b\u8d44\u91d1\u7684\u6bd4\u4f8b"
+    },
+    {
+      "label": "\u68c0\u67e5\u662f\u5426\u9700\u8981\u964d\u4ed3         :return: (\u662f\u5426\u9700\u8981\u8c03\u6574, \u76ee\u6807\u4ed3\u4f4d\u6bd4\u4f8b)",
+      "file_type": "rationale",
+      "source_file": "guanyu-risk/research/factors-strategy-risk-control-20260327/risk_control.py",
+      "source_location": "L110",
+      "id": "factors_strategy_risk_control_20260327_risk_control_rationale_110",
+      "community": 81,
+      "norm_label": "\u68c0\u67e5\u662f\u5426\u9700\u8981\u964d\u4ed3         :return: (\u662f\u5426\u9700\u8981\u8c03\u6574, \u76ee\u6807\u4ed3\u4f4d\u6bd4\u4f8b)"
+    },
+    {
+      "label": "\u9ed1\u5929\u9e45\u8fc7\u6ee4\uff1a\u6392\u9664ST\u3001\u8dcc\u505c\u3001\u8d22\u52a1\u9020\u5047\u3001\u4f4e\u6d41\u52a8\u6027\u7968",
+      "file_type": "rationale",
+      "source_file": "guanyu-risk/research/factors-strategy-risk-control-20260327/risk_control.py",
+      "source_location": "L125",
+      "id": "factors_strategy_risk_control_20260327_risk_control_rationale_125",
+      "community": 310,
+      "norm_label": "\u9ed1\u5929\u9e45\u8fc7\u6ee4:\u6392\u9664st\u3001\u8dcc\u505c\u3001\u8d22\u52a1\u9020\u5047\u3001\u4f4e\u6d41\u52a8\u6027\u7968"
+    },
+    {
+      "label": "\u521d\u59cb\u5316\u8fc7\u6ee4\u5668         :param min_daily_volume: \u6700\u5c0f\u65e5\u6210\u4ea4\u989d\uff08\u4ebf\uff09\uff0c\u4f4e\u4e8e\u6b64\u6392\u9664",
+      "file_type": "rationale",
+      "source_file": "guanyu-risk/research/factors-strategy-risk-control-20260327/risk_control.py",
+      "source_location": "L128",
+      "id": "factors_strategy_risk_control_20260327_risk_control_rationale_128",
+      "community": 310,
+      "norm_label": "\u521d\u59cb\u5316\u8fc7\u6ee4\u5668         :param min_daily_volume: \u6700\u5c0f\u65e5\u6210\u4ea4\u989d(\u4ebf),\u4f4e\u4e8e\u6b64\u6392\u9664"
+    },
+    {
+      "label": "\u8fc7\u6ee4\u4e2a\u80a1         :return: (\u662f\u5426\u901a\u8fc7\u8fc7\u6ee4, \u4e0d\u901a\u8fc7\u539f\u56e0)         True = \u53ef\u4ee5\u4e70\u5165\uff0cFalse = \u6392\u9664",
+      "file_type": "rationale",
+      "source_file": "guanyu-risk/research/factors-strategy-risk-control-20260327/risk_control.py",
+      "source_location": "L135",
+      "id": "factors_strategy_risk_control_20260327_risk_control_rationale_135",
+      "community": 310,
+      "norm_label": "\u8fc7\u6ee4\u4e2a\u80a1         :return: (\u662f\u5426\u901a\u8fc7\u8fc7\u6ee4, \u4e0d\u901a\u8fc7\u539f\u56e0)         true = \u53ef\u4ee5\u4e70\u5165,false = \u6392\u9664"
+    },
+    {
+      "label": "\u4ea4\u6613\u524d\u68c0\u67e5\uff1a\u5f00\u4ed3\u524d\u8c03\u7528         :return: (\u662f\u5426\u5141\u8bb8\u5f00\u4ed3, \u539f\u56e0)",
+      "file_type": "rationale",
+      "source_file": "guanyu-risk/research/factors-strategy-risk-control-20260327/risk_control.py",
+      "source_location": "L178",
+      "id": "factors_strategy_risk_control_20260327_risk_control_rationale_178",
+      "community": 81,
+      "norm_label": "\u4ea4\u6613\u524d\u68c0\u67e5:\u5f00\u4ed3\u524d\u8c03\u7528         :return: (\u662f\u5426\u5141\u8bb8\u5f00\u4ed3, \u539f\u56e0)"
+    },
+    {
+      "label": "\u6536\u76d8\u540e\u68c0\u67e5\uff1a\u6b62\u635f\u68c0\u67e5 + \u964d\u4ed3\u68c0\u67e5         :return: \u98ce\u63a7\u7ed3\u679c\uff0c\u5305\u542b\u9700\u8981\u6b62\u635f\u7684\u7968\u548c\u9700\u8981\u964d\u4ed3\u7684\u4fe1\u606f",
+      "file_type": "rationale",
+      "source_file": "guanyu-risk/research/factors-strategy-risk-control-20260327/risk_control.py",
+      "source_location": "L197",
+      "id": "factors_strategy_risk_control_20260327_risk_control_rationale_197",
+      "community": 81,
+      "norm_label": "\u6536\u76d8\u540e\u68c0\u67e5:\u6b62\u635f\u68c0\u67e5 + \u964d\u4ed3\u68c0\u67e5         :return: \u98ce\u63a7\u7ed3\u679c,\u5305\u542b\u9700\u8981\u6b62\u635f\u7684\u7968\u548c\u9700\u8981\u964d\u4ed3\u7684\u4fe1\u606f"
+    },
+    {
+      "label": "technical_selection_backtest_with_risk.py",
+      "file_type": "code",
+      "source_file": "guanyu-risk/research/factors-strategy-risk-control-20260327/technical_selection_backtest_with_risk.py",
+      "source_location": "L1",
+      "id": "guanyu_risk_research_factors_strategy_risk_control_20260327_technical_selection_backtest_with_risk_py",
+      "community": 41,
+      "norm_label": "technical_selection_backtest_with_risk.py"
+    },
+    {
+      "label": "Trade",
+      "file_type": "code",
+      "source_file": "guanyu-risk/research/factors-strategy-risk-control-20260327/technical_selection_backtest_with_risk.py",
+      "source_location": "L30",
+      "id": "factors_strategy_risk_control_20260327_technical_selection_backtest_with_risk_trade",
+      "community": 41,
+      "norm_label": "trade"
+    },
+    {
+      "label": "BacktestResult",
+      "file_type": "code",
+      "source_file": "guanyu-risk/research/factors-strategy-risk-control-20260327/technical_selection_backtest_with_risk.py",
+      "source_location": "L47",
+      "id": "factors_strategy_risk_control_20260327_technical_selection_backtest_with_risk_backtestresult",
+      "community": 41,
+      "norm_label": "backtestresult"
+    },
+    {
+      "label": "TechnicalIndicators",
+      "file_type": "code",
+      "source_file": "guanyu-risk/research/factors-strategy-risk-control-20260327/technical_selection_backtest_with_risk.py",
+      "source_location": "L67",
+      "id": "factors_strategy_risk_control_20260327_technical_selection_backtest_with_risk_technicalindicators",
+      "community": 41,
+      "norm_label": "technicalindicators"
+    },
+    {
+      "label": "sma()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/research/factors-strategy-risk-control-20260327/technical_selection_backtest_with_risk.py",
+      "source_location": "L69",
+      "id": "factors_strategy_risk_control_20260327_technical_selection_backtest_with_risk_sma",
+      "community": 41,
+      "norm_label": "sma()"
+    },
+    {
+      "label": "ema()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/research/factors-strategy-risk-control-20260327/technical_selection_backtest_with_risk.py",
+      "source_location": "L73",
+      "id": "factors_strategy_risk_control_20260327_technical_selection_backtest_with_risk_ema",
+      "community": 41,
+      "norm_label": "ema()"
+    },
+    {
+      "label": "macd()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/research/factors-strategy-risk-control-20260327/technical_selection_backtest_with_risk.py",
+      "source_location": "L77",
+      "id": "factors_strategy_risk_control_20260327_technical_selection_backtest_with_risk_macd",
+      "community": 41,
+      "norm_label": "macd()"
+    },
+    {
+      "label": "bollinger_bands()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/research/factors-strategy-risk-control-20260327/technical_selection_backtest_with_risk.py",
+      "source_location": "L86",
+      "id": "factors_strategy_risk_control_20260327_technical_selection_backtest_with_risk_bollinger_bands",
+      "community": 41,
+      "norm_label": "bollinger_bands()"
+    },
+    {
+      "label": "donchian_channel()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/research/factors-strategy-risk-control-20260327/technical_selection_backtest_with_risk.py",
+      "source_location": "L94",
+      "id": "factors_strategy_risk_control_20260327_technical_selection_backtest_with_risk_donchian_channel",
+      "community": 41,
+      "norm_label": "donchian_channel()"
+    },
+    {
+      "label": "atr()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/research/factors-strategy-risk-control-20260327/technical_selection_backtest_with_risk.py",
+      "source_location": "L100",
+      "id": "factors_strategy_risk_control_20260327_technical_selection_backtest_with_risk_atr",
+      "community": 41,
+      "norm_label": "atr()"
+    },
+    {
+      "label": "MACDDivergenceStrategy",
+      "file_type": "code",
+      "source_file": "guanyu-risk/research/factors-strategy-risk-control-20260327/technical_selection_backtest_with_risk.py",
+      "source_location": "L110",
+      "id": "factors_strategy_risk_control_20260327_technical_selection_backtest_with_risk_macddivergencestrategy",
+      "community": 41,
+      "norm_label": "macddivergencestrategy"
+    },
+    {
+      "label": ".__init__()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/research/factors-strategy-risk-control-20260327/technical_selection_backtest_with_risk.py",
+      "source_location": "L111",
+      "id": "factors_strategy_risk_control_20260327_technical_selection_backtest_with_risk_macddivergencestrategy_init",
+      "community": 41,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": ".check_buy_signal()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/research/factors-strategy-risk-control-20260327/technical_selection_backtest_with_risk.py",
+      "source_location": "L118",
+      "id": "factors_strategy_risk_control_20260327_technical_selection_backtest_with_risk_macddivergencestrategy_check_buy_signal",
+      "community": 41,
+      "norm_label": ".check_buy_signal()"
+    },
+    {
+      "label": ".check_sell_signal()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/research/factors-strategy-risk-control-20260327/technical_selection_backtest_with_risk.py",
+      "source_location": "L140",
+      "id": "factors_strategy_risk_control_20260327_technical_selection_backtest_with_risk_macddivergencestrategy_check_sell_signal",
+      "community": 41,
+      "norm_label": ".check_sell_signal()"
+    },
+    {
+      "label": "BollingerBandsStrategy",
+      "file_type": "code",
+      "source_file": "guanyu-risk/research/factors-strategy-risk-control-20260327/technical_selection_backtest_with_risk.py",
+      "source_location": "L154",
+      "id": "factors_strategy_risk_control_20260327_technical_selection_backtest_with_risk_bollingerbandsstrategy",
+      "community": 41,
+      "norm_label": "bollingerbandsstrategy"
+    },
+    {
+      "label": ".__init__()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/research/factors-strategy-risk-control-20260327/technical_selection_backtest_with_risk.py",
+      "source_location": "L155",
+      "id": "factors_strategy_risk_control_20260327_technical_selection_backtest_with_risk_bollingerbandsstrategy_init",
+      "community": 41,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": ".rsi()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/research/factors-strategy-risk-control-20260327/technical_selection_backtest_with_risk.py",
+      "source_location": "L162",
+      "id": "factors_strategy_risk_control_20260327_technical_selection_backtest_with_risk_bollingerbandsstrategy_rsi",
+      "community": 41,
+      "norm_label": ".rsi()"
+    },
+    {
+      "label": ".check_buy_signal()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/research/factors-strategy-risk-control-20260327/technical_selection_backtest_with_risk.py",
+      "source_location": "L179",
+      "id": "factors_strategy_risk_control_20260327_technical_selection_backtest_with_risk_bollingerbandsstrategy_check_buy_signal",
+      "community": 41,
+      "norm_label": ".check_buy_signal()"
+    },
+    {
+      "label": ".check_sell_signal()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/research/factors-strategy-risk-control-20260327/technical_selection_backtest_with_risk.py",
+      "source_location": "L202",
+      "id": "factors_strategy_risk_control_20260327_technical_selection_backtest_with_risk_bollingerbandsstrategy_check_sell_signal",
+      "community": 41,
+      "norm_label": ".check_sell_signal()"
+    },
+    {
+      "label": "DonchianChannelStrategy",
+      "file_type": "code",
+      "source_file": "guanyu-risk/research/factors-strategy-risk-control-20260327/technical_selection_backtest_with_risk.py",
+      "source_location": "L220",
+      "id": "factors_strategy_risk_control_20260327_technical_selection_backtest_with_risk_donchianchannelstrategy",
+      "community": 41,
+      "norm_label": "donchianchannelstrategy"
+    },
+    {
+      "label": ".__init__()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/research/factors-strategy-risk-control-20260327/technical_selection_backtest_with_risk.py",
+      "source_location": "L221",
+      "id": "factors_strategy_risk_control_20260327_technical_selection_backtest_with_risk_donchianchannelstrategy_init",
+      "community": 41,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": ".check_buy_signal()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/research/factors-strategy-risk-control-20260327/technical_selection_backtest_with_risk.py",
+      "source_location": "L228",
+      "id": "factors_strategy_risk_control_20260327_technical_selection_backtest_with_risk_donchianchannelstrategy_check_buy_signal",
+      "community": 41,
+      "norm_label": ".check_buy_signal()"
+    },
+    {
+      "label": ".check_sell_signal()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/research/factors-strategy-risk-control-20260327/technical_selection_backtest_with_risk.py",
+      "source_location": "L244",
+      "id": "factors_strategy_risk_control_20260327_technical_selection_backtest_with_risk_donchianchannelstrategy_check_sell_signal",
+      "community": 41,
+      "norm_label": ".check_sell_signal()"
+    },
+    {
+      "label": "BacktestEngine",
+      "file_type": "code",
+      "source_file": "guanyu-risk/research/factors-strategy-risk-control-20260327/technical_selection_backtest_with_risk.py",
+      "source_location": "L260",
+      "id": "factors_strategy_risk_control_20260327_technical_selection_backtest_with_risk_backtestengine",
+      "community": 41,
+      "norm_label": "backtestengine"
+    },
+    {
+      "label": ".__init__()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/research/factors-strategy-risk-control-20260327/technical_selection_backtest_with_risk.py",
+      "source_location": "L261",
+      "id": "factors_strategy_risk_control_20260327_technical_selection_backtest_with_risk_backtestengine_init",
+      "community": 41,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": ".backtest()",
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+      "norm_label": "._calculate_performance()"
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+      "norm_label": "main()"
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+      "label": "Technical Selection Strategies Backtest Framework with Risk Control  Implements",
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+      "norm_label": "technical selection strategies backtest framework with risk control  implements"
+    },
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+      "id": "tests_stress_test_test_normal_market",
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+      "norm_label": "test_normal_market()"
+    },
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+      "norm_label": "test_daily_drawdown_warning()"
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+      "id": "tests_stress_test_test_continuous_drawdown",
+      "community": 73,
+      "norm_label": "test_continuous_drawdown()"
+    },
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+      "community": 73,
+      "norm_label": "test_high_position_concentration()"
+    },
+    {
+      "label": "test_emergency_liquidate()",
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+      "source_location": "L122",
+      "id": "tests_stress_test_test_emergency_liquidate",
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+      "norm_label": "test_emergency_liquidate()"
+    },
+    {
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+      "source_location": "L147",
+      "id": "tests_stress_test_test_performance",
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+      "norm_label": "test_performance()"
+    },
+    {
+      "label": "main()",
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+      "source_location": "L182",
+      "id": "tests_stress_test_main",
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+      "norm_label": "main()"
+    },
+    {
+      "label": "\u5b9e\u65f6\u98ce\u63a7\u7cfb\u7edf\u538b\u529b\u6d4b\u8bd5 ============  \u6d4b\u8bd5\u573a\u666f\uff1a 1. \u6b63\u5e38\u884c\u60c5\u6ce2\u52a8 - \u65e0\u9884\u8b66 2. \u5355\u65e5\u56de\u64a4 - \u89e6\u53d1\u8b66\u544a 3. \u8fde\u7eed\u56de\u64a4 - \u89e6\u53d1\u7d27\u6025\u5904\u7406 4",
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+    },
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+    },
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+      "label": "RiskMetrics",
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+      "source_location": "L19",
+      "id": "src_risk_calculator_riskmetrics",
+      "community": 104,
+      "norm_label": "riskmetrics"
+    },
+    {
+      "label": ".to_dict()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/risk_calculator.py",
+      "source_location": "L35",
+      "id": "src_risk_calculator_riskmetrics_to_dict",
+      "community": 104,
+      "norm_label": ".to_dict()"
+    },
+    {
+      "label": "RealTimeRiskCalculator",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/risk_calculator.py",
+      "source_location": "L54",
+      "id": "src_risk_calculator_realtimeriskcalculator",
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+      "norm_label": "realtimeriskcalculator"
+    },
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+      "id": "src_risk_calculator_realtimeriskcalculator_init",
+      "community": 104,
+      "norm_label": ".__init__()"
+    },
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+      "label": ".update_net_value()",
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+      "community": 104,
+      "norm_label": ".update_net_value()"
+    },
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+      "label": ".update_position()",
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+      "id": "src_risk_calculator_realtimeriskcalculator_update_position",
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+      "source_location": "L105",
+      "id": "src_risk_calculator_realtimeriskcalculator_remove_position",
+      "community": 104,
+      "norm_label": ".remove_position()"
+    },
+    {
+      "label": ".calculate_var()",
+      "file_type": "code",
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+      "source_location": "L112",
+      "id": "src_risk_calculator_realtimeriskcalculator_calculate_var",
+      "community": 104,
+      "norm_label": ".calculate_var()"
+    },
+    {
+      "label": ".calculate_volatility()",
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+      "source_location": "L124",
+      "id": "src_risk_calculator_realtimeriskcalculator_calculate_volatility",
+      "community": 104,
+      "norm_label": ".calculate_volatility()"
+    },
+    {
+      "label": ".calculate_concentration()",
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+      "source_location": "L133",
+      "id": "src_risk_calculator_realtimeriskcalculator_calculate_concentration",
+      "community": 104,
+      "norm_label": ".calculate_concentration()"
+    },
+    {
+      "label": ".calculate_drawdowns()",
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+      "source_location": "L141",
+      "id": "src_risk_calculator_realtimeriskcalculator_calculate_drawdowns",
+      "community": 104,
+      "norm_label": ".calculate_drawdowns()"
+    },
+    {
+      "label": ".calculate_all_metrics()",
+      "file_type": "code",
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+      "source_location": "L173",
+      "id": "src_risk_calculator_realtimeriskcalculator_calculate_all_metrics",
+      "community": 104,
+      "norm_label": ".calculate_all_metrics()"
+    },
+    {
+      "label": "\u5b9e\u65f6\u98ce\u9669\u6307\u6807\u8ba1\u7b97\u5f15\u64ce ============  \u5b9e\u65f6\u8ba1\u7b97\u5404\u7c7b\u98ce\u9669\u6307\u6807\uff0c\u652f\u6301\uff1a - \u6301\u4ed3\u98ce\u9669\u6307\u6807\u8ba1\u7b97 - \u52a8\u6001VaR\u8ba1\u7b97 - \u5b9e\u65f6\u56de\u64a4\u76d1\u63a7 - \u6d41\u52a8\u6027\u98ce\u9669\u8ba1\u7b97",
+      "file_type": "rationale",
+      "source_file": "guanyu-risk/realtime-system/src/risk_calculator.py",
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+    },
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+      "label": "risk_monitor.py",
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+      "source_file": "guanyu-risk/realtime-system/src/risk_monitor.py",
+      "source_location": "L1",
+      "id": "guanyu_risk_realtime_system_src_risk_monitor_py",
+      "community": 89,
+      "norm_label": "risk_monitor.py"
+    },
+    {
+      "label": "AlertLevel",
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+      "source_location": "L19",
+      "id": "src_risk_monitor_alertlevel",
+      "community": 89,
+      "norm_label": "alertlevel"
+    },
+    {
+      "label": "RiskAlert",
+      "file_type": "code",
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+      "source_location": "L28",
+      "id": "src_risk_monitor_riskalert",
+      "community": 91,
+      "norm_label": "riskalert"
+    },
+    {
+      "label": ".to_dict()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/risk_monitor.py",
+      "source_location": "L40",
+      "id": "src_risk_monitor_riskalert_to_dict",
+      "community": 91,
+      "norm_label": ".to_dict()"
+    },
+    {
+      "label": "ThresholdConfig",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/risk_monitor.py",
+      "source_location": "L54",
+      "id": "src_risk_monitor_thresholdconfig",
+      "community": 104,
+      "norm_label": "thresholdconfig"
+    },
+    {
+      "label": ".__init__()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/risk_monitor.py",
+      "source_location": "L57",
+      "id": "src_risk_monitor_thresholdconfig_init",
+      "community": 104,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": "conservative()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/risk_monitor.py",
+      "source_location": "L87",
+      "id": "src_risk_monitor_conservative",
+      "community": 89,
+      "norm_label": "conservative()"
+    },
+    {
+      "label": "aggressive()",
+      "file_type": "code",
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+      "id": "src_risk_monitor_aggressive",
+      "community": 89,
+      "norm_label": "aggressive()"
+    },
+    {
+      "label": "RealTimeRiskMonitor",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/risk_monitor.py",
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+      "id": "src_risk_monitor_realtimeriskmonitor",
+      "community": 91,
+      "norm_label": "realtimeriskmonitor"
+    },
+    {
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+      "source_file": "guanyu-risk/realtime-system/src/risk_monitor.py",
+      "source_location": "L128",
+      "id": "src_risk_monitor_realtimeriskmonitor_init",
+      "community": 104,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": "._generate_alert_id()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/risk_monitor.py",
+      "source_location": "L145",
+      "id": "src_risk_monitor_realtimeriskmonitor_generate_alert_id",
+      "community": 91,
+      "norm_label": "._generate_alert_id()"
+    },
+    {
+      "label": ".check_daily_drawdown()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/risk_monitor.py",
+      "source_location": "L151",
+      "id": "src_risk_monitor_realtimeriskmonitor_check_daily_drawdown",
+      "community": 91,
+      "norm_label": ".check_daily_drawdown()"
+    },
+    {
+      "label": ".check_total_drawdown()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/risk_monitor.py",
+      "source_location": "L179",
+      "id": "src_risk_monitor_realtimeriskmonitor_check_total_drawdown",
+      "community": 91,
+      "norm_label": ".check_total_drawdown()"
+    },
+    {
+      "label": ".check_max_drawdown()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/risk_monitor.py",
+      "source_location": "L207",
+      "id": "src_risk_monitor_realtimeriskmonitor_check_max_drawdown",
+      "community": 91,
+      "norm_label": ".check_max_drawdown()"
+    },
+    {
+      "label": ".check_position_pct()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/risk_monitor.py",
+      "source_location": "L224",
+      "id": "src_risk_monitor_realtimeriskmonitor_check_position_pct",
+      "community": 91,
+      "norm_label": ".check_position_pct()"
+    },
+    {
+      "label": ".check_concentration()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/risk_monitor.py",
+      "source_location": "L252",
+      "id": "src_risk_monitor_realtimeriskmonitor_check_concentration",
+      "community": 91,
+      "norm_label": ".check_concentration()"
+    },
+    {
+      "label": ".check_var()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/risk_monitor.py",
+      "source_location": "L280",
+      "id": "src_risk_monitor_realtimeriskmonitor_check_var",
+      "community": 91,
+      "norm_label": ".check_var()"
+    },
+    {
+      "label": ".check_volatility()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/risk_monitor.py",
+      "source_location": "L308",
+      "id": "src_risk_monitor_realtimeriskmonitor_check_volatility",
+      "community": 91,
+      "norm_label": ".check_volatility()"
+    },
+    {
+      "label": ".check_all()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/risk_monitor.py",
+      "source_location": "L336",
+      "id": "src_risk_monitor_realtimeriskmonitor_check_all",
+      "community": 91,
+      "norm_label": ".check_all()"
+    },
+    {
+      "label": ".update_and_check()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/risk_monitor.py",
+      "source_location": "L364",
+      "id": "src_risk_monitor_realtimeriskmonitor_update_and_check",
+      "community": 91,
+      "norm_label": ".update_and_check()"
+    },
+    {
+      "label": ".mark_handled()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/risk_monitor.py",
+      "source_location": "L379",
+      "id": "src_risk_monitor_realtimeriskmonitor_mark_handled",
+      "community": 91,
+      "norm_label": ".mark_handled()"
+    },
+    {
+      "label": ".get_unhandled_alerts()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/risk_monitor.py",
+      "source_location": "L388",
+      "id": "src_risk_monitor_realtimeriskmonitor_get_unhandled_alerts",
+      "community": 91,
+      "norm_label": ".get_unhandled_alerts()"
+    },
+    {
+      "label": ".get_all_alerts()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/risk_monitor.py",
+      "source_location": "L392",
+      "id": "src_risk_monitor_realtimeriskmonitor_get_all_alerts",
+      "community": 91,
+      "norm_label": ".get_all_alerts()"
+    },
+    {
+      "label": ".get_alerts_by_level()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/risk_monitor.py",
+      "source_location": "L396",
