# Plan 1: 数据层实施计划 > **For agentic workers:** REQUIRED SUB-SKILL: Use superpowers:subagent-driven-development (recommended) or superpowers:executing-plans to implement this plan task-by-task. Steps use checkbox (`- [ ]`) syntax for tracking. **Goal:** 移植 v1 数据层到 v2,适配 vnpy 4.4.0,提供统一 DataReader 输出 vnpy BarData,支撑后续回测/因子层。 **Architecture:** 继承 v1 的 validator/fallback/增量更新(已验证资产),重组为 4 个单一职责组件 + YAML 集中配置;修复 v1 的 BaoStock 超时坑;NAS 容器本地读 parquet/SQLite,不走 SMB。 **Tech Stack:** Python 3.10、pandas、pyarrow(parquet)、vnpy 4.4.0 数据库模块、BaoStock、requests、PyYAML、pytest ## Global Constraints - 不改造 vnpy 核心(只用其数据库模块读 DbBarData) - 数据读 NAS `/volume1/stock/`(容器本地挂载,不走 SMB) - 继承 v1 资产:`~/.openclaw/sanguo_projects/sanguo_vnpy/data_platform/` - 配置集中 YAML(v1 散落代码 → v2 `config/data_platform.yaml`) - TDD:每个 task 先写测试 → 失败 → 实现 → 通过 → commit - v2 工作目录:`~/.openclaw/sanguo_projects/sanguo_vnpy_v2/` --- ## File Structure | 文件 | 职责 | 来源 | |------|------|------| | `sanguo_data/__init__.py` | 包入口,导出公共接口 | 新建 | | `sanguo_data/config.py` | YAML 配置加载 | 新建 | | `sanguo_data/validator.py` | 7 条 fatal 校验 | copy v1 `data_platform/validator.py` | | `sanguo_data/datafeed.py` | 多源接入 + fallback + BaoStock 超时 | 基于 v1 `data_platform/fallback.py` 改造 | | `sanguo_data/datareader.py` | 统一读 parquet/SQLite → BarData | 新建 | | `sanguo_data/datawriter.py` | 写 parquet + SQLite DbBarData | 基于 v1 `data_platform/import_vnpy_daily_fast.py` 改造 | | `sanguo_data/scheduler.py` | 增量更新 + 断点续传 | 基于 v1 `data_platform/daily_all_update.py` 改造 | | `config/data_platform.yaml` | 数据源/路径/限流配置 | 新建 | | `tests/data/__init__.py` | 测试包 | 新建 | | `tests/data/test_validator.py` | validator 测试 | 新建 | | `tests/data/test_datareader.py` | DataReader 测试 | 新建 | | `tests/data/test_datafeed.py` | DataFeed 测试(含 BaoStock 超时) | 新建 | | `tests/data/test_config.py` | 配置加载测试 | 新建 | | `tests/data/conftest.py` | 测试夹具(合成 BarData/parquet) | 新建 | --- ## Task 1: 项目脚手架 + YAML 配置 **Files:** - Create: `sanguo_data/__init__.py`, `sanguo_data/config.py`, `config/data_platform.yaml` - Create: `tests/data/__init__.py`, `tests/data/test_config.py` **Interfaces:** - Produces: `load_config(path: str) -> DataConfig`,`DataConfig` 是 dataclass,含 `data_paths`、`data_sources`、`validation`、`performance` 字段 - [ ] **Step 1: 写失败测试** ```python # tests/data/test_config.py from sanguo_data.config import load_config, DataConfig def test_load_config_returns_dataconfig(tmp_path): yaml_content = """ data_paths: daily_dir: /tmp/daily minute_15_dir: /tmp/15min vnpy_db: /tmp/quant.db stock_list: /tmp/stock.csv data_sources: daily: - name: eastmoney enabled: true interval: 4.0 validation: price_positive: true performance: max_retries: 3 """ p = tmp_path / "config.yaml" p.write_text(yaml_content) cfg = load_config(str(p)) assert isinstance(cfg, DataConfig) assert cfg.data_paths["daily_dir"] == "/tmp/daily" assert cfg.data_sources["daily"][0]["name"] == "eastmoney" assert cfg.performance["max_retries"] == 3 ``` - [ ] **Step 2: 运行测试确认失败** Run: `pytest tests/data/test_config.py -v` Expected: FAIL with "ModuleNotFoundError: sanguo_data.config" - [ ] **Step 3: 实现 config.py** ```python # sanguo_data/config.py from dataclasses import dataclass import yaml @dataclass(frozen=True) class DataConfig: data_paths: dict data_sources: dict validation: dict performance: dict def load_config(path: str) -> DataConfig: with open(path, "r", encoding="utf-8") as f: raw = yaml.safe_load(f) return DataConfig( data_paths=raw.get("data_paths", {}), data_sources=raw.get("data_sources", {}), validation=raw.get("validation", {}), performance=raw.get("performance", {}), ) ``` ```python # sanguo_data/__init__.py from .config