+      "id": "src_risk_monitor_realtimeriskmonitor_get_alerts_by_level",
+      "community": 91,
+      "norm_label": ".get_alerts_by_level()"
+    },
+    {
+      "label": ".has_critical_alerts()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/risk_monitor.py",
+      "source_location": "L400",
+      "id": "src_risk_monitor_realtimeriskmonitor_has_critical_alerts",
+      "community": 91,
+      "norm_label": ".has_critical_alerts()"
+    },
+    {
+      "label": ".has_emergency_alerts()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/risk_monitor.py",
+      "source_location": "L404",
+      "id": "src_risk_monitor_realtimeriskmonitor_has_emergency_alerts",
+      "community": 91,
+      "norm_label": ".has_emergency_alerts()"
+    },
+    {
+      "label": "\u5b9e\u65f6\u98ce\u9669\u9608\u503c\u76d1\u63a7\u7cfb\u7edf ============  \u5b9e\u65f6\u76d1\u63a7\u98ce\u9669\u6307\u6807\uff0c\u89e6\u53d1\u9608\u503c\u81ea\u52a8\u9884\u8b66\uff1a - \u5355\u65e5\u56de\u64a4\u9884\u8b66 - \u7d2f\u8ba1\u56de\u64a4\u9884\u8b66 - \u9ad8\u4ed3\u4f4d\u9884\u8b66 - \u96c6\u4e2d\u5ea6\u9884\u8b66 -",
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+      "source_file": "guanyu-risk/realtime-system/src/risk_monitor.py",
+      "source_location": "L1",
+      "id": "src_risk_monitor_rationale_1",
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+    },
+    {
+      "label": "realtime_risk_panel.py",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/realtime_risk_panel.py",
+      "source_location": "L1",
+      "id": "guanyu_risk_realtime_system_src_realtime_risk_panel_py",
+      "community": 73,
+      "norm_label": "realtime_risk_panel.py"
+    },
+    {
+      "label": "RealtimeRiskPanel",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/realtime_risk_panel.py",
+      "source_location": "L14",
+      "id": "src_realtime_risk_panel_realtimeriskpanel",
+      "community": 73,
+      "norm_label": "realtimeriskpanel"
+    },
+    {
+      "label": ".__init__()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/realtime_risk_panel.py",
+      "source_location": "L17",
+      "id": "src_realtime_risk_panel_realtimeriskpanel_init",
+      "community": 92,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": "._on_alert()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/realtime_risk_panel.py",
+      "source_location": "L57",
+      "id": "src_realtime_risk_panel_realtimeriskpanel_on_alert",
+      "community": 73,
+      "norm_label": "._on_alert()"
+    },
+    {
+      "label": "._on_emergency()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/realtime_risk_panel.py",
+      "source_location": "L62",
+      "id": "src_realtime_risk_panel_realtimeriskpanel_on_emergency",
+      "community": 73,
+      "norm_label": "._on_emergency()"
+    },
+    {
+      "label": ".update()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/realtime_risk_panel.py",
+      "source_location": "L67",
+      "id": "src_realtime_risk_panel_realtimeriskpanel_update",
+      "community": 73,
+      "norm_label": ".update()"
+    },
+    {
+      "label": ".update_position()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/realtime_risk_panel.py",
+      "source_location": "L89",
+      "id": "src_realtime_risk_panel_realtimeriskpanel_update_position",
+      "community": 73,
+      "norm_label": ".update_position()"
+    },
+    {
+      "label": ".remove_position()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/realtime_risk_panel.py",
+      "source_location": "L94",
+      "id": "src_realtime_risk_panel_realtimeriskpanel_remove_position",
+      "community": 73,
+      "norm_label": ".remove_position()"
+    },
+    {
+      "label": ".update_net_value()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/realtime_risk_panel.py",
+      "source_location": "L98",
+      "id": "src_realtime_risk_panel_realtimeriskpanel_update_net_value",
+      "community": 73,
+      "norm_label": ".update_net_value()"
+    },
+    {
+      "label": ".get_current_metrics()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/realtime_risk_panel.py",
+      "source_location": "L102",
+      "id": "src_realtime_risk_panel_realtimeriskpanel_get_current_metrics",
+      "community": 73,
+      "norm_label": ".get_current_metrics()"
+    },
+    {
+      "label": ".get_all_alerts()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/realtime_risk_panel.py",
+      "source_location": "L106",
+      "id": "src_realtime_risk_panel_realtimeriskpanel_get_all_alerts",
+      "community": 73,
+      "norm_label": ".get_all_alerts()"
+    },
+    {
+      "label": ".get_unhandled_alerts()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/realtime_risk_panel.py",
+      "source_location": "L110",
+      "id": "src_realtime_risk_panel_realtimeriskpanel_get_unhandled_alerts",
+      "community": 73,
+      "norm_label": ".get_unhandled_alerts()"
+    },
+    {
+      "label": ".get_action_history()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/realtime_risk_panel.py",
+      "source_location": "L114",
+      "id": "src_realtime_risk_panel_realtimeriskpanel_get_action_history",
+      "community": 73,
+      "norm_label": ".get_action_history()"
+    },
+    {
+      "label": ".get_current_level()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/realtime_risk_panel.py",
+      "source_location": "L118",
+      "id": "src_realtime_risk_panel_realtimeriskpanel_get_current_level",
+      "community": 73,
+      "norm_label": ".get_current_level()"
+    },
+    {
+      "label": ".mark_alert_handled()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/realtime_risk_panel.py",
+      "source_location": "L122",
+      "id": "src_realtime_risk_panel_realtimeriskpanel_mark_alert_handled",
+      "community": 73,
+      "norm_label": ".mark_alert_handled()"
+    },
+    {
+      "label": ".clear_all()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/realtime_risk_panel.py",
+      "source_location": "L130",
+      "id": "src_realtime_risk_panel_realtimeriskpanel_clear_all",
+      "community": 73,
+      "norm_label": ".clear_all()"
+    },
+    {
+      "label": ".get_panel_summary()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/realtime_risk_panel.py",
+      "source_location": "L134",
+      "id": "src_realtime_risk_panel_realtimeriskpanel_get_panel_summary",
+      "community": 73,
+      "norm_label": ".get_panel_summary()"
+    },
+    {
+      "label": "\u5b9e\u65f6\u98ce\u63a7\u9762\u677f\uff08\u4e3b\u5165\u53e3\uff09 ============  \u6574\u5408\u98ce\u9669\u8ba1\u7b97\u3001\u76d1\u63a7\u3001\u7d27\u6025\u5904\u7406\uff0c\u63d0\u4f9b\u7edf\u4e00\u63a5\u53e3",
+      "file_type": "rationale",
+      "source_file": "guanyu-risk/realtime-system/src/realtime_risk_panel.py",
+      "source_location": "L1",
+      "id": "src_realtime_risk_panel_rationale_1",
+      "community": 73,
+      "norm_label": "\u5b9e\u65f6\u98ce\u63a7\u9762\u677f(\u4e3b\u5165\u53e3) ============  \u6574\u5408\u98ce\u9669\u8ba1\u7b97\u3001\u76d1\u63a7\u3001\u7d27\u6025\u5904\u7406,\u63d0\u4f9b\u7edf\u4e00\u63a5\u53e3"
+    },
+    {
+      "label": "\u521d\u59cb\u5316                  \u53c2\u6570:             risk_style: \"conservative\" / \"aggressive\"",
+      "file_type": "rationale",
+      "source_file": "guanyu-risk/realtime-system/src/realtime_risk_panel.py",
+      "source_location": "L21",
+      "id": "src_realtime_risk_panel_rationale_21",
+      "community": 92,
+      "norm_label": "\u521d\u59cb\u5316                  \u53c2\u6570:             risk_style: \"conservative\" / \"aggressive\""
+    },
+    {
+      "label": "emergency_handler.py",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/emergency_handler.py",
+      "source_location": "L1",
+      "id": "guanyu_risk_realtime_system_src_emergency_handler_py",
+      "community": 89,
+      "norm_label": "emergency_handler.py"
+    },
+    {
+      "label": "EmergencyLevel",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/emergency_handler.py",
+      "source_location": "L20",
+      "id": "src_emergency_handler_emergencylevel",
+      "community": 89,
+      "norm_label": "emergencylevel"
+    },
+    {
+      "label": "EmergencyAction",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/emergency_handler.py",
+      "source_location": "L31",
+      "id": "src_emergency_handler_emergencyaction",
+      "community": 89,
+      "norm_label": "emergencyaction"
+    },
+    {
+      "label": ".to_dict()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/emergency_handler.py",
+      "source_location": "L41",
+      "id": "src_emergency_handler_emergencyaction_to_dict",
+      "community": 89,
+      "norm_label": ".to_dict()"
+    },
+    {
+      "label": "EmergencyConfig",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/emergency_handler.py",
+      "source_location": "L53",
+      "id": "src_emergency_handler_emergencyconfig",
+      "community": 92,
+      "norm_label": "emergencyconfig"
+    },
+    {
+      "label": ".__init__()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/emergency_handler.py",
+      "source_location": "L56",
+      "id": "src_emergency_handler_emergencyconfig_init",
+      "community": 92,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": "EmergencyHandler",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/emergency_handler.py",
+      "source_location": "L68",
+      "id": "src_emergency_handler_emergencyhandler",
+      "community": 92,
+      "norm_label": "emergencyhandler"
+    },
+    {
+      "label": ".__init__()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/emergency_handler.py",
+      "source_location": "L71",
+      "id": "src_emergency_handler_emergencyhandler_init",
+      "community": 92,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": "._generate_action_id()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/emergency_handler.py",
+      "source_location": "L90",
+      "id": "src_emergency_handler_emergencyhandler_generate_action_id",
+      "community": 92,
+      "norm_label": "._generate_action_id()"
+    },
+    {
+      "label": ".assess_emergency_level()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/emergency_handler.py",
+      "source_location": "L96",
+      "id": "src_emergency_handler_emergencyhandler_assess_emergency_level",
+      "community": 92,
+      "norm_label": ".assess_emergency_level()"
+    },
+    {
+      "label": ".create_action()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/emergency_handler.py",
+      "source_location": "L121",
+      "id": "src_emergency_handler_emergencyhandler_create_action",
+      "community": 92,
+      "norm_label": ".create_action()"
+    },
+    {
+      "label": ".execute_action()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/emergency_handler.py",
+      "source_location": "L142",
+      "id": "src_emergency_handler_emergencyhandler_execute_action",
+      "community": 92,
+      "norm_label": ".execute_action()"
+    },
+    {
+      "label": ".check_and_handle()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/emergency_handler.py",
+      "source_location": "L191",
+      "id": "src_emergency_handler_emergencyhandler_check_and_handle",
+      "community": 92,
+      "norm_label": ".check_and_handle()"
+    },
+    {
+      "label": ".get_current_level()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/emergency_handler.py",
+      "source_location": "L214",
+      "id": "src_emergency_handler_emergencyhandler_get_current_level",
+      "community": 92,
+      "norm_label": ".get_current_level()"
+    },
+    {
+      "label": ".get_action_history()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/emergency_handler.py",
+      "source_location": "L218",
+      "id": "src_emergency_handler_emergencyhandler_get_action_history",
+      "community": 92,
+      "norm_label": ".get_action_history()"
+    },
+    {
+      "label": ".get_unexecuted_actions()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/emergency_handler.py",
+      "source_location": "L222",
+      "id": "src_emergency_handler_emergencyhandler_get_unexecuted_actions",
+      "community": 92,
+      "norm_label": ".get_unexecuted_actions()"
+    },
+    {
+      "label": ".clear_all_alerts()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/emergency_handler.py",
+      "source_location": "L226",
+      "id": "src_emergency_handler_emergencyhandler_clear_all_alerts",
+      "community": 92,
+      "norm_label": ".clear_all_alerts()"
+    },
+    {
+      "label": ".can_open_position()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/emergency_handler.py",
+      "source_location": "L235",
+      "id": "src_emergency_handler_emergencyhandler_can_open_position",
+      "community": 92,
+      "norm_label": ".can_open_position()"
+    },
+    {
+      "label": ".can_close_position()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/emergency_handler.py",
+      "source_location": "L240",
+      "id": "src_emergency_handler_emergencyhandler_can_close_position",
+      "community": 92,
+      "norm_label": ".can_close_position()"
+    },
+    {
+      "label": ".need_emergency_liquidate()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/emergency_handler.py",
+      "source_location": "L244",
+      "id": "src_emergency_handler_emergencyhandler_need_emergency_liquidate",
+      "community": 92,
+      "norm_label": ".need_emergency_liquidate()"
+    },
+    {
+      "label": ".is_system_running()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/emergency_handler.py",
+      "source_location": "L248",
+      "id": "src_emergency_handler_emergencyhandler_is_system_running",
+      "community": 92,
+      "norm_label": ".is_system_running()"
+    },
+    {
+      "label": "\u4ea4\u6613\u4e2d\u65ad\u548c\u7d27\u6025\u5904\u7406\u7b97\u6cd5 ============  \u63d0\u4f9b\u591a\u7ea7\u7d27\u6025\u98ce\u9669\u5904\u7f6e\uff1a - \u7ea7\u522b1\uff1a\u9884\u8b66\u63d0\u793a\uff08\u4e0d\u5e72\u9884\uff0c\u53ea\u901a\u77e5\uff09 - \u7ea7\u522b2\uff1a\u9650\u5236\u5f00\u4ed3\uff08\u53ea\u5141\u8bb8\u5e73\u4ed3\uff0c\u4e0d\u5141\u8bb8\u5f00\u4ed3",
+      "file_type": "rationale",
+      "source_file": "guanyu-risk/realtime-system/src/emergency_handler.py",
+      "source_location": "L1",
+      "id": "src_emergency_handler_rationale_1",
+      "community": 89,
+      "norm_label": "\u4ea4\u6613\u4e2d\u65ad\u548c\u7d27\u6025\u5904\u7406\u7b97\u6cd5 ============  \u63d0\u4f9b\u591a\u7ea7\u7d27\u6025\u98ce\u9669\u5904\u7f6e: - \u7ea7\u522b1:\u9884\u8b66\u63d0\u793a(\u4e0d\u5e72\u9884,\u53ea\u901a\u77e5) - \u7ea7\u522b2:\u9650\u5236\u5f00\u4ed3(\u53ea\u5141\u8bb8\u5e73\u4ed3,\u4e0d\u5141\u8bb8\u5f00\u4ed3"
+    },
+    {
+      "label": "__init__.py",
+      "file_type": "code",
+      "source_file": "guanyu-risk/realtime-system/src/__init__.py",
+      "source_location": "L1",
+      "id": "guanyu_risk_realtime_system_src_init_py",
+      "community": 515,
+      "norm_label": "__init__.py"
+    },
+    {
+      "label": "\u5b9e\u65f6\u98ce\u63a7\u7cfb\u7edf - \u5bfc\u51fa\u63a5\u53e3 ============  \u4f7f\u7528\u793a\u4f8b\uff1a  ```python from realtime_system import Realtim",
+      "file_type": "rationale",
+      "source_file": "guanyu-risk/realtime-system/src/__init__.py",
+      "source_location": "L1",
+      "id": "src_init_rationale_1",
+      "community": 515,
+      "norm_label": "\u5b9e\u65f6\u98ce\u63a7\u7cfb\u7edf - \u5bfc\u51fa\u63a5\u53e3 ============  \u4f7f\u7528\u793a\u4f8b:  ```python from realtime_system import realtim"
+    },
+    {
+      "label": "structural_market_risk.py",
+      "file_type": "code",
+      "source_file": "guanyu-risk/common/structural_market_risk.py",
+      "source_location": "L1",
+      "id": "guanyu_risk_common_structural_market_risk_py",
+      "community": 124,
+      "norm_label": "structural_market_risk.py"
+    },
+    {
+      "label": "SectorInfo",
+      "file_type": "code",
+      "source_file": "guanyu-risk/common/structural_market_risk.py",
+      "source_location": "L18",
+      "id": "common_structural_market_risk_sectorinfo",
+      "community": 124,
+      "norm_label": "sectorinfo"
+    },
+    {
+      "label": "StructuredMarketTiming",
+      "file_type": "code",
+      "source_file": "guanyu-risk/common/structural_market_risk.py",
+      "source_location": "L28",
+      "id": "common_structural_market_risk_structuredmarkettiming",
+      "community": 124,
+      "norm_label": "structuredmarkettiming"
+    },
+    {
+      "label": ".__init__()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/common/structural_market_risk.py",
+      "source_location": "L31",
+      "id": "common_structural_market_risk_structuredmarkettiming_init",
+      "community": 124,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": ".timing_sector()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/common/structural_market_risk.py",
+      "source_location": "L41",
+      "id": "common_structural_market_risk_structuredmarkettiming_timing_sector",
+      "community": 124,
+      "norm_label": ".timing_sector()"
+    },
+    {
+      "label": "SectorConcentrationRisk",
+      "file_type": "code",
+      "source_file": "guanyu-risk/common/structural_market_risk.py",
+      "source_location": "L79",
+      "id": "common_structural_market_risk_sectorconcentrationrisk",
+      "community": 124,
+      "norm_label": "sectorconcentrationrisk"
+    },
+    {
+      "label": ".__init__()",
+      "file_type": "code",
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+      "source_location": "L90",
+      "id": "common_structural_market_risk_sectorconcentrationrisk_check_concentration",
+      "community": 124,
+      "norm_label": ".check_concentration()"
+    },
+    {
+      "label": "HotSectorNewsRiskAdjust",
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+      "id": "common_news_risk_monitor_stocknewsdata",
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+      "id": "common_news_risk_monitor_newsriskresult",
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+      "norm_label": "newsriskresult"
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+      "label": "PriceVolumeMonitor",
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+      "source_file": "guanyu-risk/common/news_risk_monitor.py",
+      "source_location": "L91",
+      "id": "common_news_risk_monitor_pricevolumemonitor",
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+      "norm_label": ".__init__()"
+    },
+    {
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+      "source_location": "L102",
+      "id": "common_news_risk_monitor_pricevolumemonitor_analyze",
+      "community": 4,
+      "norm_label": ".analyze()"
+    },
+    {
+      "label": "FinanceMonitor",
+      "file_type": "code",
+      "source_file": "guanyu-risk/common/news_risk_monitor.py",
+      "source_location": "L137",
+      "id": "common_news_risk_monitor_financemonitor",
+      "community": 4,
+      "norm_label": "financemonitor"
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+      "norm_label": ".__init__()"
+    },
+    {
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+      "source_location": "L146",
+      "id": "common_news_risk_monitor_financemonitor_analyze",
+      "community": 4,
+      "norm_label": ".analyze()"
+    },
+    {
+      "label": "InstitutionalMonitor",
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+      "source_file": "guanyu-risk/common/news_risk_monitor.py",
+      "source_location": "L167",
+      "id": "common_news_risk_monitor_institutionalmonitor",
+      "community": 4,
+      "norm_label": "institutionalmonitor"
+    },
+    {
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+      "source_file": "guanyu-risk/common/news_risk_monitor.py",
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+      "id": "common_news_risk_monitor_institutionalmonitor_init",
+      "community": 4,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": ".analyze()",
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+      "source_file": "guanyu-risk/common/news_risk_monitor.py",
+      "source_location": "L174",
+      "id": "common_news_risk_monitor_institutionalmonitor_analyze",
+      "community": 4,
+      "norm_label": ".analyze()"
+    },
+    {
+      "label": "SentimentMonitor",
+      "file_type": "code",
+      "source_file": "guanyu-risk/common/news_risk_monitor.py",
+      "source_location": "L194",
+      "id": "common_news_risk_monitor_sentimentmonitor",
+      "community": 4,
+      "norm_label": "sentimentmonitor"
+    },
+    {
+      "label": ".__init__()",
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+      "source_file": "guanyu-risk/common/news_risk_monitor.py",
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+      "norm_label": ".__init__()"
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+    {
+      "label": ".analyze()",
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+      "source_location": "L203",
+      "id": "common_news_risk_monitor_sentimentmonitor_analyze",
+      "community": 4,
+      "norm_label": ".analyze()"
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+    {
+      "label": "InternationalLinkageMonitor",
+      "file_type": "code",
+      "source_file": "guanyu-risk/common/news_risk_monitor.py",
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+      "id": "common_news_risk_monitor_internationallinkagemonitor",
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+      "source_file": "guanyu-risk/common/news_risk_monitor.py",
+      "source_location": "L235",
+      "id": "common_news_risk_monitor_internationallinkagemonitor_analyze",
+      "community": 4,
+      "norm_label": ".analyze()"
+    },
+    {
+      "label": "StructuralMarketRisk",
+      "file_type": "code",
+      "source_file": "guanyu-risk/common/news_risk_monitor.py",
+      "source_location": "L274",
+      "id": "common_news_risk_monitor_structuralmarketrisk",
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+      "norm_label": "structuralmarketrisk"
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+      "source_file": "guanyu-risk/common/news_risk_monitor.py",
+      "source_location": "L281",
+      "id": "common_news_risk_monitor_structuralmarketrisk_init",
+      "community": 4,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": ".analyze_sector_risk()",
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+      "source_file": "guanyu-risk/common/news_risk_monitor.py",
+      "source_location": "L289",
+      "id": "common_news_risk_monitor_structuralmarketrisk_analyze_sector_risk",
+      "community": 4,
+      "norm_label": ".analyze_sector_risk()"
+    },
+    {
+      "label": ".adjust_news_risk_for_hot_sector()",
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+      "source_file": "guanyu-risk/common/news_risk_monitor.py",
+      "source_location": "L316",
+      "id": "common_news_risk_monitor_structuralmarketrisk_adjust_news_risk_for_hot_sector",
+      "community": 4,
+      "norm_label": ".adjust_news_risk_for_hot_sector()"
+    },
+    {
+      "label": "StyleConcentrationRisk",
+      "file_type": "code",
+      "source_file": "guanyu-risk/common/news_risk_monitor.py",
+      "source_location": "L324",
+      "id": "common_news_risk_monitor_styleconcentrationrisk",
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+      "source_file": "guanyu-risk/common/news_risk_monitor.py",
+      "source_location": "L327",
+      "id": "common_news_risk_monitor_styleconcentrationrisk_init",
+      "community": 4,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": ".analyze_style_risk()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/common/news_risk_monitor.py",
+      "source_location": "L330",
+      "id": "common_news_risk_monitor_styleconcentrationrisk_analyze_style_risk",
+      "community": 4,
+      "norm_label": ".analyze_style_risk()"
+    },
+    {
+      "label": "NewsRiskMonitor",
+      "file_type": "code",
+      "source_file": "guanyu-risk/common/news_risk_monitor.py",
+      "source_location": "L344",
+      "id": "common_news_risk_monitor_newsriskmonitor",
+      "community": 4,
+      "norm_label": "newsriskmonitor"
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+    },
+    {
+      "label": ".analyze_stock()",
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+      "source_location": "L355",
+      "id": "common_news_risk_monitor_newsriskmonitor_analyze_stock",
+      "community": 4,
+      "norm_label": ".analyze_stock()"
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+    {
+      "label": ".analyze_stocks()",
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+      "source_location": "L423",
+      "id": "common_news_risk_monitor_newsriskmonitor_analyze_stocks",
+      "community": 4,
+      "norm_label": ".analyze_stocks()"
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+    {
+      "label": "._get_suggestion()",
+      "file_type": "code",
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+      "id": "common_news_risk_monitor_newsriskmonitor_get_suggestion",
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+      "label": ".get_risk_report()",
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+      "source_location": "L444",
+      "id": "common_news_risk_monitor_newsriskmonitor_get_risk_report",
+      "community": 4,
+      "norm_label": ".get_risk_report()"
+    },
+    {
+      "label": ".get_risk_score_for_risk_system()",
+      "file_type": "code",
+      "source_file": "guanyu-risk/common/news_risk_monitor.py",
+      "source_location": "L484",
+      "id": "common_news_risk_monitor_newsriskmonitor_get_risk_score_for_risk_system",
+      "community": 4,
+      "norm_label": ".get_risk_score_for_risk_system()"
+    },
+    {
+      "label": "FiveDimensionRiskAssessment",
+      "file_type": "code",
+      "source_file": "guanyu-risk/common/news_risk_monitor.py",
+      "source_location": "L493",
+      "id": "common_news_risk_monitor_fivedimensionriskassessment",
+      "community": 4,
+      "norm_label": "fivedimensionriskassessment"
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+      "label": ".calculate_total_risk()",
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+      "source_location": "L502",
+      "id": "common_news_risk_monitor_fivedimensionriskassessment_calculate_total_risk",
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+      "label": "._get_level()",
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+    {
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+    {
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+      "source_location": "L357",
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+      "community": 60,
+      "norm_label": ".check_data_accuracy()"
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+    {
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+      "source_file": "zhaoyun-data/scripts/data_quality/data_quality_manager.py",
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+      "norm_label": "._check_daily_accuracy()"
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+    {
+      "label": "._check_financial_accuracy()",
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+      "source_file": "zhaoyun-data/scripts/data_quality/data_quality_manager.py",
+      "source_location": "L434",
+      "id": "data_quality_data_quality_manager_astockdataqualitymanager_check_financial_accuracy",
+      "community": 60,
+      "norm_label": "._check_financial_accuracy()"
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+    {
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+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_quality/data_quality_manager.py",
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+      "community": 60,
+      "norm_label": ".run_quality_checks()"
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+    {
+      "label": "._save_quality_report()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_quality/data_quality_manager.py",
+      "source_location": "L529",
+      "id": "data_quality_data_quality_manager_astockdataqualitymanager_save_quality_report",
+      "community": 60,
+      "norm_label": "._save_quality_report()"
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+    {
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+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_quality/data_quality_manager.py",
+      "source_location": "L569",
+      "id": "data_quality_data_quality_manager_astockdataqualitymanager_run_update_check",
+      "community": 60,
+      "norm_label": ".run_update_check()"
+    },
+    {
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+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_quality/data_quality_manager.py",
+      "source_location": "L639",
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+      "community": 60,
+      "norm_label": "main()"
+    },
+    {
+      "label": "\u52a0\u8f7d\u914d\u7f6e                  Returns:             Dict: \u914d\u7f6e\u4fe1\u606f",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_quality/data_quality_manager.py",
+      "source_location": "L58",
+      "id": "data_quality_data_quality_manager_rationale_58",
+      "community": 60,
+      "norm_label": "\u52a0\u8f7d\u914d\u7f6e                  returns:             dict: \u914d\u7f6e\u4fe1\u606f"
+    },
+    {
+      "label": "\u4fdd\u5b58\u914d\u7f6e                  Args:             config: \u914d\u7f6e\u4fe1\u606f",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_quality/data_quality_manager.py",
+      "source_location": "L130",
+      "id": "data_quality_data_quality_manager_rationale_130",
+      "community": 60,
+      "norm_label": "\u4fdd\u5b58\u914d\u7f6e                  args:             config: \u914d\u7f6e\u4fe1\u606f"
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+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_quality/data_quality_manager.py",
+      "source_location": "L144",
+      "id": "data_quality_data_quality_manager_rationale_144",
+      "community": 60,
+      "norm_label": "\u68c0\u67e5\u6570\u636e\u5b8c\u6574\u6027                  args:             data_type: \u6570\u636e\u7c7b\u578b(daily, financial, inf"
+    },
+    {
+      "label": "\u68c0\u67e5\u65e5\u7ebf\u6570\u636e\u5b8c\u6574\u6027                  Args:             data_path: \u65e5\u7ebf\u6570\u636e\u8def\u5f84",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_quality/data_quality_manager.py",
+      "source_location": "L211",
+      "id": "data_quality_data_quality_manager_rationale_211",
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+      "norm_label": "\u68c0\u67e5\u65e5\u7ebf\u6570\u636e\u5b8c\u6574\u6027                  args:             data_path: \u65e5\u7ebf\u6570\u636e\u8def\u5f84"
+    },
+    {
+      "label": "\u68c0\u67e5\u8d22\u52a1\u6570\u636e\u5b8c\u6574\u6027                  Args:             data_path: \u8d22\u52a1\u6570\u636e\u8def\u5f84",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_quality/data_quality_manager.py",
+      "source_location": "L271",
+      "id": "data_quality_data_quality_manager_rationale_271",
+      "community": 60,
+      "norm_label": "\u68c0\u67e5\u8d22\u52a1\u6570\u636e\u5b8c\u6574\u6027                  args:             data_path: \u8d22\u52a1\u6570\u636e\u8def\u5f84"
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+    {
+      "label": "\u68c0\u67e5\u57fa\u7840\u4fe1\u606f\u5b8c\u6574\u6027                  Args:             data_path: \u57fa\u7840\u4fe1\u606f\u8def\u5f84",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_quality/data_quality_manager.py",
+      "source_location": "L299",
+      "id": "data_quality_data_quality_manager_rationale_299",
+      "community": 60,
+      "norm_label": "\u68c0\u67e5\u57fa\u7840\u4fe1\u606f\u5b8c\u6574\u6027                  args:             data_path: \u57fa\u7840\u4fe1\u606f\u8def\u5f84"
+    },
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+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_quality/data_quality_manager.py",
+      "source_location": "L327",
+      "id": "data_quality_data_quality_manager_rationale_327",
+      "community": 60,
+      "norm_label": "\u83b7\u53d6\u80a1\u7968\u4ee3\u7801\u5217\u8868                  args:             info_path: \u57fa\u7840\u4fe1\u606f\u8def\u5f84"
+    },
+    {
+      "label": "\u68c0\u67e5\u6570\u636e\u51c6\u786e\u6027                  Args:             data_type: \u6570\u636e\u7c7b\u578b",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_quality/data_quality_manager.py",
+      "source_location": "L358",
+      "id": "data_quality_data_quality_manager_rationale_358",
+      "community": 60,
+      "norm_label": "\u68c0\u67e5\u6570\u636e\u51c6\u786e\u6027                  args:             data_type: \u6570\u636e\u7c7b\u578b"
+    },
+    {
+      "label": "\u68c0\u67e5\u65e5\u7ebf\u6570\u636e\u51c6\u786e\u6027                  Returns:             Dict: \u51c6\u786e\u6027\u68c0\u67e5\u7ed3\u679c",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_quality/data_quality_manager.py",
+      "source_location": "L412",
+      "id": "data_quality_data_quality_manager_rationale_412",
+      "community": 60,
+      "norm_label": "\u68c0\u67e5\u65e5\u7ebf\u6570\u636e\u51c6\u786e\u6027                  returns:             dict: \u51c6\u786e\u6027\u68c0\u67e5\u7ed3\u679c"
+    },
+    {
+      "label": "\u68c0\u67e5\u8d22\u52a1\u6570\u636e\u51c6\u786e\u6027                  Returns:             Dict: \u51c6\u786e\u6027\u68c0\u67e5\u7ed3\u679c",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_quality/data_quality_manager.py",
+      "source_location": "L435",
+      "id": "data_quality_data_quality_manager_rationale_435",
+      "community": 60,
+      "norm_label": "\u68c0\u67e5\u8d22\u52a1\u6570\u636e\u51c6\u786e\u6027                  returns:             dict: \u51c6\u786e\u6027\u68c0\u67e5\u7ed3\u679c"
+    },
+    {
+      "label": "\u8fd0\u884c\u6240\u6709\u8d28\u91cf\u68c0\u67e5                  Returns:             Dict: \u7efc\u5408\u8d28\u91cf\u68c0\u67e5\u7ed3\u679c",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_quality/data_quality_manager.py",
+      "source_location": "L458",
+      "id": "data_quality_data_quality_manager_rationale_458",
+      "community": 60,
+      "norm_label": "\u8fd0\u884c\u6240\u6709\u8d28\u91cf\u68c0\u67e5                  returns:             dict: \u7efc\u5408\u8d28\u91cf\u68c0\u67e5\u7ed3\u679c"
+    },
+    {
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+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_quality/data_quality_manager.py",
+      "source_location": "L530",
+      "id": "data_quality_data_quality_manager_rationale_530",
+      "community": 60,
+      "norm_label": "\u4fdd\u5b58\u8d28\u91cf\u68c0\u67e5\u62a5\u544a                  args:             results: \u8d28\u91cf\u68c0\u67e5\u7ed3\u679c"
+    },
+    {
+      "label": "\u8fd0\u884c\u6570\u636e\u66f4\u65b0\u68c0\u67e5                  Returns:             Dict: \u66f4\u65b0\u68c0\u67e5\u7ed3\u679c",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_quality/data_quality_manager.py",
+      "source_location": "L570",
+      "id": "data_quality_data_quality_manager_rationale_570",
+      "community": 60,
+      "norm_label": "\u8fd0\u884c\u6570\u636e\u66f4\u65b0\u68c0\u67e5                  returns:             dict: \u66f4\u65b0\u68c0\u67e5\u7ed3\u679c"
+    },
+    {
+      "label": "run_basic_info_quality_check.py",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_quality/run_basic_info_quality_check.py",
+      "source_location": "L1",
+      "id": "zhaoyun_data_scripts_data_quality_run_basic_info_quality_check_py",
+      "community": 529,
+      "norm_label": "run_basic_info_quality_check.py"
+    },
+    {
+      "label": "nas_config_check.py",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/nas_deployment/nas_config_check.py",
+      "source_location": "L1",
+      "id": "zhaoyun_data_scripts_nas_deployment_nas_config_check_py",
+      "community": 446,
+      "norm_label": "nas_config_check.py"
+    },
+    {
+      "label": "__init__()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/nas_deployment/nas_config_check.py",
+      "source_location": "L29",
+      "id": "nas_deployment_nas_config_check_init",
+      "community": 446,
+      "norm_label": "__init__()"
+    },
+    {
+      "label": "create_config_template()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/nas_deployment/nas_config_check.py",
+      "source_location": "L70",
+      "id": "nas_deployment_nas_config_check_create_config_template",
+      "community": 446,
+      "norm_label": "create_config_template()"
+    },
+    {
+      "label": "check_vpn_connectivity()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/nas_deployment/nas_config_check.py",
+      "source_location": "L103",
+      "id": "nas_deployment_nas_config_check_check_vpn_connectivity",
+      "community": 446,
+      "norm_label": "check_vpn_connectivity()"
+    },
+    {
+      "label": "nas_temp_config.py",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/nas_deployment/nas_temp_config.py",
+      "source_location": "L1",
+      "id": "zhaoyun_data_scripts_nas_deployment_nas_temp_config_py",
+      "community": 530,
+      "norm_label": "nas_temp_config.py"
+    },
+    {
+      "label": "simple_temp_setup.py",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/nas_deployment/simple_temp_setup.py",
+      "source_location": "L1",
+      "id": "zhaoyun_data_scripts_nas_deployment_simple_temp_setup_py",
+      "community": 531,
+      "norm_label": "simple_temp_setup.py"
+    },
+    {
+      "label": "start_minute_download.py",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/nas_deployment/start_minute_download.py",
+      "source_location": "L1",
+      "id": "zhaoyun_data_scripts_nas_deployment_start_minute_download_py",
+      "community": 532,
+      "norm_label": "start_minute_download.py"
+    },
+    {
+      "label": "quick_vpn_test.py",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/nas_deployment/quick_vpn_test.py",
+      "source_location": "L1",
+      "id": "zhaoyun_data_scripts_nas_deployment_quick_vpn_test_py",
+      "community": 533,
+      "norm_label": "quick_vpn_test.py"
+    },
+    {
+      "label": "test_nas_vpn.py",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/nas_deployment/test_nas_vpn.py",
+      "source_location": "L1",
+      "id": "zhaoyun_data_scripts_nas_deployment_test_nas_vpn_py",
+      "community": 385,
+      "norm_label": "test_nas_vpn.py"
+    },
+    {
+      "label": "NASVPNTester",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/nas_deployment/test_nas_vpn.py",
+      "source_location": "L18",
+      "id": "nas_deployment_test_nas_vpn_nasvpntester",
+      "community": 385,
+      "norm_label": "nasvpntester"
+    },
+    {
+      "label": ".test_nas_connection()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/nas_deployment/test_nas_vpn.py",
+      "source_location": "L21",
+      "id": "nas_deployment_test_nas_vpn_nasvpntester_test_nas_connection",
+      "community": 385,
+      "norm_label": ".test_nas_connection()"
+    },
+    {
+      "label": ".test_vpn_connectivity()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/nas_deployment/test_nas_vpn.py",
+      "source_location": "L77",
+      "id": "nas_deployment_test_nas_vpn_nasvpntester_test_vpn_connectivity",
+      "community": 385,
+      "norm_label": ".test_vpn_connectivity()"
+    },
+    {
+      "label": "main()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/nas_deployment/test_nas_vpn.py",
+      "source_location": "L152",
+      "id": "nas_deployment_test_nas_vpn_main",
+      "community": 385,
+      "norm_label": "main()"
+    },
+    {
+      "label": "vnpy_github_crawler.py",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/github_crawler/vnpy_github_crawler.py",
+      "source_location": "L1",
+      "id": "zhaoyun_data_scripts_github_crawler_vnpy_github_crawler_py",
+      "community": 170,
+      "norm_label": "vnpy_github_crawler.py"
+    },
+    {
+      "label": "VNPYGitHubCrawler",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/github_crawler/vnpy_github_crawler.py",
+      "source_location": "L29",
+      "id": "github_crawler_vnpy_github_crawler_vnpygithubcrawler",
+      "community": 170,
+      "norm_label": "vnpygithubcrawler"
+    },
+    {
+      "label": ".__init__()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/github_crawler/vnpy_github_crawler.py",
+      "source_location": "L32",
+      "id": "github_crawler_vnpy_github_crawler_vnpygithubcrawler_init",
+      "community": 170,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": ".get_all_repos()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/github_crawler/vnpy_github_crawler.py",
+      "source_location": "L60",
+      "id": "github_crawler_vnpy_github_crawler_vnpygithubcrawler_get_all_repos",
+      "community": 170,
+      "norm_label": ".get_all_repos()"
+    },
+    {
+      "label": ".save_repo_list()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/github_crawler/vnpy_github_crawler.py",
+      "source_location": "L116",
+      "id": "github_crawler_vnpy_github_crawler_vnpygithubcrawler_save_repo_list",
+      "community": 170,
+      "norm_label": ".save_repo_list()"
+    },
+    {
+      "label": ".get_readme_content()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/github_crawler/vnpy_github_crawler.py",
+      "source_location": "L142",
+      "id": "github_crawler_vnpy_github_crawler_vnpygithubcrawler_get_readme_content",
+      "community": 170,
+      "norm_label": ".get_readme_content()"
+    },
+    {
+      "label": ".clone_repo_source()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/github_crawler/vnpy_github_crawler.py",
+      "source_location": "L168",
+      "id": "github_crawler_vnpy_github_crawler_vnpygithubcrawler_clone_repo_source",
+      "community": 170,
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+    {
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+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/github_crawler/vnpy_github_crawler.py",
+      "source_location": "L194",
+      "id": "github_crawler_vnpy_github_crawler_vnpygithubcrawler_save_readme",
+      "community": 170,
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+    },
+    {
+      "label": ".save_repo_info()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/github_crawler/vnpy_github_crawler.py",
+      "source_location": "L203",
+      "id": "github_crawler_vnpy_github_crawler_vnpygithubcrawler_save_repo_info",
+      "community": 170,
+      "norm_label": ".save_repo_info()"
+    },
+    {
+      "label": ".crawl_all_repos()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/github_crawler/vnpy_github_crawler.py",
+      "source_location": "L210",
+      "id": "github_crawler_vnpy_github_crawler_vnpygithubcrawler_crawl_all_repos",
+      "community": 170,
+      "norm_label": ".crawl_all_repos()"
+    },
+    {
+      "label": ".generate_index()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/github_crawler/vnpy_github_crawler.py",
+      "source_location": "L292",
+      "id": "github_crawler_vnpy_github_crawler_vnpygithubcrawler_generate_index",
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+      "norm_label": ".generate_index()"
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+    {
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+      "norm_label": "main()"
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+    {
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+      "source_location": "L1",
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+      "community": 36,
+      "norm_label": "akshare_vnpy_adapter.py"
+    },
+    {
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+    {
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+      "norm_label": ".__init__()"
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+    {
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+      "source_location": "L44",
+      "id": "common_tools_akshare_vnpy_adapter_aksharedataadapter_load_config",
+      "community": 36,
+      "norm_label": "._load_config()"
+    },
+    {
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+      "source_location": "L103",
+      "id": "common_tools_akshare_vnpy_adapter_aksharedataadapter_get_stock_daily",
+      "community": 36,
+      "norm_label": ".get_stock_daily()"
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+    {
+      "label": "._generate_mock_stock_data()",
+      "file_type": "code",
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+      "community": 36,
+      "norm_label": "._generate_mock_stock_data()"
+    },
+    {
+      "label": "._convert_to_vnpy_format()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/common_tools/akshare_vnpy_adapter.py",
+      "source_location": "L173",
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+      "norm_label": "._convert_to_vnpy_format()"
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+    {
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+      "community": 36,
+      "norm_label": ".get_index_daily()"
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+    {
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+      "community": 36,
+      "norm_label": "._generate_mock_index_data()"
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+    {
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+      "community": 36,
+      "norm_label": ".export_to_vnpy_csv()"
+    },
+    {
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+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/common_tools/akshare_vnpy_adapter.py",
+      "source_location": "L316",
+      "id": "common_tools_akshare_vnpy_adapter_aksharedataadapter_export_to_vnpy_database",
+      "community": 36,
+      "norm_label": ".export_to_vnpy_database()"
+    },
+    {
+      "label": "main()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/common_tools/akshare_vnpy_adapter.py",
+      "source_location": "L356",
+      "id": "common_tools_akshare_vnpy_adapter_main",
+      "community": 36,
+      "norm_label": "main()"
+    },
+    {
+      "label": "\u521d\u59cb\u5316\u9002\u914d\u5668                  Args:             config_path: \u914d\u7f6e\u6587\u4ef6\u8def\u5f84",
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+      "source_file": "zhaoyun-data/scripts/common_tools/akshare_vnpy_adapter.py",
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+      "source_file": "zhaoyun-data/scripts/common_tools/akshare_vnpy_adapter.py",
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+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/common_tools/akshare_vnpy_adapter.py",
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+      "norm_label": "\u83b7\u53d6\u80a1\u7968\u65e5\u7ebf\u6570\u636e                  args:             symbol: \u80a1\u7968\u4ee3\u7801(\u5982:000001)             s"
+    },
+    {
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+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/common_tools/akshare_vnpy_adapter.py",
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+      "norm_label": "\u751f\u6210\u6a21\u62df\u80a1\u7968\u6570\u636e(\u5f53akshare\u4e0d\u53ef\u7528\u65f6)                  args:             symbol: \u80a1\u7968\u4ee3\u7801"
+    },
+    {
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+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/common_tools/akshare_vnpy_adapter.py",
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+      "norm_label": "\u8f6c\u6362\u4e3avnpy\u683c\u5f0f                  args:             df: \u539f\u59cb\u6570\u636edataframe             data_"
+    },
+    {
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+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/common_tools/akshare_vnpy_adapter.py",
+      "source_location": "L222",
+      "id": "common_tools_akshare_vnpy_adapter_rationale_222",
+      "community": 36,
+      "norm_label": "\u83b7\u53d6\u6307\u6570\u65e5\u7ebf\u6570\u636e                  args:             index_symbol: \u6307\u6570\u4ee3\u7801(\u5982:000001.sh)"
+    },
+    {
+      "label": "\u751f\u6210\u6a21\u62df\u6307\u6570\u6570\u636e                  Args:             index_symbol: \u6307\u6570\u4ee3\u7801             start",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/common_tools/akshare_vnpy_adapter.py",
+      "source_location": "L258",
+      "id": "common_tools_akshare_vnpy_adapter_rationale_258",
+      "community": 36,
+      "norm_label": "\u751f\u6210\u6a21\u62df\u6307\u6570\u6570\u636e                  args:             index_symbol: \u6307\u6570\u4ee3\u7801             start"
+    },
+    {
+      "label": "\u5bfc\u51fa\u4e3avnPy CSV\u683c\u5f0f                  Args:             df: \u6570\u636eDataFrame             sym",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/common_tools/akshare_vnpy_adapter.py",
+      "source_location": "L286",
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+      "community": 36,
+      "norm_label": "\u5bfc\u51fa\u4e3avnpy csv\u683c\u5f0f                  args:             df: \u6570\u636edataframe             sym"
+    },
+    {
+      "label": "\u5bfc\u51fa\u5230vnPy\u6570\u636e\u5e93\u683c\u5f0f\uff08\u6a21\u62df\uff09                  Args:             df: \u6570\u636eDataFrame",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/common_tools/akshare_vnpy_adapter.py",
+      "source_location": "L317",
+      "id": "common_tools_akshare_vnpy_adapter_rationale_317",
+      "community": 36,
+      "norm_label": "\u5bfc\u51fa\u5230vnpy\u6570\u636e\u5e93\u683c\u5f0f(\u6a21\u62df)                  args:             df: \u6570\u636edataframe"
+    },
+    {
+      "label": "a_stock_basic_info.py",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_basic_info.py",
+      "source_location": "L1",
+      "id": "zhaoyun_data_scripts_data_acquisition_a_stock_basic_info_py",
+      "community": 100,
+      "norm_label": "a_stock_basic_info.py"
+    },
+    {
+      "label": "AStockBasicInfoCollector",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_basic_info.py",
+      "source_location": "L25",
+      "id": "data_acquisition_a_stock_basic_info_astockbasicinfocollector",
+      "community": 100,
+      "norm_label": "astockbasicinfocollector"
+    },
+    {
+      "label": ".__init__()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_basic_info.py",
+      "source_location": "L28",
+      "id": "data_acquisition_a_stock_basic_info_astockbasicinfocollector_init",
+      "community": 100,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": ".collect_basic_info()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_basic_info.py",
+      "source_location": "L46",
+      "id": "data_acquisition_a_stock_basic_info_astockbasicinfocollector_collect_basic_info",
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+      "norm_label": ".collect_basic_info()"
+    },
+    {
+      "label": ".collect_industry_info()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_basic_info.py",
+      "source_location": "L128",
+      "id": "data_acquisition_a_stock_basic_info_astockbasicinfocollector_collect_industry_info",
+      "community": 100,
+      "norm_label": ".collect_industry_info()"
+    },
+    {
+      "label": "._save_raw_data()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_basic_info.py",
+      "source_location": "L174",
+      "id": "data_acquisition_a_stock_basic_info_astockbasicinfocollector_save_raw_data",
+      "community": 100,
+      "norm_label": "._save_raw_data()"
+    },
+    {
+      "label": "._process_basic_info()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_basic_info.py",
+      "source_location": "L203",
+      "id": "data_acquisition_a_stock_basic_info_astockbasicinfocollector_process_basic_info",
+      "community": 100,
+      "norm_label": "._process_basic_info()"
+    },
+    {
+      "label": "._save_processed_data()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_basic_info.py",
+      "source_location": "L274",
+      "id": "data_acquisition_a_stock_basic_info_astockbasicinfocollector_save_processed_data",
+      "community": 100,
+      "norm_label": "._save_processed_data()"
+    },
+    {
+      "label": "._generate_summary()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_basic_info.py",
+      "source_location": "L305",
+      "id": "data_acquisition_a_stock_basic_info_astockbasicinfocollector_generate_summary",
+      "community": 100,
+      "norm_label": "._generate_summary()"
+    },
+    {
+      "label": ".run()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_basic_info.py",
+      "source_location": "L369",
+      "id": "data_acquisition_a_stock_basic_info_astockbasicinfocollector_run",
+      "community": 100,
+      "norm_label": ".run()"
+    },
+    {
+      "label": "main()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_basic_info.py",
+      "source_location": "L427",
+      "id": "data_acquisition_a_stock_basic_info_main",
+      "community": 100,
+      "norm_label": "main()"
+    },
+    {
+      "label": "\u91c7\u96c6A\u80a1\u57fa\u7840\u4fe1\u606f                  Returns:             pd.DataFrame: \u80a1\u7968\u57fa\u7840\u4fe1\u606f\u6570\u636e",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_basic_info.py",
+      "source_location": "L47",
+      "id": "data_acquisition_a_stock_basic_info_rationale_47",
+      "community": 100,
+      "norm_label": "\u91c7\u96c6a\u80a1\u57fa\u7840\u4fe1\u606f                  returns:             pd.dataframe: \u80a1\u7968\u57fa\u7840\u4fe1\u606f\u6570\u636e"
+    },
+    {
+      "label": "\u91c7\u96c6\u884c\u4e1a\u5206\u7c7b\u4fe1\u606f                  Returns:             pd.DataFrame: \u884c\u4e1a\u5206\u7c7b\u6570\u636e",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_basic_info.py",
+      "source_location": "L129",
+      "id": "data_acquisition_a_stock_basic_info_rationale_129",
+      "community": 100,
+      "norm_label": "\u91c7\u96c6\u884c\u4e1a\u5206\u7c7b\u4fe1\u606f                  returns:             pd.dataframe: \u884c\u4e1a\u5206\u7c7b\u6570\u636e"
+    },
+    {
+      "label": "\u4fdd\u5b58\u539f\u59cb\u6570\u636e                  Args:             df: \u539f\u59cb\u6570\u636e",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_basic_info.py",
+      "source_location": "L175",
+      "id": "data_acquisition_a_stock_basic_info_rationale_175",
+      "community": 100,
+      "norm_label": "\u4fdd\u5b58\u539f\u59cb\u6570\u636e                  args:             df: \u539f\u59cb\u6570\u636e"
+    },
+    {
+      "label": "\u5904\u7406\u57fa\u7840\u4fe1\u606f\u6570\u636e                  Args:             df: \u539f\u59cb\u6570\u636e                      Return",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_basic_info.py",
+      "source_location": "L204",
+      "id": "data_acquisition_a_stock_basic_info_rationale_204",
+      "community": 100,
+      "norm_label": "\u5904\u7406\u57fa\u7840\u4fe1\u606f\u6570\u636e                  args:             df: \u539f\u59cb\u6570\u636e                      return"
+    },
+    {
+      "label": "\u4fdd\u5b58\u5904\u7406\u540e\u6570\u636e                  Args:             df: \u5904\u7406\u540e\u6570\u636e",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_basic_info.py",
+      "source_location": "L275",
+      "id": "data_acquisition_a_stock_basic_info_rationale_275",
+      "community": 100,
+      "norm_label": "\u4fdd\u5b58\u5904\u7406\u540e\u6570\u636e                  args:             df: \u5904\u7406\u540e\u6570\u636e"
+    },
+    {
+      "label": "\u751f\u6210\u6570\u636e\u6458\u8981                  Args:             df: \u6570\u636e                      Returns:",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_basic_info.py",
+      "source_location": "L306",
+      "id": "data_acquisition_a_stock_basic_info_rationale_306",
+      "community": 100,
+      "norm_label": "\u751f\u6210\u6570\u636e\u6458\u8981                  args:             df: \u6570\u636e                      returns:"
+    },
+    {
+      "label": "\u8fd0\u884c\u91c7\u96c6\u5668                  Returns:             dict: \u91c7\u96c6\u7ed3\u679c",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_basic_info.py",
+      "source_location": "L370",
+      "id": "data_acquisition_a_stock_basic_info_rationale_370",
+      "community": 100,
+      "norm_label": "\u8fd0\u884c\u91c7\u96c6\u5668                  returns:             dict: \u91c7\u96c6\u7ed3\u679c"
+    },
+    {
+      "label": "a_stock_daily_data_downloader.py",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_daily_data_downloader.py",
+      "source_location": "L1",
+      "id": "zhaoyun_data_scripts_data_acquisition_a_stock_daily_data_downloader_py",
+      "community": 138,
+      "norm_label": "a_stock_daily_data_downloader.py"
+    },
+    {
+      "label": "AStockDailyDownloader",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_daily_data_downloader.py",
+      "source_location": "L45",
+      "id": "data_acquisition_a_stock_daily_data_downloader_astockdailydownloader",
+      "community": 138,
+      "norm_label": "astockdailydownloader"
+    },
+    {
+      "label": ".__init__()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_daily_data_downloader.py",
+      "source_location": "L48",
+      "id": "data_acquisition_a_stock_daily_data_downloader_astockdailydownloader_init",
+      "community": 138,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": "._create_directory_structure()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_daily_data_downloader.py",
+      "source_location": "L79",
+      "id": "data_acquisition_a_stock_daily_data_downloader_astockdailydownloader_create_directory_structure",
+      "community": 138,
+      "norm_label": "._create_directory_structure()"
+    },
+    {
+      "label": ".get_all_a_stock_codes()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_daily_data_downloader.py",
+      "source_location": "L95",
+      "id": "data_acquisition_a_stock_daily_data_downloader_astockdailydownloader_get_all_a_stock_codes",
+      "community": 138,
+      "norm_label": ".get_all_a_stock_codes()"
+    },
+    {
+      "label": "._save_stock_list()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_daily_data_downloader.py",
+      "source_location": "L147",
+      "id": "data_acquisition_a_stock_daily_data_downloader_astockdailydownloader_save_stock_list",
+      "community": 138,
+      "norm_label": "._save_stock_list()"
+    },
+    {
+      "label": ".download_stock_daily()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_daily_data_downloader.py",
+      "source_location": "L160",
+      "id": "data_acquisition_a_stock_daily_data_downloader_astockdailydownloader_download_stock_daily",
+      "community": 138,
+      "norm_label": ".download_stock_daily()"
+    },
+    {
+      "label": ".save_stock_data()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_daily_data_downloader.py",
+      "source_location": "L230",
+      "id": "data_acquisition_a_stock_daily_data_downloader_astockdailydownloader_save_stock_data",
+      "community": 138,
+      "norm_label": ".save_stock_data()"
+    },
+    {
+      "label": ".check_already_downloaded()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_daily_data_downloader.py",
+      "source_location": "L261",
+      "id": "data_acquisition_a_stock_daily_data_downloader_astockdailydownloader_check_already_downloaded",
+      "community": 138,
+      "norm_label": ".check_already_downloaded()"
+    },
+    {
+      "label": ".download_all_stocks()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_daily_data_downloader.py",
+      "source_location": "L269",
+      "id": "data_acquisition_a_stock_daily_data_downloader_astockdailydownloader_download_all_stocks",
+      "community": 138,
+      "norm_label": ".download_all_stocks()"
+    },
+    {
+      "label": "._save_download_stats()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_daily_data_downloader.py",
+      "source_location": "L353",
+      "id": "data_acquisition_a_stock_daily_data_downloader_astockdailydownloader_save_download_stats",
+      "community": 138,
+      "norm_label": "._save_download_stats()"
+    },
+    {
+      "label": "._calculate_success_rate()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_daily_data_downloader.py",
+      "source_location": "L360",
+      "id": "data_acquisition_a_stock_daily_data_downloader_astockdailydownloader_calculate_success_rate",
+      "community": 138,
+      "norm_label": "._calculate_success_rate()"
+    },
+    {
+      "label": "._generate_download_report()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_daily_data_downloader.py",
+      "source_location": "L367",
+      "id": "data_acquisition_a_stock_daily_data_downloader_astockdailydownloader_generate_download_report",
+      "community": 138,
+      "norm_label": "._generate_download_report()"
+    },
+    {
+      "label": "main()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_daily_data_downloader.py",
+      "source_location": "L426",
+      "id": "data_acquisition_a_stock_daily_data_downloader_main",
+      "community": 138,
+      "norm_label": "main()"
+    },
+    {
+      "label": "test_nas_environment.py",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/test_nas_environment.py",
+      "source_location": "L1",
+      "id": "zhaoyun_data_scripts_data_acquisition_test_nas_environment_py",
+      "community": 534,
+      "norm_label": "test_nas_environment.py"
+    },
+    {
+      "label": "minute_kline_collector.py",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/minute_kline_collector.py",
+      "source_location": "L1",
+      "id": "zhaoyun_data_scripts_data_acquisition_minute_kline_collector_py",
+      "community": 97,
+      "norm_label": "minute_kline_collector.py"
+    },
+    {
+      "label": "TimeFrame",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/minute_kline_collector.py",
+      "source_location": "L30",
+      "id": "data_acquisition_minute_kline_collector_timeframe",
+      "community": 89,
+      "norm_label": "timeframe"
+    },
+    {
+      "label": "DownloadConfig",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/minute_kline_collector.py",
+      "source_location": "L40",
+      "id": "data_acquisition_minute_kline_collector_downloadconfig",
+      "community": 97,
+      "norm_label": "downloadconfig"
+    },
+    {
+      "label": "MinuteKlineCollector",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/minute_kline_collector.py",
+      "source_location": "L51",
+      "id": "data_acquisition_minute_kline_collector_minuteklinecollector",
+      "community": 97,
+      "norm_label": "minuteklinecollector"
+    },
+    {
+      "label": ".__init__()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/minute_kline_collector.py",
+      "source_location": "L54",
+      "id": "data_acquisition_minute_kline_collector_minuteklinecollector_init",
+      "community": 97,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": ".test_environment()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/minute_kline_collector.py",
+      "source_location": "L97",
+      "id": "data_acquisition_minute_kline_collector_minuteklinecollector_test_environment",
+      "community": 97,
+      "norm_label": ".test_environment()"
+    },
+    {
+      "label": ".test_data_source()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/minute_kline_collector.py",
+      "source_location": "L161",
+      "id": "data_acquisition_minute_kline_collector_minuteklinecollector_test_data_source",
+      "community": 97,
+      "norm_label": ".test_data_source()"
+    },
+    {
+      "label": "._validate_data_quality()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/minute_kline_collector.py",
+      "source_location": "L272",
+      "id": "data_acquisition_minute_kline_collector_minuteklinecollector_validate_data_quality",
+      "community": 97,
+      "norm_label": "._validate_data_quality()"
+    },
+    {
+      "label": ".download_single_stock()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/minute_kline_collector.py",
+      "source_location": "L368",
+      "id": "data_acquisition_minute_kline_collector_minuteklinecollector_download_single_stock",
+      "community": 97,
+      "norm_label": ".download_single_stock()"
+    },
+    {
+      "label": ".batch_download_stocks()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/minute_kline_collector.py",
+      "source_location": "L447",
+      "id": "data_acquisition_minute_kline_collector_minuteklinecollector_batch_download_stocks",
+      "community": 97,
+      "norm_label": ".batch_download_stocks()"
+    },
+    {
+      "label": ".save_download_report()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/minute_kline_collector.py",
+      "source_location": "L580",
+      "id": "data_acquisition_minute_kline_collector_minuteklinecollector_save_download_report",
+      "community": 97,
+      "norm_label": ".save_download_report()"
+    },
+    {
+      "label": "main()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/minute_kline_collector.py",
+      "source_location": "L603",
+      "id": "data_acquisition_minute_kline_collector_main",
+      "community": 97,
+      "norm_label": "main()"
+    },
+    {
+      "label": "\u521d\u59cb\u5316\u6536\u96c6\u5668                  Args:             base_dir: \u57fa\u7840\u76ee\u5f55\uff08\u7528\u4e8e\u6d4b\u8bd5\uff0cNAS\u5c31\u7eea\u540e\u4fee\u6539\uff09",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/minute_kline_collector.py",
+      "source_location": "L55",
+      "id": "data_acquisition_minute_kline_collector_rationale_55",
+      "community": 97,
+      "norm_label": "\u521d\u59cb\u5316\u6536\u96c6\u5668                  args:             base_dir: \u57fa\u7840\u76ee\u5f55(\u7528\u4e8e\u6d4b\u8bd5,nas\u5c31\u7eea\u540e\u4fee\u6539)"
+    },
+    {
+      "label": "\u6d4b\u8bd5\u73af\u5883\u914d\u7f6e                  Returns:             Dict[str, bool]: \u73af\u5883\u6d4b\u8bd5\u7ed3\u679c",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/minute_kline_collector.py",
+      "source_location": "L98",
+      "id": "data_acquisition_minute_kline_collector_rationale_98",
+      "community": 97,
+      "norm_label": "\u6d4b\u8bd5\u73af\u5883\u914d\u7f6e                  returns:             dict[str, bool]: \u73af\u5883\u6d4b\u8bd5\u7ed3\u679c"
+    },
+    {
+      "label": "\u6d4b\u8bd5\u6570\u636e\u6e90\u53ef\u7528\u6027                  Returns:             Dict[str, Any]: \u6570\u636e\u6e90\u6d4b\u8bd5\u7ed3\u679c",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/minute_kline_collector.py",
+      "source_location": "L162",
+      "id": "data_acquisition_minute_kline_collector_rationale_162",
+      "community": 97,
+      "norm_label": "\u6d4b\u8bd5\u6570\u636e\u6e90\u53ef\u7528\u6027                  returns:             dict[str, any]: \u6570\u636e\u6e90\u6d4b\u8bd5\u7ed3\u679c"
+    },
+    {
+      "label": "\u9a8c\u8bc1\u6570\u636e\u8d28\u91cf                  Args:             data: \u6570\u636e             timeframe: \u65f6\u95f4\u7c92\u5ea6",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/minute_kline_collector.py",
+      "source_location": "L273",
+      "id": "data_acquisition_minute_kline_collector_rationale_273",
+      "community": 97,
+      "norm_label": "\u9a8c\u8bc1\u6570\u636e\u8d28\u91cf                  args:             data: \u6570\u636e             timeframe: \u65f6\u95f4\u7c92\u5ea6"
+    },
+    {
+      "label": "\u4e0b\u8f7d\u5355\u53ea\u80a1\u7968\u7684\u5206\u949f\u6570\u636e                  Args:             config: \u4e0b\u8f7d\u914d\u7f6e",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/minute_kline_collector.py",
+      "source_location": "L369",
+      "id": "data_acquisition_minute_kline_collector_rationale_369",
+      "community": 97,
+      "norm_label": "\u4e0b\u8f7d\u5355\u53ea\u80a1\u7968\u7684\u5206\u949f\u6570\u636e                  args:             config: \u4e0b\u8f7d\u914d\u7f6e"
+    },
+    {
+      "label": "\u6279\u91cf\u4e0b\u8f7d\u80a1\u7968\u6570\u636e                  Args:             symbols: \u80a1\u7968\u4ee3\u7801\u5217\u8868             timefram",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/minute_kline_collector.py",
+      "source_location": "L454",
+      "id": "data_acquisition_minute_kline_collector_rationale_454",
+      "community": 97,
+      "norm_label": "\u6279\u91cf\u4e0b\u8f7d\u80a1\u7968\u6570\u636e                  args:             symbols: \u80a1\u7968\u4ee3\u7801\u5217\u8868             timefram"
+    },
+    {
+      "label": "\u4fdd\u5b58\u4e0b\u8f7d\u62a5\u544a                  Args:             result: \u4e0b\u8f7d\u7ed3\u679c             report_dir: \u62a5",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/minute_kline_collector.py",
+      "source_location": "L581",
+      "id": "data_acquisition_minute_kline_collector_rationale_581",
+      "community": 97,
+      "norm_label": "\u4fdd\u5b58\u4e0b\u8f7d\u62a5\u544a                  args:             result: \u4e0b\u8f7d\u7ed3\u679c             report_dir: \u62a5"
+    },
+    {
+      "label": "batch_downloader.py",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/batch_downloader.py",
+      "source_location": "L1",
+      "id": "zhaoyun_data_scripts_data_acquisition_batch_downloader_py",
+      "community": 171,
+      "norm_label": "batch_downloader.py"
+    },
+    {
+      "label": "BatchDownloader",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/batch_downloader.py",
+      "source_location": "L13",
+      "id": "data_acquisition_batch_downloader_batchdownloader",
+      "community": 171,
+      "norm_label": "batchdownloader"
+    },
+    {
+      "label": ".__init__()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/batch_downloader.py",
+      "source_location": "L16",
+      "id": "data_acquisition_batch_downloader_batchdownloader_init",
+      "community": 171,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": ".download_jq_articles()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/batch_downloader.py",
+      "source_location": "L33",
+      "id": "data_acquisition_batch_downloader_batchdownloader_download_jq_articles",
+      "community": 171,
+      "norm_label": ".download_jq_articles()"
+    },
+    {
+      "label": "._parse_jq_article()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/batch_downloader.py",
+      "source_location": "L87",
+      "id": "data_acquisition_batch_downloader_batchdownloader_parse_jq_article",
+      "community": 171,
+      "norm_label": "._parse_jq_article()"
+    },
+    {
+      "label": ".download_financial_data()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/batch_downloader.py",
+      "source_location": "L107",
+      "id": "data_acquisition_batch_downloader_batchdownloader_download_financial_data",
+      "community": 171,
+      "norm_label": ".download_financial_data()"
+    },
+    {
+      "label": ".resume_download()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/batch_downloader.py",
+      "source_location": "L152",
+      "id": "data_acquisition_batch_downloader_batchdownloader_resume_download",
+      "community": 171,
+      "norm_label": ".resume_download()"
+    },
+    {
+      "label": "main()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/batch_downloader.py",
+      "source_location": "L198",
+      "id": "data_acquisition_batch_downloader_main",
+      "community": 171,
+      "norm_label": "main()"
+    },
+    {
+      "label": "\u4e0b\u8f7d\u805a\u5bbd\u6587\u7ae0                  Args:             article_links: \u6587\u7ae0\u94fe\u63a5\u5217\u8868             dela",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/batch_downloader.py",
+      "source_location": "L34",
+      "id": "data_acquisition_batch_downloader_rationale_34",
+      "community": 171,
+      "norm_label": "\u4e0b\u8f7d\u805a\u5bbd\u6587\u7ae0                  args:             article_links: \u6587\u7ae0\u94fe\u63a5\u5217\u8868             dela"
+    },
+    {
+      "label": "\u89e3\u6790\u805a\u5bbd\u6587\u7ae0\u5185\u5bb9                  Args:             html_content: HTML\u5185\u5bb9",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/batch_downloader.py",
+      "source_location": "L88",
+      "id": "data_acquisition_batch_downloader_rationale_88",
+      "community": 171,
+      "norm_label": "\u89e3\u6790\u805a\u5bbd\u6587\u7ae0\u5185\u5bb9                  args:             html_content: html\u5185\u5bb9"
+    },
+    {
+      "label": "\u4e0b\u8f7d\u91d1\u878d\u6570\u636e                  Args:             symbols: \u80a1\u7968\u4ee3\u7801\u5217\u8868             start_date",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/batch_downloader.py",
+      "source_location": "L108",
+      "id": "data_acquisition_batch_downloader_rationale_108",
+      "community": 171,
+      "norm_label": "\u4e0b\u8f7d\u91d1\u878d\u6570\u636e                  args:             symbols: \u80a1\u7968\u4ee3\u7801\u5217\u8868             start_date"
+    },
+    {
+      "label": "\u65ad\u70b9\u7eed\u4f20                  Args:             log_file: \u4e0b\u8f7d\u65e5\u5fd7\u6587\u4ef6                      Re",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/batch_downloader.py",
+      "source_location": "L153",
+      "id": "data_acquisition_batch_downloader_rationale_153",
+      "community": 171,
+      "norm_label": "\u65ad\u70b9\u7eed\u4f20                  args:             log_file: \u4e0b\u8f7d\u65e5\u5fd7\u6587\u4ef6                      re"
+    },
+    {
+      "label": "get_hs300_constituents.py",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/get_hs300_constituents.py",
+      "source_location": "L1",
+      "id": "zhaoyun_data_scripts_data_acquisition_get_hs300_constituents_py",
+      "community": 535,
+      "norm_label": "get_hs300_constituents.py"
+    },
+    {
+      "label": "debug_minute_api.py",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/debug_minute_api.py",
+      "source_location": "L1",
+      "id": "zhaoyun_data_scripts_data_acquisition_debug_minute_api_py",
+      "community": 536,
+      "norm_label": "debug_minute_api.py"
+    },
+    {
+      "label": "a_stock_financial_data_downloader.py",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_financial_data_downloader.py",
+      "source_location": "L1",
+      "id": "zhaoyun_data_scripts_data_acquisition_a_stock_financial_data_downloader_py",
+      "community": 114,
+      "norm_label": "a_stock_financial_data_downloader.py"
+    },
+    {
+      "label": "AStockFinancialDownloader",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_financial_data_downloader.py",
+      "source_location": "L46",
+      "id": "data_acquisition_a_stock_financial_data_downloader_astockfinancialdownloader",
+      "community": 114,
+      "norm_label": "astockfinancialdownloader"
+    },
+    {
+      "label": ".__init__()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_financial_data_downloader.py",
+      "source_location": "L49",
+      "id": "data_acquisition_a_stock_financial_data_downloader_astockfinancialdownloader_init",
+      "community": 114,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": "._create_directory_structure()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_financial_data_downloader.py",
+      "source_location": "L79",
+      "id": "data_acquisition_a_stock_financial_data_downloader_astockfinancialdownloader_create_directory_structure",
+      "community": 114,
+      "norm_label": "._create_directory_structure()"
+    },
+    {
+      "label": ".get_all_a_stock_codes()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_financial_data_downloader.py",
+      "source_location": "L92",
+      "id": "data_acquisition_a_stock_financial_data_downloader_astockfinancialdownloader_get_all_a_stock_codes",
+      "community": 114,
+      "norm_label": ".get_all_a_stock_codes()"
+    },
+    {
+      "label": "._save_stock_list()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_financial_data_downloader.py",
+      "source_location": "L144",
+      "id": "data_acquisition_a_stock_financial_data_downloader_astockfinancialdownloader_save_stock_list",
+      "community": 114,
+      "norm_label": "._save_stock_list()"
+    },
+    {
+      "label": ".download_stock_financial()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_financial_data_downloader.py",
+      "source_location": "L157",
+      "id": "data_acquisition_a_stock_financial_data_downloader_astockfinancialdownloader_download_stock_financial",
+      "community": 114,
+      "norm_label": ".download_stock_financial()"
+    },
+    {
+      "label": ".calculate_valuation_metrics()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_financial_data_downloader.py",
+      "source_location": "L234",
+      "id": "data_acquisition_a_stock_financial_data_downloader_astockfinancialdownloader_calculate_valuation_metrics",
+      "community": 114,
+      "norm_label": ".calculate_valuation_metrics()"
+    },
+    {
+      "label": ".save_financial_data()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_financial_data_downloader.py",
+      "source_location": "L261",
+      "id": "data_acquisition_a_stock_financial_data_downloader_astockfinancialdownloader_save_financial_data",
+      "community": 114,
+      "norm_label": ".save_financial_data()"
+    },
+    {
+      "label": ".check_already_downloaded()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_financial_data_downloader.py",
+      "source_location": "L310",
+      "id": "data_acquisition_a_stock_financial_data_downloader_astockfinancialdownloader_check_already_downloaded",
+      "community": 114,
+      "norm_label": ".check_already_downloaded()"
+    },
+    {
+      "label": ".download_all_stocks()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_financial_data_downloader.py",
+      "source_location": "L320",
+      "id": "data_acquisition_a_stock_financial_data_downloader_astockfinancialdownloader_download_all_stocks",
+      "community": 114,
+      "norm_label": ".download_all_stocks()"
+    },
+    {
+      "label": "._save_download_stats()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_financial_data_downloader.py",
+      "source_location": "L407",
+      "id": "data_acquisition_a_stock_financial_data_downloader_astockfinancialdownloader_save_download_stats",
+      "community": 114,
+      "norm_label": "._save_download_stats()"
+    },
+    {
+      "label": "._calculate_success_rate()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_financial_data_downloader.py",
+      "source_location": "L414",
+      "id": "data_acquisition_a_stock_financial_data_downloader_astockfinancialdownloader_calculate_success_rate",
+      "community": 114,
+      "norm_label": "._calculate_success_rate()"
+    },
+    {
+      "label": "._generate_download_report()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_financial_data_downloader.py",
+      "source_location": "L421",
+      "id": "data_acquisition_a_stock_financial_data_downloader_astockfinancialdownloader_generate_download_report",
+      "community": 114,
+      "norm_label": "._generate_download_report()"
+    },
+    {
+      "label": "main()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_financial_data_downloader.py",
+      "source_location": "L485",
+      "id": "data_acquisition_a_stock_financial_data_downloader_main",
+      "community": 114,
+      "norm_label": "main()"
+    },
+    {
+      "label": "\u8ba1\u7b97\u4f30\u503c\u6307\u6807 (PE, PB, ROE, \u80a1\u606f\u7387)",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_financial_data_downloader.py",
+      "source_location": "L239",
+      "id": "data_acquisition_a_stock_financial_data_downloader_rationale_239",
+      "community": 114,
+      "norm_label": "\u8ba1\u7b97\u4f30\u503c\u6307\u6807 (pe, pb, roe, \u80a1\u606f\u7387)"
+    },
+    {
+      "label": "test_single_download.py",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/test_single_download.py",
+      "source_location": "L1",
+      "id": "zhaoyun_data_scripts_data_acquisition_test_single_download_py",
+      "community": 537,
+      "norm_label": "test_single_download.py"
+    },
+    {
+      "label": "start_daily_download.py",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/start_daily_download.py",
+      "source_location": "L1",
+      "id": "zhaoyun_data_scripts_data_acquisition_start_daily_download_py",
+      "community": 538,
+      "norm_label": "start_daily_download.py"
+    },
+    {
+      "label": "fix_missing_510300.py",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/fix_missing_510300.py",
+      "source_location": "L1",
+      "id": "zhaoyun_data_scripts_data_acquisition_fix_missing_510300_py",
+      "community": 539,
+      "norm_label": "fix_missing_510300.py"
+    },
+    {
+      "label": "a_stock_daily_data.py",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_daily_data.py",
+      "source_location": "L1",
+      "id": "zhaoyun_data_scripts_data_acquisition_a_stock_daily_data_py",
+      "community": 94,
+      "norm_label": "a_stock_daily_data.py"
+    },
+    {
+      "label": "AStockDailyDataCollector",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_daily_data.py",
+      "source_location": "L29",
+      "id": "data_acquisition_a_stock_daily_data_astockdailydatacollector",
+      "community": 94,
+      "norm_label": "astockdailydatacollector"
+    },
+    {
+      "label": ".__init__()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_daily_data.py",
+      "source_location": "L32",
+      "id": "data_acquisition_a_stock_daily_data_astockdailydatacollector_init",
+      "community": 94,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": "._create_year_directories()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_daily_data.py",
+      "source_location": "L57",
+      "id": "data_acquisition_a_stock_daily_data_astockdailydatacollector_create_year_directories",
+      "community": 94,
+      "norm_label": "._create_year_directories()"
+    },
+    {
+      "label": ".load_stock_list()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_daily_data.py",
+      "source_location": "L67",
+      "id": "data_acquisition_a_stock_daily_data_astockdailydatacollector_load_stock_list",
+      "community": 94,
+      "norm_label": ".load_stock_list()"
+    },
+    {
+      "label": ".collect_daily_data_for_stock()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_daily_data.py",
+      "source_location": "L108",
+      "id": "data_acquisition_a_stock_daily_data_astockdailydatacollector_collect_daily_data_for_stock",
+      "community": 94,
+      "norm_label": ".collect_daily_data_for_stock()"
+    },
+    {
+      "label": ".batch_collect_daily_data()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_daily_data.py",
+      "source_location": "L183",
+      "id": "data_acquisition_a_stock_daily_data_astockdailydatacollector_batch_collect_daily_data",
+      "community": 94,
+      "norm_label": ".batch_collect_daily_data()"
+    },
+    {
+      "label": "._save_stock_daily_data()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_daily_data.py",
+      "source_location": "L295",
+      "id": "data_acquisition_a_stock_daily_data_astockdailydatacollector_save_stock_daily_data",
+      "community": 94,
+      "norm_label": "._save_stock_daily_data()"
+    },
+    {
+      "label": "._save_combined_daily_data()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_daily_data.py",
+      "source_location": "L326",
+      "id": "data_acquisition_a_stock_daily_data_astockdailydatacollector_save_combined_daily_data",
+      "community": 94,
+      "norm_label": "._save_combined_daily_data()"
+    },
+    {
+      "label": "._get_saved_files()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_daily_data.py",
+      "source_location": "L351",
+      "id": "data_acquisition_a_stock_daily_data_astockdailydatacollector_get_saved_files",
+      "community": 94,
+      "norm_label": "._get_saved_files()"
+    },
+    {
+      "label": ".generate_summary_report()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_daily_data.py",
+      "source_location": "L371",
+      "id": "data_acquisition_a_stock_daily_data_astockdailydatacollector_generate_summary_report",
+      "community": 94,
+      "norm_label": ".generate_summary_report()"
+    },
+    {
+      "label": "main()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_daily_data.py",
+      "source_location": "L403",
+      "id": "data_acquisition_a_stock_daily_data_main",
+      "community": 94,
+      "norm_label": "main()"
+    },
+    {
+      "label": "\u52a0\u8f7d\u80a1\u7968\u4ee3\u7801\u5217\u8868                  Returns:             List[str]: \u80a1\u7968\u4ee3\u7801\u5217\u8868",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_daily_data.py",
+      "source_location": "L68",
+      "id": "data_acquisition_a_stock_daily_data_rationale_68",
+      "community": 94,
+      "norm_label": "\u52a0\u8f7d\u80a1\u7968\u4ee3\u7801\u5217\u8868                  returns:             list[str]: \u80a1\u7968\u4ee3\u7801\u5217\u8868"
+    },
+    {
+      "label": "\u91c7\u96c6\u5355\u53ea\u80a1\u7968\u7684\u65e5\u7ebf\u6570\u636e                  Args:             symbol: \u80a1\u7968\u4ee3\u7801             start_da",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_daily_data.py",
+      "source_location": "L109",
+      "id": "data_acquisition_a_stock_daily_data_rationale_109",
+      "community": 94,
+      "norm_label": "\u91c7\u96c6\u5355\u53ea\u80a1\u7968\u7684\u65e5\u7ebf\u6570\u636e                  args:             symbol: \u80a1\u7968\u4ee3\u7801             start_da"
+    },
+    {
+      "label": "\u6279\u91cf\u91c7\u96c6\u65e5\u7ebf\u6570\u636e                  Args:             stock_list: \u80a1\u7968\u4ee3\u7801\u5217\u8868\uff08\u5982\u4e3a\u7a7a\u5219\u81ea\u52a8\u83b7\u53d6\uff09",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_daily_data.py",
+      "source_location": "L184",
+      "id": "data_acquisition_a_stock_daily_data_rationale_184",
+      "community": 94,
+      "norm_label": "\u6279\u91cf\u91c7\u96c6\u65e5\u7ebf\u6570\u636e                  args:             stock_list: \u80a1\u7968\u4ee3\u7801\u5217\u8868(\u5982\u4e3a\u7a7a\u5219\u81ea\u52a8\u83b7\u53d6)"
+    },
+    {
+      "label": "\u4fdd\u5b58\u5355\u53ea\u80a1\u7968\u65e5\u7ebf\u6570\u636e                  Args:             stock_data: \u80a1\u7968\u65e5\u7ebf\u6570\u636e",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_daily_data.py",
+      "source_location": "L296",
+      "id": "data_acquisition_a_stock_daily_data_rationale_296",
+      "community": 94,
+      "norm_label": "\u4fdd\u5b58\u5355\u53ea\u80a1\u7968\u65e5\u7ebf\u6570\u636e                  args:             stock_data: \u80a1\u7968\u65e5\u7ebf\u6570\u636e"
+    },
+    {
+      "label": "\u4fdd\u5b58\u5408\u5e76\u540e\u7684\u65e5\u7ebf\u6570\u636e                  Args:             combined_data: \u5408\u5e76\u540e\u7684\u6240\u6709\u65e5\u7ebf\u6570\u636e",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_daily_data.py",
+      "source_location": "L327",
+      "id": "data_acquisition_a_stock_daily_data_rationale_327",
+      "community": 94,
+      "norm_label": "\u4fdd\u5b58\u5408\u5e76\u540e\u7684\u65e5\u7ebf\u6570\u636e                  args:             combined_data: \u5408\u5e76\u540e\u7684\u6240\u6709\u65e5\u7ebf\u6570\u636e"
+    },
+    {
+      "label": "\u83b7\u53d6\u5df2\u4fdd\u5b58\u7684\u6587\u4ef6\u5217\u8868                  Returns:             List[str]: \u6587\u4ef6\u8def\u5f84\u5217\u8868",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_daily_data.py",
+      "source_location": "L352",
+      "id": "data_acquisition_a_stock_daily_data_rationale_352",
+      "community": 94,
+      "norm_label": "\u83b7\u53d6\u5df2\u4fdd\u5b58\u7684\u6587\u4ef6\u5217\u8868                  returns:             list[str]: \u6587\u4ef6\u8def\u5f84\u5217\u8868"
+    },
+    {
+      "label": "\u751f\u6210\u91c7\u96c6\u6458\u8981\u62a5\u544a                  Args:             result: \u91c7\u96c6\u7ed3\u679c                      Re",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_daily_data.py",
+      "source_location": "L372",
+      "id": "data_acquisition_a_stock_daily_data_rationale_372",
+      "community": 94,
+      "norm_label": "\u751f\u6210\u91c7\u96c6\u6458\u8981\u62a5\u544a                  args:             result: \u91c7\u96c6\u7ed3\u679c                      re"
+    },
+    {
+      "label": "test_daily_api.py",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/test_daily_api.py",
+      "source_location": "L1",
+      "id": "zhaoyun_data_scripts_data_acquisition_test_daily_api_py",
+      "community": 540,
+      "norm_label": "test_daily_api.py"
+    },
+    {
+      "label": "start_full_download.py",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/start_full_download.py",
+      "source_location": "L1",
+      "id": "zhaoyun_data_scripts_data_acquisition_start_full_download_py",
+      "community": 541,
+      "norm_label": "start_full_download.py"
+    },
+    {
+      "label": "test_minute_data_sources.py",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/test_minute_data_sources.py",
+      "source_location": "L1",
+      "id": "zhaoyun_data_scripts_data_acquisition_test_minute_data_sources_py",
+      "community": 209,
+      "norm_label": "test_minute_data_sources.py"
+    },
+    {
+      "label": "MinuteDataSourceTester",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/test_minute_data_sources.py",
+      "source_location": "L26",
+      "id": "data_acquisition_test_minute_data_sources_minutedatasourcetester",
+      "community": 209,
+      "norm_label": "minutedatasourcetester"
+    },
+    {
+      "label": ".__init__()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/test_minute_data_sources.py",
+      "source_location": "L29",
+      "id": "data_acquisition_test_minute_data_sources_minutedatasourcetester_init",
+      "community": 209,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": ".test_akshare_minute_data()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/test_minute_data_sources.py",
+      "source_location": "L48",
+      "id": "data_acquisition_test_minute_data_sources_minutedatasourcetester_test_akshare_minute_data",
+      "community": 209,
+      "norm_label": ".test_akshare_minute_data()"
+    },
+    {
+      "label": ".test_tushare_minute_data()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/test_minute_data_sources.py",
+      "source_location": "L163",
+      "id": "data_acquisition_test_minute_data_sources_minutedatasourcetester_test_tushare_minute_data",
+      "community": 209,
+      "norm_label": ".test_tushare_minute_data()"
+    },
+    {
+      "label": "._check_data_quality()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/test_minute_data_sources.py",
+      "source_location": "L279",
+      "id": "data_acquisition_test_minute_data_sources_minutedatasourcetester_check_data_quality",
+      "community": 209,
+      "norm_label": "._check_data_quality()"
+    },
+    {
+      "label": ".generate_test_report()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/test_minute_data_sources.py",
+      "source_location": "L339",
+      "id": "data_acquisition_test_minute_data_sources_minutedatasourcetester_generate_test_report",
+      "community": 209,
+      "norm_label": ".generate_test_report()"
+    },
+    {
+      "label": "main()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/test_minute_data_sources.py",
+      "source_location": "L422",
+      "id": "data_acquisition_test_minute_data_sources_main",
+      "community": 209,
+      "norm_label": "main()"
+    },
+    {
+      "label": "\u6d4b\u8bd5Tushare\u5206\u949f\u6570\u636e\u63a5\u53e3\uff08\u9700\u8981API Token\uff09",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/test_minute_data_sources.py",
+      "source_location": "L164",
+      "id": "data_acquisition_test_minute_data_sources_rationale_164",
+      "community": 209,
+      "norm_label": "\u6d4b\u8bd5tushare\u5206\u949f\u6570\u636e\u63a5\u53e3(\u9700\u8981api token)"
+    },
+    {
+      "label": "\u68c0\u67e5\u6570\u636e\u8d28\u91cf                  Args:             data: \u6570\u636e             period: \u65f6\u95f4\u5468\u671f",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/test_minute_data_sources.py",
+      "source_location": "L280",
+      "id": "data_acquisition_test_minute_data_sources_rationale_280",
+      "community": 209,
+      "norm_label": "\u68c0\u67e5\u6570\u636e\u8d28\u91cf                  args:             data: \u6570\u636e             period: \u65f6\u95f4\u5468\u671f"
+    },
+    {
+      "label": "a_stock_financial_data.py",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_financial_data.py",
+      "source_location": "L1",
+      "id": "zhaoyun_data_scripts_data_acquisition_a_stock_financial_data_py",
+      "community": 75,
+      "norm_label": "a_stock_financial_data.py"
+    },
+    {
+      "label": "AStockFinancialDataCollector",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_financial_data.py",
+      "source_location": "L29",
+      "id": "data_acquisition_a_stock_financial_data_astockfinancialdatacollector",
+      "community": 75,
+      "norm_label": "astockfinancialdatacollector"
+    },
+    {
+      "label": ".__init__()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_financial_data.py",
+      "source_location": "L32",
+      "id": "data_acquisition_a_stock_financial_data_astockfinancialdatacollector_init",
+      "community": 75,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": "._create_date_directories()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_financial_data.py",
+      "source_location": "L57",
+      "id": "data_acquisition_a_stock_financial_data_astockfinancialdatacollector_create_date_directories",
+      "community": 75,
+      "norm_label": "._create_date_directories()"
+    },
+    {
+      "label": ".load_stock_list()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_financial_data.py",
+      "source_location": "L70",
+      "id": "data_acquisition_a_stock_financial_data_astockfinancialdatacollector_load_stock_list",
+      "community": 75,
+      "norm_label": ".load_stock_list()"
+    },
+    {
+      "label": ".collect_financial_indicators()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_financial_data.py",
+      "source_location": "L111",
+      "id": "data_acquisition_a_stock_financial_data_astockfinancialdatacollector_collect_financial_indicators",
+      "community": 75,
+      "norm_label": ".collect_financial_indicators()"
+    },
+    {
+      "label": ".collect_balance_sheet()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_financial_data.py",
+      "source_location": "L146",
+      "id": "data_acquisition_a_stock_financial_data_astockfinancialdatacollector_collect_balance_sheet",
+      "community": 75,
+      "norm_label": ".collect_balance_sheet()"
+    },
+    {
+      "label": ".collect_income_statement()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_financial_data.py",
+      "source_location": "L181",
+      "id": "data_acquisition_a_stock_financial_data_astockfinancialdatacollector_collect_income_statement",
+      "community": 75,
+      "norm_label": ".collect_income_statement()"
+    },
+    {
+      "label": ".collect_cash_flow()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_financial_data.py",
+      "source_location": "L216",
+      "id": "data_acquisition_a_stock_financial_data_astockfinancialdatacollector_collect_cash_flow",
+      "community": 75,
+      "norm_label": ".collect_cash_flow()"
+    },
+    {
+      "label": ".batch_collect_financial_data()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_financial_data.py",
+      "source_location": "L251",
+      "id": "data_acquisition_a_stock_financial_data_astockfinancialdatacollector_batch_collect_financial_data",
+      "community": 75,
+      "norm_label": ".batch_collect_financial_data()"
+    },
+    {
+      "label": "._save_financial_data()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_financial_data.py",
+      "source_location": "L394",
+      "id": "data_acquisition_a_stock_financial_data_astockfinancialdatacollector_save_financial_data",
+      "community": 75,
+      "norm_label": "._save_financial_data()"
+    },
+    {
+      "label": "._process_financial_data()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_financial_data.py",
+      "source_location": "L434",
+      "id": "data_acquisition_a_stock_financial_data_astockfinancialdatacollector_process_financial_data",
+      "community": 75,
+      "norm_label": "._process_financial_data()"
+    },
+    {
+      "label": "._calculate_valuation_indicators()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_financial_data.py",
+      "source_location": "L489",
+      "id": "data_acquisition_a_stock_financial_data_astockfinancialdatacollector_calculate_valuation_indicators",
+      "community": 75,
+      "norm_label": "._calculate_valuation_indicators()"
+    },
+    {
+      "label": "._save_valuation_indicators()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_financial_data.py",
+      "source_location": "L540",
+      "id": "data_acquisition_a_stock_financial_data_astockfinancialdatacollector_save_valuation_indicators",
+      "community": 75,
+      "norm_label": "._save_valuation_indicators()"
+    },
+    {
+      "label": "main()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_financial_data.py",
+      "source_location": "L573",
+      "id": "data_acquisition_a_stock_financial_data_main",
+      "community": 75,
+      "norm_label": "main()"
+    },
+    {
+      "label": "\u52a0\u8f7d\u80a1\u7968\u4ee3\u7801\u5217\u8868                  Returns:             List[str]: \u80a1\u7968\u4ee3\u7801\u5217\u8868",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_financial_data.py",
+      "source_location": "L71",
+      "id": "data_acquisition_a_stock_financial_data_rationale_71",
+      "community": 75,
+      "norm_label": "\u52a0\u8f7d\u80a1\u7968\u4ee3\u7801\u5217\u8868                  returns:             list[str]: \u80a1\u7968\u4ee3\u7801\u5217\u8868"
+    },
+    {
+      "label": "\u91c7\u96c6\u5355\u53ea\u80a1\u7968\u7684\u8d22\u52a1\u6307\u6807                  Args:             symbol: \u80a1\u7968\u4ee3\u7801",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_financial_data.py",
+      "source_location": "L112",
+      "id": "data_acquisition_a_stock_financial_data_rationale_112",
+      "community": 75,
+      "norm_label": "\u91c7\u96c6\u5355\u53ea\u80a1\u7968\u7684\u8d22\u52a1\u6307\u6807                  args:             symbol: \u80a1\u7968\u4ee3\u7801"
+    },
+    {
+      "label": "\u91c7\u96c6\u8d44\u4ea7\u8d1f\u503a\u8868\u6570\u636e                  Args:             symbol: \u80a1\u7968\u4ee3\u7801                      R",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_financial_data.py",
+      "source_location": "L147",
+      "id": "data_acquisition_a_stock_financial_data_rationale_147",
+      "community": 75,
+      "norm_label": "\u91c7\u96c6\u8d44\u4ea7\u8d1f\u503a\u8868\u6570\u636e                  args:             symbol: \u80a1\u7968\u4ee3\u7801                      r"
+    },
+    {
+      "label": "\u91c7\u96c6\u5229\u6da6\u8868\u6570\u636e                  Args:             symbol: \u80a1\u7968\u4ee3\u7801                      Ret",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_financial_data.py",
+      "source_location": "L182",
+      "id": "data_acquisition_a_stock_financial_data_rationale_182",
+      "community": 75,
+      "norm_label": "\u91c7\u96c6\u5229\u6da6\u8868\u6570\u636e                  args:             symbol: \u80a1\u7968\u4ee3\u7801                      ret"
+    },
+    {
+      "label": "\u91c7\u96c6\u73b0\u91d1\u6d41\u91cf\u8868\u6570\u636e                  Args:             symbol: \u80a1\u7968\u4ee3\u7801                      R",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_financial_data.py",
+      "source_location": "L217",
+      "id": "data_acquisition_a_stock_financial_data_rationale_217",
+      "community": 75,
+      "norm_label": "\u91c7\u96c6\u73b0\u91d1\u6d41\u91cf\u8868\u6570\u636e                  args:             symbol: \u80a1\u7968\u4ee3\u7801                      r"
+    },
+    {
+      "label": "\u6279\u91cf\u91c7\u96c6\u8d22\u52a1\u6570\u636e                  Args:             stock_list: \u80a1\u7968\u4ee3\u7801\u5217\u8868             max_w",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_financial_data.py",
+      "source_location": "L252",
+      "id": "data_acquisition_a_stock_financial_data_rationale_252",
+      "community": 75,
+      "norm_label": "\u6279\u91cf\u91c7\u96c6\u8d22\u52a1\u6570\u636e                  args:             stock_list: \u80a1\u7968\u4ee3\u7801\u5217\u8868             max_w"
+    },
+    {
+      "label": "\u4fdd\u5b58\u8d22\u52a1\u6570\u636e                  Args:             df: \u8d22\u52a1\u6570\u636e             data_type: \u6570\u636e\u7c7b\u578b",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_financial_data.py",
+      "source_location": "L395",
+      "id": "data_acquisition_a_stock_financial_data_rationale_395",
+      "community": 75,
+      "norm_label": "\u4fdd\u5b58\u8d22\u52a1\u6570\u636e                  args:             df: \u8d22\u52a1\u6570\u636e             data_type: \u6570\u636e\u7c7b\u578b"
+    },
+    {
+      "label": "\u5904\u7406\u8d22\u52a1\u6570\u636e                  Args:             df: \u539f\u59cb\u8d22\u52a1\u6570\u636e             data_type: \u6570\u636e\u7c7b\u578b",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_financial_data.py",
+      "source_location": "L435",
+      "id": "data_acquisition_a_stock_financial_data_rationale_435",
+      "community": 75,
+      "norm_label": "\u5904\u7406\u8d22\u52a1\u6570\u636e                  args:             df: \u539f\u59cb\u8d22\u52a1\u6570\u636e             data_type: \u6570\u636e\u7c7b\u578b"
+    },
+    {
+      "label": "\u8ba1\u7b97\u4f30\u503c\u6307\u6807                  Args:             financial_indicators: \u8d22\u52a1\u6307\u6807\u6570\u636e\u5217\u8868",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_financial_data.py",
+      "source_location": "L490",
+      "id": "data_acquisition_a_stock_financial_data_rationale_490",
+      "community": 75,
+      "norm_label": "\u8ba1\u7b97\u4f30\u503c\u6307\u6807                  args:             financial_indicators: \u8d22\u52a1\u6307\u6807\u6570\u636e\u5217\u8868"
+    },
+    {
+      "label": "\u4fdd\u5b58\u4f30\u503c\u6307\u6807\u6570\u636e                  Args:             valuation_df: \u4f30\u503c\u6307\u6807\u6570\u636e",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_financial_data.py",
+      "source_location": "L541",
+      "id": "data_acquisition_a_stock_financial_data_rationale_541",
+      "community": 75,
+      "norm_label": "\u4fdd\u5b58\u4f30\u503c\u6307\u6807\u6570\u636e                  args:             valuation_df: \u4f30\u503c\u6307\u6807\u6570\u636e"
+    },
+    {
+      "label": "a_stock_data_main.py",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_data_main.py",
+      "source_location": "L1",
+      "id": "zhaoyun_data_scripts_data_acquisition_a_stock_data_main_py",
+      "community": 107,
+      "norm_label": "a_stock_data_main.py"
+    },
+    {
+      "label": "AStockDataMainController",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_data_main.py",
+      "source_location": "L26",
+      "id": "data_acquisition_a_stock_data_main_astockdatamaincontroller",
+      "community": 107,
+      "norm_label": "astockdatamaincontroller"
+    },
+    {
+      "label": ".__init__()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_data_main.py",
+      "source_location": "L29",
+      "id": "data_acquisition_a_stock_data_main_astockdatamaincontroller_init",
+      "community": 107,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": ".run_basic_info_task()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_data_main.py",
+      "source_location": "L58",
+      "id": "data_acquisition_a_stock_data_main_astockdatamaincontroller_run_basic_info_task",
+      "community": 107,
+      "norm_label": ".run_basic_info_task()"
+    },
+    {
+      "label": ".run_daily_data_task()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_data_main.py",
+      "source_location": "L113",
+      "id": "data_acquisition_a_stock_data_main_astockdatamaincontroller_run_daily_data_task",
+      "community": 107,
+      "norm_label": ".run_daily_data_task()"
+    },
+    {
+      "label": ".run_financial_data_task()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_data_main.py",
+      "source_location": "L187",
+      "id": "data_acquisition_a_stock_data_main_astockdatamaincontroller_run_financial_data_task",
+      "community": 107,
+      "norm_label": ".run_financial_data_task()"
+    },
+    {
+      "label": ".run_quality_check_task()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_data_main.py",
+      "source_location": "L260",
+      "id": "data_acquisition_a_stock_data_main_astockdatamaincontroller_run_quality_check_task",
+      "community": 107,
+      "norm_label": ".run_quality_check_task()"
+    },
+    {
+      "label": ".run_full_pipeline()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_data_main.py",
+      "source_location": "L320",
+      "id": "data_acquisition_a_stock_data_main_astockdatamaincontroller_run_full_pipeline",
+      "community": 107,
+      "norm_label": ".run_full_pipeline()"
+    },
+    {
+      "label": "._generate_summary_report()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_data_main.py",
+      "source_location": "L371",
+      "id": "data_acquisition_a_stock_data_main_astockdatamaincontroller_generate_summary_report",
+      "community": 107,
+      "norm_label": "._generate_summary_report()"
+    },
+    {
+      "label": "._finalize_task_status()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_data_main.py",
+      "source_location": "L454",
+      "id": "data_acquisition_a_stock_data_main_astockdatamaincontroller_finalize_task_status",
+      "community": 107,
+      "norm_label": "._finalize_task_status()"
+    },
+    {
+      "label": "main()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_data_main.py",
+      "source_location": "L480",
+      "id": "data_acquisition_a_stock_data_main_main",
+      "community": 107,
+      "norm_label": "main()"
+    },
+    {
+      "label": "\u8fd0\u884c\u57fa\u7840\u4fe1\u606f\u91c7\u96c6\u4efb\u52a1                  Args:             test_mode: \u6d4b\u8bd5\u6a21\u5f0f\uff08\u5c11\u91cf\u6570\u636e\uff09",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_data_main.py",
+      "source_location": "L59",
+      "id": "data_acquisition_a_stock_data_main_rationale_59",
+      "community": 107,
+      "norm_label": "\u8fd0\u884c\u57fa\u7840\u4fe1\u606f\u91c7\u96c6\u4efb\u52a1                  args:             test_mode: \u6d4b\u8bd5\u6a21\u5f0f(\u5c11\u91cf\u6570\u636e)"
+    },
+    {
+      "label": "\u8fd0\u884c\u65e5\u7ebf\u6570\u636e\u91c7\u96c6\u4efb\u52a1                  Args:             test_mode: \u6d4b\u8bd5\u6a21\u5f0f\uff08\u5c11\u91cf\u6570\u636e\uff09",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_data_main.py",
+      "source_location": "L114",
+      "id": "data_acquisition_a_stock_data_main_rationale_114",
+      "community": 107,
+      "norm_label": "\u8fd0\u884c\u65e5\u7ebf\u6570\u636e\u91c7\u96c6\u4efb\u52a1                  args:             test_mode: \u6d4b\u8bd5\u6a21\u5f0f(\u5c11\u91cf\u6570\u636e)"
+    },
+    {
+      "label": "\u8fd0\u884c\u8d22\u52a1\u6570\u636e\u91c7\u96c6\u4efb\u52a1                  Args:             test_mode: \u6d4b\u8bd5\u6a21\u5f0f\uff08\u5c11\u91cf\u6570\u636e\uff09",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_data_main.py",
+      "source_location": "L188",
+      "id": "data_acquisition_a_stock_data_main_rationale_188",
+      "community": 107,
+      "norm_label": "\u8fd0\u884c\u8d22\u52a1\u6570\u636e\u91c7\u96c6\u4efb\u52a1                  args:             test_mode: \u6d4b\u8bd5\u6a21\u5f0f(\u5c11\u91cf\u6570\u636e)"
+    },
+    {
+      "label": "\u8fd0\u884c\u8d28\u91cf\u68c0\u67e5\u4efb\u52a1                  Returns:             Dict: \u4efb\u52a1\u6267\u884c\u7ed3\u679c",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_data_main.py",
+      "source_location": "L261",
+      "id": "data_acquisition_a_stock_data_main_rationale_261",
+      "community": 107,
+      "norm_label": "\u8fd0\u884c\u8d28\u91cf\u68c0\u67e5\u4efb\u52a1                  returns:             dict: \u4efb\u52a1\u6267\u884c\u7ed3\u679c"
+    },
+    {
+      "label": "\u8fd0\u884c\u5b8c\u6574\u7684\u6570\u636e\u91c7\u96c6\u6d41\u6c34\u7ebf                  Args:             test_mode: \u6d4b\u8bd5\u6a21\u5f0f",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_data_main.py",
+      "source_location": "L321",
+      "id": "data_acquisition_a_stock_data_main_rationale_321",
+      "community": 107,
+      "norm_label": "\u8fd0\u884c\u5b8c\u6574\u7684\u6570\u636e\u91c7\u96c6\u6d41\u6c34\u7ebf                  args:             test_mode: \u6d4b\u8bd5\u6a21\u5f0f"
+    },
+    {
+      "label": "\u751f\u6210\u6c47\u603b\u62a5\u544a                  Args:             execution_time: \u6267\u884c\u65f6\u95f4\uff08\u79d2\uff09",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/a_stock_data_main.py",
+      "source_location": "L372",
+      "id": "data_acquisition_a_stock_data_main_rationale_372",
+      "community": 107,
+      "norm_label": "\u751f\u6210\u6c47\u603b\u62a5\u544a                  args:             execution_time: \u6267\u884c\u65f6\u95f4(\u79d2)"
+    },
+    {
+      "label": "get_a_stock_list.py",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/get_a_stock_list.py",
+      "source_location": "L1",
+      "id": "zhaoyun_data_scripts_data_acquisition_get_a_stock_list_py",
+      "community": 36,
+      "norm_label": "get_a_stock_list.py"
+    },
+    {
+      "label": "AStockListFetcher",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/get_a_stock_list.py",
+      "source_location": "L25",
+      "id": "data_acquisition_get_a_stock_list_astocklistfetcher",
+      "community": 36,
+      "norm_label": "astocklistfetcher"
+    },
+    {
+      "label": ".__init__()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/get_a_stock_list.py",
+      "source_location": "L28",
+      "id": "data_acquisition_get_a_stock_list_astocklistfetcher_init",
+      "community": 36,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": ".get_all_a_stocks()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/get_a_stock_list.py",
+      "source_location": "L34",
+      "id": "data_acquisition_get_a_stock_list_astocklistfetcher_get_all_a_stocks",
+      "community": 36,
+      "norm_label": ".get_all_a_stocks()"
+    },
+    {
+      "label": "._generate_mock_data()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/get_a_stock_list.py",
+      "source_location": "L111",
+      "id": "data_acquisition_get_a_stock_list_astocklistfetcher_generate_mock_data",
+      "community": 36,
+      "norm_label": "._generate_mock_data()"
+    },
+    {
+      "label": ".filter_by_market()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/get_a_stock_list.py",
+      "source_location": "L145",
+      "id": "data_acquisition_get_a_stock_list_astocklistfetcher_filter_by_market",
+      "community": 36,
+      "norm_label": ".filter_by_market()"
+    },
+    {
+      "label": ".save_to_csv()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/get_a_stock_list.py",
+      "source_location": "L177",
+      "id": "data_acquisition_get_a_stock_list_astocklistfetcher_save_to_csv",
+      "community": 36,
+      "norm_label": ".save_to_csv()"
+    },
+    {
+      "label": ".save_to_json()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/get_a_stock_list.py",
+      "source_location": "L206",
+      "id": "data_acquisition_get_a_stock_list_astocklistfetcher_save_to_json",
+      "community": 36,
+      "norm_label": ".save_to_json()"
+    },
+    {
+      "label": "main()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/get_a_stock_list.py",
+      "source_location": "L244",
+      "id": "data_acquisition_get_a_stock_list_main",
+      "community": 36,
+      "norm_label": "main()"
+    },
+    {
+      "label": "\u83b7\u53d6\u6240\u6709A\u80a1\u80a1\u7968\u5217\u8868                  Returns:             pd.DataFrame: \u5305\u542b\u4ee3\u7801\u3001\u540d\u79f0\u3001\u5f53\u524d\u4ef7\u683c\u7684Data",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/get_a_stock_list.py",
+      "source_location": "L35",
+      "id": "data_acquisition_get_a_stock_list_rationale_35",
+      "community": 36,
+      "norm_label": "\u83b7\u53d6\u6240\u6709a\u80a1\u80a1\u7968\u5217\u8868                  returns:             pd.dataframe: \u5305\u542b\u4ee3\u7801\u3001\u540d\u79f0\u3001\u5f53\u524d\u4ef7\u683c\u7684data"
+    },
+    {
+      "label": "\u751f\u6210\u6a21\u62df\u6570\u636e\u7528\u4e8e\u6d4b\u8bd5                  Returns:             pd.DataFrame: \u6a21\u62df\u80a1\u7968\u6570\u636e",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/get_a_stock_list.py",
+      "source_location": "L112",
+      "id": "data_acquisition_get_a_stock_list_rationale_112",
+      "community": 36,
+      "norm_label": "\u751f\u6210\u6a21\u62df\u6570\u636e\u7528\u4e8e\u6d4b\u8bd5                  returns:             pd.dataframe: \u6a21\u62df\u80a1\u7968\u6570\u636e"
+    },
+    {
+      "label": "\u6309\u5e02\u573a\u7b5b\u9009\u80a1\u7968                  Args:             df: \u539f\u59cb\u80a1\u7968\u5217\u8868             market: \u5e02\u573a\u7c7b\u578b\uff0c'",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/get_a_stock_list.py",
+      "source_location": "L146",
+      "id": "data_acquisition_get_a_stock_list_rationale_146",
+      "community": 36,
+      "norm_label": "\u6309\u5e02\u573a\u7b5b\u9009\u80a1\u7968                  args:             df: \u539f\u59cb\u80a1\u7968\u5217\u8868             market: \u5e02\u573a\u7c7b\u578b,'"
+    },
+    {
+      "label": "\u4fdd\u5b58\u6570\u636e\u5230CSV\u6587\u4ef6                  Args:             df: \u80a1\u7968\u6570\u636eDataFrame             outp",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/get_a_stock_list.py",
+      "source_location": "L178",
+      "id": "data_acquisition_get_a_stock_list_rationale_178",
+      "community": 36,
+      "norm_label": "\u4fdd\u5b58\u6570\u636e\u5230csv\u6587\u4ef6                  args:             df: \u80a1\u7968\u6570\u636edataframe             outp"
+    },
+    {
+      "label": "\u4fdd\u5b58\u6570\u636e\u5230JSON\u6587\u4ef6                  Args:             df: \u80a1\u7968\u6570\u636eDataFrame             out",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/get_a_stock_list.py",
+      "source_location": "L207",
+      "id": "data_acquisition_get_a_stock_list_rationale_207",
+      "community": 36,
+      "norm_label": "\u4fdd\u5b58\u6570\u636e\u5230json\u6587\u4ef6                  args:             df: \u80a1\u7968\u6570\u636edataframe             out"
+    },
+    {
+      "label": "finalize_local_daily_data.py",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/finalize_local_daily_data.py",
+      "source_location": "L1",
+      "id": "zhaoyun_data_scripts_data_acquisition_finalize_local_daily_data_py",
+      "community": 252,
+      "norm_label": "finalize_local_daily_data.py"
+    },
+    {
+      "label": "LocalDailyDataFinalizer",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/finalize_local_daily_data.py",
+      "source_location": "L27",
+      "id": "data_acquisition_finalize_local_daily_data_localdailydatafinalizer",
+      "community": 252,
+      "norm_label": "localdailydatafinalizer"
+    },
+    {
+      "label": ".__init__()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/finalize_local_daily_data.py",
+      "source_location": "L30",
+      "id": "data_acquisition_finalize_local_daily_data_localdailydatafinalizer_init",
+      "community": 252,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": ".load_existing_data()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/finalize_local_daily_data.py",
+      "source_location": "L53",
+      "id": "data_acquisition_finalize_local_daily_data_localdailydatafinalizer_load_existing_data",
+      "community": 252,
+      "norm_label": ".load_existing_data()"
+    },
+    {
+      "label": ".create_daily_data_structure()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/finalize_local_daily_data.py",
+      "source_location": "L77",
+      "id": "data_acquisition_finalize_local_daily_data_localdailydatafinalizer_create_daily_data_structure",
+      "community": 252,
+      "norm_label": ".create_daily_data_structure()"
+    },
+    {
+      "label": ".generate_data_summary()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/finalize_local_daily_data.py",
+      "source_location": "L117",
+      "id": "data_acquisition_finalize_local_daily_data_localdailydatafinalizer_generate_data_summary",
+      "community": 252,
+      "norm_label": ".generate_data_summary()"
+    },
+    {
+      "label": ".create_data_readme()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/finalize_local_daily_data.py",
+      "source_location": "L178",
+      "id": "data_acquisition_finalize_local_daily_data_localdailydatafinalizer_create_data_readme",
+      "community": 252,
+      "norm_label": ".create_data_readme()"
+    },
+    {
+      "label": ".run()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/finalize_local_daily_data.py",
+      "source_location": "L289",
+      "id": "data_acquisition_finalize_local_daily_data_localdailydatafinalizer_run",
+      "community": 252,
+      "norm_label": ".run()"
+    },
+    {
+      "label": "main()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/finalize_local_daily_data.py",
+      "source_location": "L343",
+      "id": "data_acquisition_finalize_local_daily_data_main",
+      "community": 252,
+      "norm_label": "main()"
+    },
+    {
+      "label": "test_fix_daily.py",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/test_fix_daily.py",
+      "source_location": "L1",
+      "id": "zhaoyun_data_scripts_data_acquisition_test_fix_daily_py",
+      "community": 542,
+      "norm_label": "test_fix_daily.py"
+    },
+    {
+      "label": "simple_downloader.py",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/simple_downloader.py",
+      "source_location": "L1",
+      "id": "zhaoyun_data_scripts_data_acquisition_simple_downloader_py",
+      "community": 184,
+      "norm_label": "simple_downloader.py"
+    },
+    {
+      "label": "SimpleMinuteDownloader",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/simple_downloader.py",
+      "source_location": "L32",
+      "id": "data_acquisition_simple_downloader_simpleminutedownloader",
+      "community": 184,
+      "norm_label": "simpleminutedownloader"
+    },
+    {
+      "label": ".__init__()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/simple_downloader.py",
+      "source_location": "L35",
+      "id": "data_acquisition_simple_downloader_simpleminutedownloader_init",
+      "community": 184,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": ".get_all_a_stock_codes()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/simple_downloader.py",
+      "source_location": "L76",
+      "id": "data_acquisition_simple_downloader_simpleminutedownloader_get_all_a_stock_codes",
+      "community": 184,
+      "norm_label": ".get_all_a_stock_codes()"
+    },
+    {
+      "label": "._get_default_stock_codes()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/simple_downloader.py",
+      "source_location": "L107",
+      "id": "data_acquisition_simple_downloader_simpleminutedownloader_get_default_stock_codes",
+      "community": 184,
+      "norm_label": "._get_default_stock_codes()"
+    },
+    {
+      "label": ".download_stock_data()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/simple_downloader.py",
+      "source_location": "L122",
+      "id": "data_acquisition_simple_downloader_simpleminutedownloader_download_stock_data",
+      "community": 184,
+      "norm_label": ".download_stock_data()"
+    },
+    {
+      "label": ".download_all_stocks()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/simple_downloader.py",
+      "source_location": "L184",
+      "id": "data_acquisition_simple_downloader_simpleminutedownloader_download_all_stocks",
+      "community": 184,
+      "norm_label": ".download_all_stocks()"
+    },
+    {
+      "label": "._save_progress_report()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/simple_downloader.py",
+      "source_location": "L249",
+      "id": "data_acquisition_simple_downloader_simpleminutedownloader_save_progress_report",
+      "community": 184,
+      "norm_label": "._save_progress_report()"
+    },
+    {
+      "label": "._save_final_report()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/simple_downloader.py",
+      "source_location": "L275",
+      "id": "data_acquisition_simple_downloader_simpleminutedownloader_save_final_report",
+      "community": 184,
+      "norm_label": "._save_final_report()"
+    },
+    {
+      "label": "._estimate_time_left()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/simple_downloader.py",
+      "source_location": "L301",
+      "id": "data_acquisition_simple_downloader_simpleminutedownloader_estimate_time_left",
+      "community": 184,
+      "norm_label": "._estimate_time_left()"
+    },
+    {
+      "label": "main()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_acquisition/simple_downloader.py",
+      "source_location": "L322",
+      "id": "data_acquisition_simple_downloader_main",
+      "community": 184,
+      "norm_label": "main()"
+    },
+    {
+      "label": "test_adapter.py",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_validation/test_adapter.py",
+      "source_location": "L1",
+      "id": "zhaoyun_data_scripts_data_validation_test_adapter_py",
+      "community": 95,
+      "norm_label": "test_adapter.py"
+    },
+    {
+      "label": "DataAdapterTester",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_validation/test_adapter.py",
+      "source_location": "L16",
+      "id": "data_validation_test_adapter_dataadaptertester",
+      "community": 95,
+      "norm_label": "dataadaptertester"
+    },
+    {
+      "label": ".__init__()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_validation/test_adapter.py",
+      "source_location": "L19",
+      "id": "data_validation_test_adapter_dataadaptertester_init",
+      "community": 95,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": "._load_config()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_validation/test_adapter.py",
+      "source_location": "L47",
+      "id": "data_validation_test_adapter_dataadaptertester_load_config",
+      "community": 95,
+      "norm_label": "._load_config()"
+    },
+    {
+      "label": ".test_akshare_vnpy_adapter()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_validation/test_adapter.py",
+      "source_location": "L80",
+      "id": "data_validation_test_adapter_dataadaptertester_test_akshare_vnpy_adapter",
+      "community": 95,
+      "norm_label": ".test_akshare_vnpy_adapter()"
+    },
+    {
+      "label": ".test_data_completeness()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_validation/test_adapter.py",
+      "source_location": "L155",
+      "id": "data_validation_test_adapter_dataadaptertester_test_data_completeness",
+      "community": 95,
+      "norm_label": ".test_data_completeness()"
+    },
+    {
+      "label": ".test_data_consistency()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_validation/test_adapter.py",
+      "source_location": "L224",
+      "id": "data_validation_test_adapter_dataadaptertester_test_data_consistency",
+      "community": 95,
+      "norm_label": ".test_data_consistency()"
+    },
+    {
+      "label": ".run_all_tests()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_validation/test_adapter.py",
+      "source_location": "L297",
+      "id": "data_validation_test_adapter_dataadaptertester_run_all_tests",
+      "community": 95,
+      "norm_label": ".run_all_tests()"
+    },
+    {
+      "label": ".generate_test_report()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_validation/test_adapter.py",
+      "source_location": "L328",
+      "id": "data_validation_test_adapter_dataadaptertester_generate_test_report",
+      "community": 95,
+      "norm_label": ".generate_test_report()"
+    },
+    {
+      "label": ".save_results()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_validation/test_adapter.py",
+      "source_location": "L360",
+      "id": "data_validation_test_adapter_dataadaptertester_save_results",
+      "community": 95,
+      "norm_label": ".save_results()"
+    },
+    {
+      "label": "main()",
+      "file_type": "code",
+      "source_file": "zhaoyun-data/scripts/data_validation/test_adapter.py",
+      "source_location": "L381",
+      "id": "data_validation_test_adapter_main",
+      "community": 95,
+      "norm_label": "main()"
+    },
+    {
+      "label": "\u521d\u59cb\u5316\u6d4b\u8bd5\u5de5\u5177                  Args:             config_file: \u914d\u7f6e\u6587\u4ef6\u8def\u5f84",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_validation/test_adapter.py",
+      "source_location": "L20",
+      "id": "data_validation_test_adapter_rationale_20",
+      "community": 95,
+      "norm_label": "\u521d\u59cb\u5316\u6d4b\u8bd5\u5de5\u5177                  args:             config_file: \u914d\u7f6e\u6587\u4ef6\u8def\u5f84"
+    },
+    {
+      "label": "\u52a0\u8f7d\u914d\u7f6e\u6587\u4ef6                  Args:             config_file: \u914d\u7f6e\u6587\u4ef6\u8def\u5f84",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_validation/test_adapter.py",
+      "source_location": "L48",
+      "id": "data_validation_test_adapter_rationale_48",
+      "community": 95,
+      "norm_label": "\u52a0\u8f7d\u914d\u7f6e\u6587\u4ef6                  args:             config_file: \u914d\u7f6e\u6587\u4ef6\u8def\u5f84"
+    },
+    {
+      "label": "\u6d4b\u8bd5AKShare\u5230vnPy\u7684\u9002\u914d\u5668                  Returns:             Dict: \u6d4b\u8bd5\u7ed3\u679c",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_validation/test_adapter.py",
+      "source_location": "L81",
+      "id": "data_validation_test_adapter_rationale_81",
+      "community": 95,
+      "norm_label": "\u6d4b\u8bd5akshare\u5230vnpy\u7684\u9002\u914d\u5668                  returns:             dict: \u6d4b\u8bd5\u7ed3\u679c"
+    },
+    {
+      "label": "\u6d4b\u8bd5\u6570\u636e\u5b8c\u6574\u6027                  Args:             data_path: \u6570\u636e\u6587\u4ef6\u8def\u5f84             require",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_validation/test_adapter.py",
+      "source_location": "L156",
+      "id": "data_validation_test_adapter_rationale_156",
+      "community": 95,
+      "norm_label": "\u6d4b\u8bd5\u6570\u636e\u5b8c\u6574\u6027                  args:             data_path: \u6570\u636e\u6587\u4ef6\u8def\u5f84             require"
+    },
+    {
+      "label": "\u6d4b\u8bd5\u6570\u636e\u4e00\u81f4\u6027                  Args:             data_path: \u6570\u636e\u6587\u4ef6\u8def\u5f84             expecte",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_validation/test_adapter.py",
+      "source_location": "L225",
+      "id": "data_validation_test_adapter_rationale_225",
+      "community": 95,
+      "norm_label": "\u6d4b\u8bd5\u6570\u636e\u4e00\u81f4\u6027                  args:             data_path: \u6570\u636e\u6587\u4ef6\u8def\u5f84             expecte"
+    },
+    {
+      "label": "\u8fd0\u884c\u6240\u6709\u6d4b\u8bd5                  Returns:             Dict: \u6240\u6709\u6d4b\u8bd5\u7ed3\u679c",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_validation/test_adapter.py",
+      "source_location": "L298",
+      "id": "data_validation_test_adapter_rationale_298",
+      "community": 95,
+      "norm_label": "\u8fd0\u884c\u6240\u6709\u6d4b\u8bd5                  returns:             dict: \u6240\u6709\u6d4b\u8bd5\u7ed3\u679c"
+    },
+    {
+      "label": "\u751f\u6210\u6d4b\u8bd5\u62a5\u544a                  Returns:             Dict: \u6d4b\u8bd5\u62a5\u544a",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_validation/test_adapter.py",
+      "source_location": "L329",
+      "id": "data_validation_test_adapter_rationale_329",
+      "community": 95,
+      "norm_label": "\u751f\u6210\u6d4b\u8bd5\u62a5\u544a                  returns:             dict: \u6d4b\u8bd5\u62a5\u544a"
+    },
+    {
+      "label": "\u4fdd\u5b58\u6d4b\u8bd5\u7ed3\u679c                  Args:             output_path: \u8f93\u51fa\u8def\u5f84",
+      "file_type": "rationale",
+      "source_file": "zhaoyun-data/scripts/data_validation/test_adapter.py",
+      "source_location": "L361",
+      "id": "data_validation_test_adapter_rationale_361",
+      "community": 95,
+      "norm_label": "\u4fdd\u5b58\u6d4b\u8bd5\u7ed3\u679c                  args:             output_path: \u8f93\u51fa\u8def\u5f84"
+    },
+    {
+      "label": "polymarket_api.py",
+      "file_type": "code",
+      "source_file": "pangtong-value/research/task-20260329-polymarket-monitor/zhaoyun/polymarket_api.py",
+      "source_location": "L1",
+      "id": "pangtong_value_research_task_20260329_polymarket_monitor_zhaoyun_polymarket_api_py",
+      "community": 543,
+      "norm_label": "polymarket_api.py"
+    },
+    {
+      "label": "polymarket-monitor.py",
+      "file_type": "code",
+      "source_file": "pangtong-value/research/task-20260329-polymarket-monitor/zhaoyun/polymarket-monitor.py",
+      "source_location": "L1",
+      "id": "pangtong_value_research_task_20260329_polymarket_monitor_zhaoyun_polymarket_monitor_py",
+      "community": 544,
+      "norm_label": "polymarket-monitor.py"
+    },
+    {
+      "label": "pine_to_python_examples.py",
+      "file_type": "code",
+      "source_file": "pangtong-value/research/tradingview-analysis-20260326/jiangwei/pine_to_python_examples.py",
+      "source_location": "L1",
+      "id": "pangtong_value_research_tradingview_analysis_20260326_jiangwei_pine_to_python_examples_py",
+      "community": 87,
+      "norm_label": "pine_to_python_examples.py"
+    },
+    {
+      "label": "get_sample_data()",
+      "file_type": "code",
+      "source_file": "pangtong-value/research/tradingview-analysis-20260326/jiangwei/pine_to_python_examples.py",
+      "source_location": "L11",
+      "id": "jiangwei_pine_to_python_examples_get_sample_data",
+      "community": 87,
+      "norm_label": "get_sample_data()"
+    },
+    {
+      "label": "sma()",
+      "file_type": "code",
+      "source_file": "pangtong-value/research/tradingview-analysis-20260326/jiangwei/pine_to_python_examples.py",
+      "source_location": "L33",
+      "id": "jiangwei_pine_to_python_examples_sma",
+      "community": 87,
+      "norm_label": "sma()"
+    },
+    {
+      "label": "ema()",
+      "file_type": "code",
+      "source_file": "pangtong-value/research/tradingview-analysis-20260326/jiangwei/pine_to_python_examples.py",
+      "source_location": "L38",
+      "id": "jiangwei_pine_to_python_examples_ema",
+      "community": 87,
+      "norm_label": "ema()"
+    },
+    {
+      "label": "rsi()",
+      "file_type": "code",
+      "source_file": "pangtong-value/research/tradingview-analysis-20260326/jiangwei/pine_to_python_examples.py",
+      "source_location": "L43",
+      "id": "jiangwei_pine_to_python_examples_rsi",
+      "community": 87,
+      "norm_label": "rsi()"
+    },
+    {
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+      "file_type": "code",
+      "source_file": "pangtong-value/research/tradingview-analysis-20260326/jiangwei/pine_to_python_examples.py",
+      "source_location": "L53",
+      "id": "jiangwei_pine_to_python_examples_macd",
+      "community": 87,
+      "norm_label": "macd()"
+    },
+    {
+      "label": "example_ma()",
+      "file_type": "code",
+      "source_file": "pangtong-value/research/tradingview-analysis-20260326/jiangwei/pine_to_python_examples.py",
+      "source_location": "L63",
+      "id": "jiangwei_pine_to_python_examples_example_ma",
+      "community": 87,
+      "norm_label": "example_ma()"
+    },
+    {
+      "label": "example_rsi()",
+      "file_type": "code",
+      "source_file": "pangtong-value/research/tradingview-analysis-20260326/jiangwei/pine_to_python_examples.py",
+      "source_location": "L77",
+      "id": "jiangwei_pine_to_python_examples_example_rsi",
+      "community": 87,
+      "norm_label": "example_rsi()"
+    },
+    {
+      "label": "example_macd()",
+      "file_type": "code",
+      "source_file": "pangtong-value/research/tradingview-analysis-20260326/jiangwei/pine_to_python_examples.py",
+      "source_location": "L90",
+      "id": "jiangwei_pine_to_python_examples_example_macd",
+      "community": 87,
+      "norm_label": "example_macd()"
+    },
+    {
+      "label": "plot_examples()",
+      "file_type": "code",
+      "source_file": "pangtong-value/research/tradingview-analysis-20260326/jiangwei/pine_to_python_examples.py",
+      "source_location": "L104",
+      "id": "jiangwei_pine_to_python_examples_plot_examples",
+      "community": 87,
+      "norm_label": "plot_examples()"
+    },
+    {
+      "label": "main()",
+      "file_type": "code",
+      "source_file": "pangtong-value/research/tradingview-analysis-20260326/jiangwei/pine_to_python_examples.py",
+      "source_location": "L139",
+      "id": "jiangwei_pine_to_python_examples_main",
+      "community": 87,
+      "norm_label": "main()"
+    },
+    {
+      "label": "Pine Script to Python Conversion Examples Common Indicators: MA, RSI, MACD",
+      "file_type": "rationale",
+      "source_file": "pangtong-value/research/tradingview-analysis-20260326/jiangwei/pine_to_python_examples.py",
+      "source_location": "L1",
+      "id": "jiangwei_pine_to_python_examples_rationale_1",
+      "community": 87,
+      "norm_label": "pine script to python conversion examples common indicators: ma, rsi, macd"
+    },
+    {
+      "label": "Generate sample historical data for testing (no external dependencies)",
+      "file_type": "rationale",
+      "source_file": "pangtong-value/research/tradingview-analysis-20260326/jiangwei/pine_to_python_examples.py",
+      "source_location": "L12",
+      "id": "jiangwei_pine_to_python_examples_rationale_12",
+      "community": 87,
+      "norm_label": "generate sample historical data for testing (no external dependencies)"
+    },
+    {
+      "label": "Calculate Simple Moving Average (SMA)",
+      "file_type": "rationale",
+      "source_file": "pangtong-value/research/tradingview-analysis-20260326/jiangwei/pine_to_python_examples.py",
+      "source_location": "L34",
+      "id": "jiangwei_pine_to_python_examples_rationale_34",
+      "community": 87,
+      "norm_label": "calculate simple moving average (sma)"
+    },
+    {
+      "label": "Calculate Exponential Moving Average (EMA)",
+      "file_type": "rationale",
+      "source_file": "pangtong-value/research/tradingview-analysis-20260326/jiangwei/pine_to_python_examples.py",
+      "source_location": "L39",
+      "id": "jiangwei_pine_to_python_examples_rationale_39",
+      "community": 87,
+      "norm_label": "calculate exponential moving average (ema)"
+    },
+    {
+      "label": "Calculate Relative Strength Index (RSI)",
+      "file_type": "rationale",
+      "source_file": "pangtong-value/research/tradingview-analysis-20260326/jiangwei/pine_to_python_examples.py",
+      "source_location": "L44",
+      "id": "jiangwei_pine_to_python_examples_rationale_44",
+      "community": 87,
+      "norm_label": "calculate relative strength index (rsi)"
+    },
+    {
+      "label": "Calculate MACD (Moving Average Convergence Divergence)",
+      "file_type": "rationale",
+      "source_file": "pangtong-value/research/tradingview-analysis-20260326/jiangwei/pine_to_python_examples.py",
+      "source_location": "L54",
+      "id": "jiangwei_pine_to_python_examples_rationale_54",
+      "community": 87,
+      "norm_label": "calculate macd (moving average convergence divergence)"
+    },
+    {
+      "label": "Moving Average (MA) Example          Pine Script:     ma5 = ta.sma(close, 5)",
+      "file_type": "rationale",
+      "source_file": "pangtong-value/research/tradingview-analysis-20260326/jiangwei/pine_to_python_examples.py",
+      "source_location": "L64",
+      "id": "jiangwei_pine_to_python_examples_rationale_64",
+      "community": 87,
+      "norm_label": "moving average (ma) example          pine script:     ma5 = ta.sma(close, 5)"
+    },
+    {
+      "label": "RSI (Relative Strength Index) Example          Pine Script:     rsiVal = ta.rsi(",
+      "file_type": "rationale",
+      "source_file": "pangtong-value/research/tradingview-analysis-20260326/jiangwei/pine_to_python_examples.py",
+      "source_location": "L78",
+      "id": "jiangwei_pine_to_python_examples_rationale_78",
+      "community": 87,
+      "norm_label": "rsi (relative strength index) example          pine script:     rsival = ta.rsi("
+    },
+    {
+      "label": "MACD (Moving Average Convergence Divergence) Example          Pine Script:     [",
+      "file_type": "rationale",
+      "source_file": "pangtong-value/research/tradingview-analysis-20260326/jiangwei/pine_to_python_examples.py",
+      "source_location": "L91",
+      "id": "jiangwei_pine_to_python_examples_rationale_91",
+      "community": 87,
+      "norm_label": "macd (moving average convergence divergence) example          pine script:     ["
+    },
+    {
+      "label": "selection_methods_backtest.py",
+      "file_type": "code",
+      "source_file": "pangtong-value/scripts/selection_methods_backtest.py",
+      "source_location": "L1",
+      "id": "pangtong_value_scripts_selection_methods_backtest_py",
+      "community": 185,
+      "norm_label": "selection_methods_backtest.py"
+    },
+    {
+      "label": "ValueInvestingBacktest",
+      "file_type": "code",
+      "source_file": "pangtong-value/scripts/selection_methods_backtest.py",
+      "source_location": "L13",
+      "id": "scripts_selection_methods_backtest_valueinvestingbacktest",
+      "community": 185,
+      "norm_label": "valueinvestingbacktest"
+    },
+    {
+      "label": ".__init__()",
+      "file_type": "code",
+      "source_file": "pangtong-value/scripts/selection_methods_backtest.py",
+      "source_location": "L16",
+      "id": "scripts_selection_methods_backtest_valueinvestingbacktest_init",
+      "community": 185,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": ".generate_historical_data()",
+      "file_type": "code",
+      "source_file": "pangtong-value/scripts/selection_methods_backtest.py",
+      "source_location": "L22",
+      "id": "scripts_selection_methods_backtest_valueinvestingbacktest_generate_historical_data",
+      "community": 185,
+      "norm_label": ".generate_historical_data()"
+    },
+    {
+      "label": ".calculate_factors()",
+      "file_type": "code",
+      "source_file": "pangtong-value/scripts/selection_methods_backtest.py",
+      "source_location": "L89",
+      "id": "scripts_selection_methods_backtest_valueinvestingbacktest_calculate_factors",
+      "community": 185,
+      "norm_label": ".calculate_factors()"
+    },
+    {
+      "label": ".test_selection_methods()",
+      "file_type": "code",
+      "source_file": "pangtong-value/scripts/selection_methods_backtest.py",
+      "source_location": "L125",
+      "id": "scripts_selection_methods_backtest_valueinvestingbacktest_test_selection_methods",
+      "community": 185,
+      "norm_label": ".test_selection_methods()"
+    },
+    {
+      "label": ".calculate_performance()",
+      "file_type": "code",
+      "source_file": "pangtong-value/scripts/selection_methods_backtest.py",
+      "source_location": "L167",
+      "id": "scripts_selection_methods_backtest_valueinvestingbacktest_calculate_performance",
+      "community": 185,
+      "norm_label": ".calculate_performance()"
+    },
+    {
+      "label": ".run_backtest()",
+      "file_type": "code",
+      "source_file": "pangtong-value/scripts/selection_methods_backtest.py",
+      "source_location": "L199",
+      "id": "scripts_selection_methods_backtest_valueinvestingbacktest_run_backtest",
+      "community": 185,
+      "norm_label": ".run_backtest()"
+    },
+    {
+      "label": ".output_results()",
+      "file_type": "code",
+      "source_file": "pangtong-value/scripts/selection_methods_backtest.py",
+      "source_location": "L219",
+      "id": "scripts_selection_methods_backtest_valueinvestingbacktest_output_results",
+      "community": 185,
+      "norm_label": ".output_results()"
+    },
+    {
+      "label": ".save_results()",
+      "file_type": "code",
+      "source_file": "pangtong-value/scripts/selection_methods_backtest.py",
+      "source_location": "L311",
+      "id": "scripts_selection_methods_backtest_valueinvestingbacktest_save_results",
+      "community": 185,
+      "norm_label": ".save_results()"
+    },
+    {
+      "label": "main()",
+      "file_type": "code",
+      "source_file": "pangtong-value/scripts/selection_methods_backtest.py",
+      "source_location": "L343",
+      "id": "scripts_selection_methods_backtest_main",
+      "community": 185,
+      "norm_label": "main()"
+    },
+    {
+      "label": "super_financial_agent.py",
+      "file_type": "code",
+      "source_file": "pangtong-value/scripts/super_financial_agent.py",
+      "source_location": "L1",
+      "id": "pangtong_value_scripts_super_financial_agent_py",
+      "community": 253,
+      "norm_label": "super_financial_agent.py"
+    },
+    {
+      "label": "SuperFinancialAgent",
+      "file_type": "code",
+      "source_file": "pangtong-value/scripts/super_financial_agent.py",
+      "source_location": "L18",
+      "id": "scripts_super_financial_agent_superfinancialagent",
+      "community": 253,
+      "norm_label": "superfinancialagent"
+    },
+    {
+      "label": ".__init__()",
+      "file_type": "code",
+      "source_file": "pangtong-value/scripts/super_financial_agent.py",
+      "source_location": "L21",
+      "id": "scripts_super_financial_agent_superfinancialagent_init",
+      "community": 253,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": ".calculate_valuation_factors()",
+      "file_type": "code",
+      "source_file": "pangtong-value/scripts/super_financial_agent.py",
+      "source_location": "L30",
+      "id": "scripts_super_financial_agent_superfinancialagent_calculate_valuation_factors",
+      "community": 253,
+      "norm_label": ".calculate_valuation_factors()"
+    },
+    {
+      "label": ".calculate_quality_factors()",
+      "file_type": "code",
+      "source_file": "pangtong-value/scripts/super_financial_agent.py",
+      "source_location": "L51",
+      "id": "scripts_super_financial_agent_superfinancialagent_calculate_quality_factors",
+      "community": 253,
+      "norm_label": ".calculate_quality_factors()"
+    },
+    {
+      "label": ".calculate_growth_factors()",
+      "file_type": "code",
+      "source_file": "pangtong-value/scripts/super_financial_agent.py",
+      "source_location": "L72",
+      "id": "scripts_super_financial_agent_superfinancialagent_calculate_growth_factors",
+      "community": 253,
+      "norm_label": ".calculate_growth_factors()"
+    },
+    {
+      "label": ".calculate_risk_factors()",
+      "file_type": "code",
+      "source_file": "pangtong-value/scripts/super_financial_agent.py",
+      "source_location": "L88",
+      "id": "scripts_super_financial_agent_superfinancialagent_calculate_risk_factors",
+      "community": 253,
+      "norm_label": ".calculate_risk_factors()"
+    },
+    {
+      "label": ".parallel_factor_calculation()",
+      "file_type": "code",
+      "source_file": "pangtong-value/scripts/super_financial_agent.py",
+      "source_location": "L104",
+      "id": "scripts_super_financial_agent_superfinancialagent_parallel_factor_calculation",
+      "community": 253,
+      "norm_label": ".parallel_factor_calculation()"
+    },
+    {
+      "label": "main()",
+      "file_type": "code",
+      "source_file": "pangtong-value/scripts/super_financial_agent.py",
+      "source_location": "L132",
+      "id": "scripts_super_financial_agent_main",
+      "community": 253,
+      "norm_label": "main()"
+    },
+    {
+      "label": "dynamic_stock_selection.py",
+      "file_type": "code",
+      "source_file": "pangtong-value/scripts/dynamic_stock_selection.py",
+      "source_location": "L1",
+      "id": "pangtong_value_scripts_dynamic_stock_selection_py",
+      "community": 172,
+      "norm_label": "dynamic_stock_selection.py"
+    },
+    {
+      "label": "DynamicStockSelection",
+      "file_type": "code",
+      "source_file": "pangtong-value/scripts/dynamic_stock_selection.py",
+      "source_location": "L13",
+      "id": "scripts_dynamic_stock_selection_dynamicstockselection",
+      "community": 172,
+      "norm_label": "dynamicstockselection"
+    },
+    {
+      "label": ".__init__()",
+      "file_type": "code",
+      "source_file": "pangtong-value/scripts/dynamic_stock_selection.py",
+      "source_location": "L16",
+      "id": "scripts_dynamic_stock_selection_dynamicstockselection_init",
+      "community": 172,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": ".load_data()",
+      "file_type": "code",
+      "source_file": "pangtong-value/scripts/dynamic_stock_selection.py",
+      "source_location": "L22",
+      "id": "scripts_dynamic_stock_selection_dynamicstockselection_load_data",
+      "community": 172,
+      "norm_label": ".load_data()"
+    },
+    {
+      "label": ".calculate_factors()",
+      "file_type": "code",
+      "source_file": "pangtong-value/scripts/dynamic_stock_selection.py",
+      "source_location": "L53",
+      "id": "scripts_dynamic_stock_selection_dynamicstockselection_calculate_factors",
+      "community": 172,
+      "norm_label": ".calculate_factors()"
+    },
+    {
+      "label": ".apply_filters()",
+      "file_type": "code",
+      "source_file": "pangtong-value/scripts/dynamic_stock_selection.py",
+      "source_location": "L97",
+      "id": "scripts_dynamic_stock_selection_dynamicstockselection_apply_filters",
+      "community": 172,
+      "norm_label": ".apply_filters()"
+    },
+    {
+      "label": ".portfolio_construction()",
+      "file_type": "code",
+      "source_file": "pangtong-value/scripts/dynamic_stock_selection.py",
+      "source_location": "L128",
+      "id": "scripts_dynamic_stock_selection_dynamicstockselection_portfolio_construction",
+      "community": 172,
+      "norm_label": ".portfolio_construction()"
+    },
+    {
+      "label": ".strategy_variants()",
+      "file_type": "code",
+      "source_file": "pangtong-value/scripts/dynamic_stock_selection.py",
+      "source_location": "L160",
+      "id": "scripts_dynamic_stock_selection_dynamicstockselection_strategy_variants",
+      "community": 172,
+      "norm_label": ".strategy_variants()"
+    },
+    {
+      "label": ".run()",
+      "file_type": "code",
+      "source_file": "pangtong-value/scripts/dynamic_stock_selection.py",
+      "source_location": "L191",
+      "id": "scripts_dynamic_stock_selection_dynamicstockselection_run",
+      "community": 172,
+      "norm_label": ".run()"
+    },
+    {
+      "label": ".output_results()",
+      "file_type": "code",
+      "source_file": "pangtong-value/scripts/dynamic_stock_selection.py",
+      "source_location": "L217",
+      "id": "scripts_dynamic_stock_selection_dynamicstockselection_output_results",
+      "community": 172,
+      "norm_label": ".output_results()"
+    },
+    {
+      "label": ".save_results()",
+      "file_type": "code",
+      "source_file": "pangtong-value/scripts/dynamic_stock_selection.py",
+      "source_location": "L264",
+      "id": "scripts_dynamic_stock_selection_dynamicstockselection_save_results",
+      "community": 172,
+      "norm_label": ".save_results()"
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+    {
+      "label": "main()",
+      "file_type": "code",
+      "source_file": "pangtong-value/scripts/dynamic_stock_selection.py",
+      "source_location": "L294",
+      "id": "scripts_dynamic_stock_selection_main",
+      "community": 172,
+      "norm_label": "main()"
+    },
+    {
+      "label": "multi_factor_scoring_model.py",
+      "file_type": "code",
+      "source_file": "pangtong-value/scripts/multi_factor_scoring_model.py",
+      "source_location": "L1",
+      "id": "pangtong_value_scripts_multi_factor_scoring_model_py",
+      "community": 186,
+      "norm_label": "multi_factor_scoring_model.py"
+    },
+    {
+      "label": "MultiFactorScoringModel",
+      "file_type": "code",
+      "source_file": "pangtong-value/scripts/multi_factor_scoring_model.py",
+      "source_location": "L13",
+      "id": "scripts_multi_factor_scoring_model_multifactorscoringmodel",
+      "community": 186,
+      "norm_label": "multifactorscoringmodel"
+    },
+    {
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+      "label": "StockSelectionBacktest",
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+      "community": 148,
+      "norm_label": "value_investing_backtest.py"
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+    {
+      "label": "ValueInvestingBacktest",
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+      "source_file": "pangtong-value/scripts/value_investing_backtest.py",
+      "source_location": "L13",
+      "id": "scripts_value_investing_backtest_valueinvestingbacktest",
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+      "source_location": "L22",
+      "id": "scripts_value_investing_backtest_valueinvestingbacktest_generate_price_data",
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+      "id": "scripts_value_investing_backtest_valueinvestingbacktest_calculate_metrics",
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+      "label": "run_backtest_auto.py",
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+      "id": "scripts_run_backtest_auto_py",
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+      "norm_label": "run_backtest_auto.py"
+    },
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+      "source_location": "L28",
+      "id": "scripts_run_backtest_auto_run_backtest",
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+      "source_location": "L171",
+      "id": "scripts_run_backtest_auto_main",
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+      "norm_label": "main()"
+    },
+    {
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+      "file_type": "code",
+      "source_file": "zhangfei-technical/research/task-20260417-atr-indicator/test_atr.py",
+      "source_location": "L1",
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+    {
+      "label": "test_tr_calculate_tr_basic()",
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+      "source_location": "L11",
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+      "community": 13,
+      "norm_label": "test_tr_calculate_tr_basic()"
+    },
+    {
+      "label": "test_tr_pandas_series()",
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+      "source_location": "L33",
+      "id": "task_20260417_atr_indicator_test_atr_test_tr_pandas_series",
+      "community": 13,
+      "norm_label": "test_tr_pandas_series()"
+    },
+    {
+      "label": "test_invalid_period()",
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+      "source_location": "L46",
+      "id": "task_20260417_atr_indicator_test_atr_test_invalid_period",
+      "community": 13,
+      "norm_label": "test_invalid_period()"
+    },
+    {
+      "label": "test_invalid_method()",
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+      "source_location": "L55",
+      "id": "task_20260417_atr_indicator_test_atr_test_invalid_method",
+      "community": 13,
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+    {
+      "label": "test_length_mismatch()",
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+      "community": 13,
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+    {
+      "label": "test_sma_atr_basic()",
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+    {
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+      "community": 13,
+      "norm_label": "test_ema_atr_basic()"
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+    {
+      "label": "test_ema_incremental_update()",
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+      "source_location": "L116",
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+      "community": 13,
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+    {
+      "label": "test_sma_incremental_error()",
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+      "source_location": "L151",
+      "id": "task_20260417_atr_indicator_test_atr_test_sma_incremental_error",
+      "community": 13,
+      "norm_label": "test_sma_incremental_error()"
+    },
+    {
+      "label": "test_calculate_atr_convenience()",
+      "file_type": "code",
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+      "id": "task_20260417_atr_indicator_test_atr_test_calculate_atr_convenience",
+      "community": 13,
+      "norm_label": "test_calculate_atr_convenience()"
+    },
+    {
+      "label": "test_short_data()",
+      "file_type": "code",
+      "source_file": "zhangfei-technical/research/task-20260417-atr-indicator/test_atr.py",
+      "source_location": "L177",
+      "id": "task_20260417_atr_indicator_test_atr_test_short_data",
+      "community": 13,
+      "norm_label": "test_short_data()"
+    },
+    {
+      "label": "example.py",
+      "file_type": "code",
+      "source_file": "zhangfei-technical/research/task-20260417-atr-indicator/example.py",
+      "source_location": "L1",
+      "id": "zhangfei_technical_research_task_20260417_atr_indicator_example_py",
+      "community": 13,
+      "norm_label": "example.py"
+    },
+    {
+      "label": "generate_sample_data()",
+      "file_type": "code",
+      "source_file": "zhangfei-technical/research/task-20260417-atr-indicator/example.py",
+      "source_location": "L11",
+      "id": "task_20260417_atr_indicator_example_generate_sample_data",
+      "community": 13,
+      "norm_label": "generate_sample_data()"
+    },
+    {
+      "label": "example_basic_usage()",
+      "file_type": "code",
+      "source_file": "zhangfei-technical/research/task-20260417-atr-indicator/example.py",
+      "source_location": "L39",
+      "id": "task_20260417_atr_indicator_example_example_basic_usage",
+      "community": 13,
+      "norm_label": "example_basic_usage()"
+    },
+    {
+      "label": "example_compare_methods()",
+      "file_type": "code",
+      "source_file": "zhangfei-technical/research/task-20260417-atr-indicator/example.py",
+      "source_location": "L70",
+      "id": "task_20260417_atr_indicator_example_example_compare_methods",
+      "community": 13,
+      "norm_label": "example_compare_methods()"
+    },
+    {
+      "label": "example_convenience_function()",
+      "file_type": "code",
+      "source_file": "zhangfei-technical/research/task-20260417-atr-indicator/example.py",
+      "source_location": "L100",
+      "id": "task_20260417_atr_indicator_example_example_convenience_function",
+      "community": 13,
+      "norm_label": "example_convenience_function()"
+    },
+    {
+      "label": "example_incremental_update()",
+      "file_type": "code",
+      "source_file": "zhangfei-technical/research/task-20260417-atr-indicator/example.py",
+      "source_location": "L120",
+      "id": "task_20260417_atr_indicator_example_example_incremental_update",
+      "community": 13,
+      "norm_label": "example_incremental_update()"
+    },
+    {
+      "label": "main()",
+      "file_type": "code",
+      "source_file": "zhangfei-technical/research/task-20260417-atr-indicator/example.py",
+      "source_location": "L144",
+      "id": "task_20260417_atr_indicator_example_main",
+      "community": 13,
+      "norm_label": "main()"
+    },
+    {
+      "label": "ATR\u6307\u6807\u8ba1\u7b97\u793a\u4f8b\u4ee3\u7801 \u6f14\u793a\u5982\u4f55\u4f7f\u7528ATRIndicator\u7c7b\u8ba1\u7b97ATR\u6307\u6807",
+      "file_type": "rationale",
+      "source_file": "zhangfei-technical/research/task-20260417-atr-indicator/example.py",
+      "source_location": "L1",
+      "id": "task_20260417_atr_indicator_example_rationale_1",
+      "community": 13,
+      "norm_label": "atr\u6307\u6807\u8ba1\u7b97\u793a\u4f8b\u4ee3\u7801 \u6f14\u793a\u5982\u4f55\u4f7f\u7528atrindicator\u7c7b\u8ba1\u7b97atr\u6307\u6807"
+    },
+    {
+      "label": "atr_indicator.py",
+      "file_type": "code",
+      "source_file": "zhangfei-technical/research/task-20260417-atr-indicator/atr_indicator.py",
+      "source_location": "L1",
+      "id": "zhangfei_technical_research_task_20260417_atr_indicator_atr_indicator_py",
+      "community": 13,
+      "norm_label": "atr_indicator.py"
+    },
+    {
+      "label": "ATRIndicator",
+      "file_type": "code",
+      "source_file": "zhangfei-technical/research/task-20260417-atr-indicator/atr_indicator.py",
+      "source_location": "L14",
+      "id": "task_20260417_atr_indicator_atr_indicator_atrindicator",
+      "community": 13,
+      "norm_label": "atrindicator"
+    },
+    {
+      "label": ".__init__()",
+      "file_type": "code",
+      "source_file": "zhangfei-technical/research/task-20260417-atr-indicator/atr_indicator.py",
+      "source_location": "L23",
+      "id": "task_20260417_atr_indicator_atr_indicator_atrindicator_init",
+      "community": 13,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": "calculate_tr()",
+      "file_type": "code",
+      "source_file": "zhangfei-technical/research/task-20260417-atr-indicator/atr_indicator.py",
+      "source_location": "L44",
+      "id": "task_20260417_atr_indicator_atr_indicator_calculate_tr",
+      "community": 13,
+      "norm_label": "calculate_tr()"
+    },
+    {
+      "label": "_calculate_tr_numpy()",
+      "file_type": "code",
+      "source_file": "zhangfei-technical/research/task-20260417-atr-indicator/atr_indicator.py",
+      "source_location": "L72",
+      "id": "task_20260417_atr_indicator_atr_indicator_calculate_tr_numpy",
+      "community": 13,
+      "norm_label": "_calculate_tr_numpy()"
+    },
+    {
+      "label": ".calculate()",
+      "file_type": "code",
+      "source_file": "zhangfei-technical/research/task-20260417-atr-indicator/atr_indicator.py",
+      "source_location": "L97",
+      "id": "task_20260417_atr_indicator_atr_indicator_atrindicator_calculate",
+      "community": 13,
+      "norm_label": ".calculate()"
+    },
+    {
+      "label": "._calculate_sma_atr()",
+      "file_type": "code",
+      "source_file": "zhangfei-technical/research/task-20260417-atr-indicator/atr_indicator.py",
+      "source_location": "L122",
+      "id": "task_20260417_atr_indicator_atr_indicator_atrindicator_calculate_sma_atr",
+      "community": 13,
+      "norm_label": "._calculate_sma_atr()"
+    },
+    {
+      "label": "._calculate_ema_atr()",
+      "file_type": "code",
+      "source_file": "zhangfei-technical/research/task-20260417-atr-indicator/atr_indicator.py",
+      "source_location": "L140",
+      "id": "task_20260417_atr_indicator_atr_indicator_atrindicator_calculate_ema_atr",
+      "community": 13,
+      "norm_label": "._calculate_ema_atr()"
+    },
+    {
+      "label": "._calculate_ema_atr_pandas()",
+      "file_type": "code",
+      "source_file": "zhangfei-technical/research/task-20260417-atr-indicator/atr_indicator.py",
+      "source_location": "L147",
+      "id": "task_20260417_atr_indicator_atr_indicator_atrindicator_calculate_ema_atr_pandas",
+      "community": 13,
+      "norm_label": "._calculate_ema_atr_pandas()"
+    },
+    {
+      "label": "._calculate_ema_atr_numpy()",
+      "file_type": "code",
+      "source_file": "zhangfei-technical/research/task-20260417-atr-indicator/atr_indicator.py",
+      "source_location": "L175",
+      "id": "task_20260417_atr_indicator_atr_indicator_atrindicator_calculate_ema_atr_numpy",
+      "community": 13,
+      "norm_label": "._calculate_ema_atr_numpy()"
+    },
+    {
+      "label": ".get_last_atr()",
+      "file_type": "code",
+      "source_file": "zhangfei-technical/research/task-20260417-atr-indicator/atr_indicator.py",
+      "source_location": "L201",
+      "id": "task_20260417_atr_indicator_atr_indicator_atrindicator_get_last_atr",
+      "community": 13,
+      "norm_label": ".get_last_atr()"
+    },
+    {
+      "label": ".update()",
+      "file_type": "code",
+      "source_file": "zhangfei-technical/research/task-20260417-atr-indicator/atr_indicator.py",
+      "source_location": "L205",
+      "id": "task_20260417_atr_indicator_atr_indicator_atrindicator_update",
+      "community": 13,
+      "norm_label": ".update()"
+    },
+    {
+      "label": "calculate_atr()",
+      "file_type": "code",
+      "source_file": "zhangfei-technical/research/task-20260417-atr-indicator/atr_indicator.py",
+      "source_location": "L239",
+      "id": "task_20260417_atr_indicator_atr_indicator_calculate_atr",
+      "community": 13,
+      "norm_label": "calculate_atr()"
+    },
+    {
+      "label": "ATR (Average True Range) \u6307\u6807\u8ba1\u7b97\u5de5\u5177 \u652f\u6301SMA\u548cEMA\u4e24\u79cd\u8ba1\u7b97\u65b9\u5f0f  Author: \u5f20\u98de \u7ffc\u5fb7 Date: 2026-04-17",
+      "file_type": "rationale",
+      "source_file": "zhangfei-technical/research/task-20260417-atr-indicator/atr_indicator.py",
+      "source_location": "L1",
+      "id": "task_20260417_atr_indicator_atr_indicator_rationale_1",
+      "community": 13,
+      "norm_label": "atr (average true range) \u6307\u6807\u8ba1\u7b97\u5de5\u5177 \u652f\u6301sma\u548cema\u4e24\u79cd\u8ba1\u7b97\u65b9\u5f0f  author: \u5f20\u98de \u7ffc\u5fb7 date: 2026-04-17"
+    },
+    {
+      "label": "ATR (Average True Range) \u6307\u6807\u8ba1\u7b97\u7c7b          \u652f\u6301\u4e24\u79cd\u8ba1\u7b97\u65b9\u5f0f\uff1a     - SMA: \u7b80\u5355\u79fb\u52a8\u5e73\u5747     - EMA: \u6307",
+      "file_type": "rationale",
+      "source_file": "zhangfei-technical/research/task-20260417-atr-indicator/atr_indicator.py",
+      "source_location": "L15",
+      "id": "task_20260417_atr_indicator_atr_indicator_rationale_15",
+      "community": 13,
+      "norm_label": "atr (average true range) \u6307\u6807\u8ba1\u7b97\u7c7b          \u652f\u6301\u4e24\u79cd\u8ba1\u7b97\u65b9\u5f0f:     - sma: \u7b80\u5355\u79fb\u52a8\u5e73\u5747     - ema: \u6307"
+    },
+    {
+      "label": "\u521d\u59cb\u5316ATR\u6307\u6807                  Parameters:             period: int, \u9ed8\u8ba414",
+      "file_type": "rationale",
+      "source_file": "zhangfei-technical/research/task-20260417-atr-indicator/atr_indicator.py",
+      "source_location": "L24",
+      "id": "task_20260417_atr_indicator_atr_indicator_rationale_24",
+      "community": 13,
+      "norm_label": "\u521d\u59cb\u5316atr\u6307\u6807                  parameters:             period: int, \u9ed8\u8ba414"
+    },
+    {
+      "label": "\u8ba1\u7b97True Range (TR)                  \u516c\u5f0f: TR = max[|high - low|, |high - prev_close",
+      "file_type": "rationale",
+      "source_file": "zhangfei-technical/research/task-20260417-atr-indicator/atr_indicator.py",
+      "source_location": "L49",
+      "id": "task_20260417_atr_indicator_atr_indicator_rationale_49",
+      "community": 545,
+      "norm_label": "\u8ba1\u7b97true range (tr)                  \u516c\u5f0f: tr = max[|high - low|, |high - prev_close"
+    },
+    {
+      "label": "\u8ba1\u7b97ATR\u6307\u6807                  Parameters:             high: \u6700\u9ad8\u4ef7\u5e8f\u5217             low: \u6700\u4f4e",
+      "file_type": "rationale",
+      "source_file": "zhangfei-technical/research/task-20260417-atr-indicator/atr_indicator.py",
+      "source_location": "L103",
+      "id": "task_20260417_atr_indicator_atr_indicator_rationale_103",
+      "community": 13,
+      "norm_label": "\u8ba1\u7b97atr\u6307\u6807                  parameters:             high: \u6700\u9ad8\u4ef7\u5e8f\u5217             low: \u6700\u4f4e"
+    },
+    {
+      "label": "\u4f7f\u7528EMA\u8ba1\u7b97ATR\uff0cWilder\u5e73\u6ed1\u65b9\u6cd5",
+      "file_type": "rationale",
+      "source_file": "zhangfei-technical/research/task-20260417-atr-indicator/atr_indicator.py",
+      "source_location": "L141",
+      "id": "task_20260417_atr_indicator_atr_indicator_rationale_141",
+      "community": 13,
+      "norm_label": "\u4f7f\u7528ema\u8ba1\u7b97atr,wilder\u5e73\u6ed1\u65b9\u6cd5"
+    },
+    {
+      "label": "Pandas\u7248\u672cEMA-ATR\u8ba1\u7b97\uff0c\u4f7f\u7528Wilder\u5e73\u6ed1",
+      "file_type": "rationale",
+      "source_file": "zhangfei-technical/research/task-20260417-atr-indicator/atr_indicator.py",
+      "source_location": "L148",
+      "id": "task_20260417_atr_indicator_atr_indicator_rationale_148",
+      "community": 13,
+      "norm_label": "pandas\u7248\u672cema-atr\u8ba1\u7b97,\u4f7f\u7528wilder\u5e73\u6ed1"
+    },
+    {
+      "label": "Numpy\u7248\u672cEMA-ATR\u8ba1\u7b97\uff0c\u4f7f\u7528Wilder\u5e73\u6ed1",
+      "file_type": "rationale",
+      "source_file": "zhangfei-technical/research/task-20260417-atr-indicator/atr_indicator.py",
+      "source_location": "L176",
+      "id": "task_20260417_atr_indicator_atr_indicator_rationale_176",
+      "community": 13,
+      "norm_label": "numpy\u7248\u672cema-atr\u8ba1\u7b97,\u4f7f\u7528wilder\u5e73\u6ed1"
+    },
+    {
+      "label": "\u66f4\u65b0\u5355\u4e2aATR\u503c\uff08\u5b9e\u76d8\u65f6\u589e\u91cf\u66f4\u65b0\u4f7f\u7528\uff09                  Parameters:             high: \u5f53\u524dK\u7ebf\u6700\u9ad8\u4ef7",
+      "file_type": "rationale",
+      "source_file": "zhangfei-technical/research/task-20260417-atr-indicator/atr_indicator.py",
+      "source_location": "L206",
+      "id": "task_20260417_atr_indicator_atr_indicator_rationale_206",
+      "community": 13,
+      "norm_label": "\u66f4\u65b0\u5355\u4e2aatr\u503c(\u5b9e\u76d8\u65f6\u589e\u91cf\u66f4\u65b0\u4f7f\u7528)                  parameters:             high: \u5f53\u524dk\u7ebf\u6700\u9ad8\u4ef7"
+    },
+    {
+      "label": "\u4fbf\u6377\u51fd\u6570\uff1a\u76f4\u63a5\u5bf9DataFrame\u8ba1\u7b97ATR\u5e76\u6dfb\u52a0\u5230\u539fDataFrame          Parameters:         df: \u8f93\u5165DataFram",
+      "file_type": "rationale",
+      "source_file": "zhangfei-technical/research/task-20260417-atr-indicator/atr_indicator.py",
+      "source_location": "L248",
+      "id": "task_20260417_atr_indicator_atr_indicator_rationale_248",
+      "community": 13,
+      "norm_label": "\u4fbf\u6377\u51fd\u6570:\u76f4\u63a5\u5bf9dataframe\u8ba1\u7b97atr\u5e76\u6dfb\u52a0\u5230\u539fdataframe          parameters:         df: \u8f93\u5165datafram"
+    },
+    {
+      "label": "technical_selection_strategies_backtest.py",
+      "file_type": "code",
+      "source_file": "zhangfei-technical/02-algorithms/technical_selection_strategies_backtest.py",
+      "source_location": "L1",
+      "id": "zhangfei_technical_02_algorithms_technical_selection_strategies_backtest_py",
+      "community": 125,
+      "norm_label": "technical_selection_strategies_backtest.py"
+    },
+    {
+      "label": "Trade",
+      "file_type": "code",
+      "source_file": "zhangfei-technical/02-algorithms/technical_selection_strategies_backtest.py",
+      "source_location": "L24",
+      "id": "02_algorithms_technical_selection_strategies_backtest_trade",
+      "community": 125,
+      "norm_label": "trade"
+    },
+    {
+      "label": "BacktestResult",
+      "file_type": "code",
+      "source_file": "zhangfei-technical/02-algorithms/technical_selection_strategies_backtest.py",
+      "source_location": "L42",
+      "id": "02_algorithms_technical_selection_strategies_backtest_backtestresult",
+      "community": 125,
+      "norm_label": "backtestresult"
+    },
+    {
+      "label": "TechnicalIndicators",
+      "file_type": "code",
+      "source_file": "zhangfei-technical/02-algorithms/technical_selection_strategies_backtest.py",
+      "source_location": "L63",
+      "id": "02_algorithms_technical_selection_strategies_backtest_technicalindicators",
+      "community": 125,
+      "norm_label": "technicalindicators"
+    },
+    {
+      "label": "calculate_sma()",
+      "file_type": "code",
+      "source_file": "zhangfei-technical/02-algorithms/technical_selection_strategies_backtest.py",
+      "source_location": "L67",
+      "id": "02_algorithms_technical_selection_strategies_backtest_calculate_sma",
+      "community": 125,
+      "norm_label": "calculate_sma()"
+    },
+    {
+      "label": "calculate_ema()",
+      "file_type": "code",
+      "source_file": "zhangfei-technical/02-algorithms/technical_selection_strategies_backtest.py",
+      "source_location": "L72",
+      "id": "02_algorithms_technical_selection_strategies_backtest_calculate_ema",
+      "community": 125,
+      "norm_label": "calculate_ema()"
+    },
+    {
+      "label": "calculate_macd()",
+      "file_type": "code",
+      "source_file": "zhangfei-technical/02-algorithms/technical_selection_strategies_backtest.py",
+      "source_location": "L77",
+      "id": "02_algorithms_technical_selection_strategies_backtest_calculate_macd",
+      "community": 125,
+      "norm_label": "calculate_macd()"
+    },
+    {
+      "label": "calculate_bollinger_bands()",
+      "file_type": "code",
+      "source_file": "zhangfei-technical/02-algorithms/technical_selection_strategies_backtest.py",
+      "source_location": "L93",
+      "id": "02_algorithms_technical_selection_strategies_backtest_calculate_bollinger_bands",
+      "community": 125,
+      "norm_label": "calculate_bollinger_bands()"
+    },
+    {
+      "label": "calculate_donchian_channel()",
+      "file_type": "code",
+      "source_file": "zhangfei-technical/02-algorithms/technical_selection_strategies_backtest.py",
+      "source_location": "L107",
+      "id": "02_algorithms_technical_selection_strategies_backtest_calculate_donchian_channel",
+      "community": 125,
+      "norm_label": "calculate_donchian_channel()"
+    },
+    {
+      "label": "calculate_atr()",
+      "file_type": "code",
+      "source_file": "zhangfei-technical/02-algorithms/technical_selection_strategies_backtest.py",
+      "source_location": "L119",
+      "id": "02_algorithms_technical_selection_strategies_backtest_calculate_atr",
+      "community": 125,
+      "norm_label": "calculate_atr()"
+    },
+    {
+      "label": "MACDDivergenceStrategy",
+      "file_type": "code",
+      "source_file": "zhangfei-technical/02-algorithms/technical_selection_strategies_backtest.py",
+      "source_location": "L139",
+      "id": "02_algorithms_technical_selection_strategies_backtest_macddivergencestrategy",
+      "community": 125,
+      "norm_label": "macddivergencestrategy"
+    },
+    {
+      "label": ".__init__()",
+      "file_type": "code",
+      "source_file": "zhangfei-technical/02-algorithms/technical_selection_strategies_backtest.py",
+      "source_location": "L155",
+      "id": "02_algorithms_technical_selection_strategies_backtest_macddivergencestrategy_init",
+      "community": 125,
+      "norm_label": ".__init__()"
+    },
+    {
+      "label": ".check_buy_signal()",
+      "file_type": "code",
+      "source_file": "zhangfei-technical/02-algorithms/technical_selection_strategies_backtest.py",
+      "source_location": "L165",
+      "id": "02_algorithms_technical_selection_strategies_backtest_macddivergencestrategy_check_buy_signal",
+      "community": 125,
+      "norm_label": ".check_buy_signal()"
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+    },
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+      "file_type": "document",
+      "source_file": "pangtong-value/research/tradingview-analysis-20260326/simayi/QUALITY_REVIEW.md",
+      "source_location": "L13",
+      "id": "simayi_quality_review_13",
+      "community": 118,
+      "norm_label": "\u5404\u90e8\u5206\u8d28\u91cf\u5ba1\u6838"
+    },
+    {
+      "label": "3. \u59dc\u7ef4 - Pine Script\u8f6cPython\u53ef\u884c\u6027\u7814\u7a76",
+      "file_type": "document",
+      "source_file": "pangtong-value/research/tradingview-analysis-20260326/simayi/QUALITY_REVIEW.md",
+      "source_location": "L43",
+      "id": "simayi_quality_review_3_pine_script_python",
+      "community": 118,
+      "norm_label": "3. \u59dc\u7ef4 - pine script\u8f6cpython\u53ef\u884c\u6027\u7814\u7a76"
+    },
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+      "label": "\u603b\u4f53\u8bc4\u4ef7",
+      "file_type": "document",
+      "source_file": "pangtong-value/research/tradingview-analysis-20260326/simayi/QUALITY_REVIEW.md",
+      "source_location": "L58",
+      "id": "simayi_quality_review_58",
+      "community": 118,
+      "norm_label": "\u603b\u4f53\u8bc4\u4ef7"
+    },
+    {
+      "label": "report.md",
+      "file_type": "document",
+      "source_file": "pangtong-value/research/20260411-three-multiagent-projects-analysis/report.md",
+      "source_location": "L1",
+      "id": "pangtong_value_research_20260411_three_multiagent_projects_analysis_report_md",
+      "community": 17,
+      "norm_label": "report.md"
+    },
+    {
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+      "file_type": "document",
+      "source_file": "pangtong-value/research/20260411-three-multiagent-projects-analysis/report.md",
+      "source_location": "L1",
+      "id": "20260411_three_multiagent_projects_analysis_report_agent",
+      "community": 17,
+      "norm_label": "\u4e09\u4e2a\u4e3b\u6d41\u591aagent\u9879\u76ee\u534f\u4f5c\u6a21\u5f0f\u5206\u6790\u62a5\u544a"
+    },
+    {
+      "label": "\u76ee\u5f55",
+      "file_type": "document",
+      "source_file": "pangtong-value/research/20260411-three-multiagent-projects-analysis/report.md",
+      "source_location": "L9",
+      "id": "20260411_three_multiagent_projects_analysis_report",
+      "community": 17,
+      "norm_label": "\u76ee\u5f55"
+    },
+    {
+      "label": "\u4e00\u3001\u9879\u76ee\u6982\u89c8",
+      "file_type": "document",
+      "source_file": "pangtong-value/research/20260411-three-multiagent-projects-analysis/report.md",
+      "source_location": "L20",
+      "id": "20260411_three_multiagent_projects_analysis_report_20",
+      "community": 17,
+      "norm_label": "\u4e00\u3001\u9879\u76ee\u6982\u89c8"
+    },
+    {
+      "label": "\u4e8c\u3001\u591aAgent\u534f\u4f5c\u6a21\u5f0f\u5bf9\u6bd4",
+      "file_type": "document",
+      "source_file": "pangtong-value/research/20260411-three-multiagent-projects-analysis/report.md",
+      "source_location": "L30",
+      "id": "20260411_three_multiagent_projects_analysis_report_agent_30",
+      "community": 17,
+      "norm_label": "\u4e8c\u3001\u591aagent\u534f\u4f5c\u6a21\u5f0f\u5bf9\u6bd4"
+    },
+    {
+      "label": "1. Hermes Agent (NousResearch)",
+      "file_type": "document",
+      "source_file": "pangtong-value/research/20260411-three-multiagent-projects-analysis/report.md",
+      "source_location": "L32",
+      "id": "20260411_three_multiagent_projects_analysis_report_1_hermes_agent_nousresearch",
+      "community": 17,
+      "norm_label": "1. hermes agent (nousresearch)"
+    },
+    {
+      "label": "2. oh-my-codex / oh-my-claudecode",
+      "file_type": "document",
+      "source_file": "pangtong-value/research/20260411-three-multiagent-projects-analysis/report.md",
+      "source_location": "L40",
+      "id": "20260411_three_multiagent_projects_analysis_report_2_oh_my_codex_oh_my_claudecode",
+      "community": 17,
+      "norm_label": "2. oh-my-codex / oh-my-claudecode"
+    },
+    {
+      "label": "code:block1 (\u6df1\u5ea6\u8bbf\u8c08\u6f84\u6e05\u9700\u6c42 \u2192 \u5236\u5b9a\u65b9\u6848\u8ba1\u5212 \u2192 \u62c6\u89e3\u4efb\u52a1 \u2192 \u591aworker\u5e76\u884c\u6267\u884c \u2192 \u9a8c\u8bc1\u8bc4\u5ba1 \u2192 \u4fee\u590d\u5faa\u73af \u2192 \u6c47\u603b\u4ea4\u4ed8)",
+      "file_type": "document",
+      "source_file": "pangtong-value/research/20260411-three-multiagent-projects-analysis/report.md",
+      "source_location": "L45",
+      "id": "20260411_three_multiagent_projects_analysis_report_codeblock_1",
+      "community": 17,
+      "norm_label": "code:block1 (\u6df1\u5ea6\u8bbf\u8c08\u6f84\u6e05\u9700\u6c42 \u2192 \u5236\u5b9a\u65b9\u6848\u8ba1\u5212 \u2192 \u62c6\u89e3\u4efb\u52a1 \u2192 \u591aworker\u5e76\u884c\u6267\u884c \u2192 \u9a8c\u8bc1\u8bc4\u5ba1 \u2192 \u4fee\u590d\u5faa\u73af \u2192 \u6c47\u603b\u4ea4\u4ed8)"
+    },
+    {
+      "label": "\u4e09\u3001\u4efb\u52a1\u4f9d\u8d56\u63a7\u5236\u5b9e\u73b0",
+      "file_type": "document",
+      "source_file": "pangtong-value/research/20260411-three-multiagent-projects-analysis/report.md",
+      "source_location": "L55",
+      "id": "20260411_three_multiagent_projects_analysis_report_55",
+      "community": 17,
+      "norm_label": "\u4e09\u3001\u4efb\u52a1\u4f9d\u8d56\u63a7\u5236\u5b9e\u73b0"
+    },
+    {
+      "label": "1. Hermes Agent",
+      "file_type": "document",
+      "source_file": "pangtong-value/research/20260411-three-multiagent-projects-analysis/report.md",
+      "source_location": "L57",
+      "id": "20260411_three_multiagent_projects_analysis_report_1_hermes_agent",
+      "community": 17,
+      "norm_label": "1. hermes agent"
+    },
+    {
+      "label": "2. oh-my-codex / oh-my-claudecode",
+      "file_type": "document",
+      "source_file": "pangtong-value/research/20260411-three-multiagent-projects-analysis/report.md",
+      "source_location": "L63",
+      "id": "20260411_three_multiagent_projects_analysis_report_2_oh_my_codex_oh_my_claudecode_63",
+      "community": 17,
+      "norm_label": "2. oh-my-codex / oh-my-claudecode"
+    },
+    {
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+      "file_type": "document",
+      "source_file": "pangtong-value/research/20260411-three-multiagent-projects-analysis/report.md",
+      "source_location": "L65",
+      "id": "20260411_three_multiagent_projects_analysis_report_65",
+      "community": 17,
+      "norm_label": "\u56fa\u5b9a\u9636\u6bb5\u6d41\u6c34\u7ebf(\u9ed8\u8ba4\u63a8\u8350)"
+    },
+    {
+      "label": "code:block2 (\u6f84\u6e05 \u2192 \u8ba1\u5212 \u2192 \u6267\u884c \u2192 \u9a8c\u8bc1 \u2192 \u4fee\u590d)",
+      "file_type": "document",
+      "source_file": "pangtong-value/research/20260411-three-multiagent-projects-analysis/report.md",
+      "source_location": "L67",
+      "id": "20260411_three_multiagent_projects_analysis_report_codeblock_2",
+      "community": 17,
+      "norm_label": "code:block2 (\u6f84\u6e05 \u2192 \u8ba1\u5212 \u2192 \u6267\u884c \u2192 \u9a8c\u8bc1 \u2192 \u4fee\u590d)"
+    },
+    {
+      "label": "\u590d\u6742\u4f9d\u8d56\uff08\u652f\u6301\uff09",
+      "file_type": "document",
+      "source_file": "pangtong-value/research/20260411-three-multiagent-projects-analysis/report.md",
+      "source_location": "L75",
+      "id": "20260411_three_multiagent_projects_analysis_report_75",
+      "community": 17,
+      "norm_label": "\u590d\u6742\u4f9d\u8d56(\u652f\u6301)"
+    },
+    {
+      "label": "\u8f6e\u8be2\u6536\u655b\u673a\u5236\uff08\u6838\u5fc3\u5b9e\u73b0\uff09",
+      "file_type": "document",
+      "source_file": "pangtong-value/research/20260411-three-multiagent-projects-analysis/report.md",
+      "source_location": "L83",
+      "id": "20260411_three_multiagent_projects_analysis_report_83",
+      "community": 17,
+      "norm_label": "\u8f6e\u8be2\u6536\u655b\u673a\u5236(\u6838\u5fc3\u5b9e\u73b0)"
+    },
+    {
+      "label": "code:typescript (// \u6bcf\u6b21\u67e5\u8be2\u72b6\u6001\u90fd\u91cd\u65b0\u4ece\u6587\u4ef6\u8bfb\u53d6)",
+      "file_type": "document",
+      "source_file": "pangtong-value/research/20260411-three-multiagent-projects-analysis/report.md",
+      "source_location": "L85",
+      "id": "20260411_three_multiagent_projects_analysis_report_codeblock_3",
+      "community": 17,
+      "norm_label": "code:typescript (// \u6bcf\u6b21\u67e5\u8be2\u72b6\u6001\u90fd\u91cd\u65b0\u4ece\u6587\u4ef6\u8bfb\u53d6)"
+    },
+    {
+      "label": "\u56db\u3001\u901a\u4fe1\u5171\u4eab\u4fe1\u606f\u5b9e\u73b0",
+      "file_type": "document",
+      "source_file": "pangtong-value/research/20260411-three-multiagent-projects-analysis/report.md",
+      "source_location": "L106",
+      "id": "20260411_three_multiagent_projects_analysis_report_106",
+      "community": 17,
+      "norm_label": "\u56db\u3001\u901a\u4fe1\u5171\u4eab\u4fe1\u606f\u5b9e\u73b0"
+    },
+    {
+      "label": "1. Hermes Agent",
+      "file_type": "document",
+      "source_file": "pangtong-value/research/20260411-three-multiagent-projects-analysis/report.md",
+      "source_location": "L108",
+      "id": "20260411_three_multiagent_projects_analysis_report_1_hermes_agent_108",
+      "community": 17,
+      "norm_label": "1. hermes agent"
+    },
+    {
+      "label": "2. oh-my-codex / oh-my-claudecode",
+      "file_type": "document",
+      "source_file": "pangtong-value/research/20260411-three-multiagent-projects-analysis/report.md",
+      "source_location": "L114",
+      "id": "20260411_three_multiagent_projects_analysis_report_2_oh_my_codex_oh_my_claudecode_114",
+      "community": 17,
+      "norm_label": "2. oh-my-codex / oh-my-claudecode"
+    },
+    {
+      "label": "\u76ee\u5f55\u7ed3\u6784",
+      "file_type": "document",
+      "source_file": "pangtong-value/research/20260411-three-multiagent-projects-analysis/report.md",
+      "source_location": "L118",
+      "id": "20260411_three_multiagent_projects_analysis_report_118",
+      "community": 17,
+      "norm_label": "\u76ee\u5f55\u7ed3\u6784"
+    },
+    {
+      "label": "code:block4 (project-root/)",
+      "file_type": "document",
+      "source_file": "pangtong-value/research/20260411-three-multiagent-projects-analysis/report.md",
+      "source_location": "L120",
+      "id": "20260411_three_multiagent_projects_analysis_report_codeblock_4",
+      "community": 17,
+      "norm_label": "code:block4 (project-root/)"
+    },
+    {
+      "label": "\u901a\u4fe1\u673a\u5236",
+      "file_type": "document",
+      "source_file": "pangtong-value/research/20260411-three-multiagent-projects-analysis/report.md",
+      "source_location": "L136",
+      "id": "20260411_three_multiagent_projects_analysis_report_136",
+      "community": 17,
+      "norm_label": "\u901a\u4fe1\u673a\u5236"
+    },
+    {
+      "label": "\u548c\u4e09\u56fdSanguo Mail\u5bf9\u6bd4",
+      "file_type": "document",
+      "source_file": "pangtong-value/research/20260411-three-multiagent-projects-analysis/report.md",
+      "source_location": "L143",
+      "id": "20260411_three_multiagent_projects_analysis_report_sanguo_mail",
+      "community": 17,
+      "norm_label": "\u548c\u4e09\u56fdsanguo mail\u5bf9\u6bd4"
+    },
+    {
+      "label": "\u4e94\u3001\u63d0\u793a\u8bcd\u8bbe\u8ba1\u603b\u7ed3",
+      "file_type": "document",
+      "source_file": "pangtong-value/research/20260411-three-multiagent-projects-analysis/report.md",
+      "source_location": "L157",
+      "id": "20260411_three_multiagent_projects_analysis_report_157",
+      "community": 17,
+      "norm_label": "\u4e94\u3001\u63d0\u793a\u8bcd\u8bbe\u8ba1\u603b\u7ed3"
+    },
+    {
+      "label": "1. Hermes Agent",
+      "file_type": "document",
+      "source_file": "pangtong-value/research/20260411-three-multiagent-projects-analysis/report.md",
+      "source_location": "L159",
+      "id": "20260411_three_multiagent_projects_analysis_report_1_hermes_agent_159",
+      "community": 17,
+      "norm_label": "1. hermes agent"
+    },
+    {
+      "label": "2. oh-my-codex / oh-my-claudecode",
+      "file_type": "document",
+      "source_file": "pangtong-value/research/20260411-three-multiagent-projects-analysis/report.md",
+      "source_location": "L169",
+      "id": "20260411_three_multiagent_projects_analysis_report_2_oh_my_codex_oh_my_claudecode_169",
+      "community": 17,
+      "norm_label": "2. oh-my-codex / oh-my-claudecode"
+    },
+    {
+      "label": "\u6838\u5fc3\u9884\u7f6e\u547d\u4ee4/\u63d0\u793a\u8bcd",
+      "file_type": "document",
+      "source_file": "pangtong-value/research/20260411-three-multiagent-projects-analysis/report.md",
+      "source_location": "L173",
+      "id": "20260411_three_multiagent_projects_analysis_report_173",
+      "community": 17,
+      "norm_label": "\u6838\u5fc3\u9884\u7f6e\u547d\u4ee4/\u63d0\u793a\u8bcd"
+    },
+    {
+      "label": "\u9636\u6bb5\u5206\u5de5\u63d0\u793a\u8bcd",
+      "file_type": "document",
+      "source_file": "pangtong-value/research/20260411-three-multiagent-projects-analysis/report.md",
+      "source_location": "L183",
+      "id": "20260411_three_multiagent_projects_analysis_report_183",
+      "community": 17,
+      "norm_label": "\u9636\u6bb5\u5206\u5de5\u63d0\u793a\u8bcd"
+    },
+    {
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+      "file_type": "document",
+      "source_file": "pangtong-value/research/20260411-three-multiagent-projects-analysis/report.md",
+      "source_location": "L195",
+      "id": "20260411_three_multiagent_projects_analysis_report_195",
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+    },
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+      "file_type": "document",
+      "source_file": "pangtong-value/research/20260411-three-multiagent-projects-analysis/report.md",
+      "source_location": "L207",
+      "id": "20260411_three_multiagent_projects_analysis_report_207",
+      "community": 17,
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+    },
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+      "file_type": "document",
+      "source_file": "pangtong-value/research/20260411-three-multiagent-projects-analysis/report.md",
+      "source_location": "L209",
+      "id": "20260411_three_multiagent_projects_analysis_report_1",
+      "community": 17,
+      "norm_label": "1. \u6211\u4eec\u5df2\u6709\u57fa\u7840"
+    },
+    {
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+      "file_type": "document",
+      "source_file": "pangtong-value/research/20260411-three-multiagent-projects-analysis/report.md",
+      "source_location": "L216",
+      "id": "20260411_three_multiagent_projects_analysis_report_2",
+      "community": 17,
+      "norm_label": "2. \u53ef\u4ee5\u76f4\u63a5\u501f\u9274\u7684\u70b9"
+    },
+    {
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+      "file_type": "document",
+      "source_file": "pangtong-value/research/20260411-three-multiagent-projects-analysis/report.md",
+      "source_location": "L218",
+      "id": "20260411_three_multiagent_projects_analysis_report_1_218",
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+    },
+    {
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+      "file_type": "document",
+      "source_file": "pangtong-value/research/20260411-three-multiagent-projects-analysis/report.md",
+      "source_location": "L222",
+      "id": "20260411_three_multiagent_projects_analysis_report_codeblock_5",
+      "community": 17,
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+    },
+    {
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+      "file_type": "document",
+      "source_file": "pangtong-value/research/20260411-three-multiagent-projects-analysis/report.md",
+      "source_location": "L237",
+      "id": "20260411_three_multiagent_projects_analysis_report_2_237",
+      "community": 17,
+      "norm_label": "(2) \u72b6\u6001\u6587\u4ef6\u7ea6\u5b9a"
+    },
+    {
+      "label": "code:block6 (<project-root>/)",
+      "file_type": "document",
+      "source_file": "pangtong-value/research/20260411-three-multiagent-projects-analysis/report.md",
+      "source_location": "L241",
+      "id": "20260411_three_multiagent_projects_analysis_report_codeblock_6",
+      "community": 17,
+      "norm_label": "code:block6 (<project-root>/)"
+    },
+    {
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\ No newline at end of file