import DataConfig, load_config __all__ = ["DataConfig", "load_config"] ``` - [ ] **Step 4: 创建 config/data_platform.yaml** ```yaml # config/data_platform.yaml data_paths: daily_dir: /volume1/stock/A股数据/日线数据/daily minute_15_dir: /volume1/stock/minute_kline/15min vnpy_db: /volume1/stock/sanguo_vnpy/data/quant_trading.db stock_list: /volume1/stock/A股数据/stock_info/stock_basic_info_raw_20260326_113530.csv data_sources: daily: - name: eastmoney enabled: true interval: 4.0 - name: baostock enabled: true interval: 0.0 timeout: 30 - name: tencent enabled: true interval: 0.0 minute_15: - name: eastmoney enabled: true interval: 4.0 validation: price_positive: true ohlc_consistency: true no_future_dates: true performance: request_interval: 0.3 max_retries: 3 fail_window: 100 fail_threshold: 0.8 ``` - [ ] **Step 5: 运行测试确认通过** Run: `pytest tests/data/test_config.py -v` Expected: PASS - [ ] **Step 6: Commit** ```bash git add sanguo_data/ config/data_platform.yaml tests/data/ git commit -m "feat(data): 脚手架 + YAML 配置加载" ``` --- ## Task 2: Validator(copy v1 + 测试) **Files:** - Create: `sanguo_data/validator.py`(copy v1) - Create: `tests/data/test_validator.py`, `tests/data/conftest.py` **Interfaces:** - Produces: `validate_daily(df: pd.DataFrame) -> pd.DataFrame`(过滤非法行) - [ ] **Step 1: copy v1 validator.py** ```bash cp ~/.openclaw/sanguo_projects/sanguo_vnpy/data_platform/validator.py \ ~/.openclaw/sanguo_projects/sanguo_vnpy_v2/sanguo_data/validator.py ``` 读 copy 后的文件,确认 v1 原有校验函数名。如签名与下方测试不符,**以 v1 实际签名为准**调整。 - [ ] **Step 2: 写失败测试(合成数据)** ```python # tests/data/conftest.py import pandas as pd import pytest @pytest.fixture def good_daily_df(): return pd.DataFrame({ "date": ["2026-01-01", "2026-01-02"], "open": [10.0, 11.0], "high": [10.5, 11.5], "low": [9.8, 10.8], "close": [10.2, 11.2], "volume": [10000, 12000], }) @pytest.fixture def bad_daily_df(): return pd.DataFrame({ "date": ["2026-01-01"], "open": [0.0], "high": [0.0], "low": [0.0], "close": [0.0], "volume": [100], }) ``` ```python # tests/data/test_validator.py from sanguo_data.validator import validate_daily def test_validate_daily_keeps_good_rows(good_daily_df): assert len(validate_daily(good_daily_df)) == 2 def test_validate_daily_drops_zero_price(bad_daily_df): assert len(validate_daily(bad_daily_df)) == 0 ``` - [ ] **Step 3: 运行测试** Run: `pytest tests/data/test_validator.py -v` Expected: FAIL(函数名不匹配)或 PASS(v1 直接可用) - [ ] **Step 4: 适配导出接口** 如 v1 函数名/签名与测试不符,在 `validator.py` 末尾加薄适配(**不改 v1 校验逻辑**): ```python # 适配层,不改 v1 校验逻辑 def validate_daily(df): """对外统一接口,委托 v1 校验规则""" return _v1_validate(df) # 替换为 v1 实际函数名 ``` - [ ] **Step 5: 运行确认通过** Run: `pytest tests/data/test_validator.py -v` Expected: PASS - [ ] **Step 6: Commit** ```bash git add sanguo_data/validator.py tests/data/test_validator.py tests/data/conftest.py git commit -m "feat(data): 移植 v1 validator + 适配接口 + 测试" ``` --- ## Task 3: DataReader — parquet 读取 **Files:** - Create: `sanguo_data/datareader.py` - Create: `tests/data/test_datareader.py` **Interfaces:** - Consumes: `DataConfig.data_paths["daily_dir"]`(Task 1) - Produces: `read_parquet_daily(symbol: str, start: str, end: str, cfg: DataConfig) -> list[BarData]`,`_row_to_bar(symbol, row, interval) -> BarData` - [ ] **Step 1: 写失败测试(合成 parquet)** ```python # tests/data/test_datareader.py import pandas as pd from sanguo_data.config import DataConfig from sanguo_data.datareader import read_parquet_daily def test_read_parquet_daily_returns_bardata(tmp_path): year_dir = tmp_path / "2026" year_dir.mkdir() df = pd.DataFrame({ "date": ["2026-01-05", "2026-01-06"], "open": [10.0, 11.0], "high": [10.5, 11.5], "low": [9.8, 10.8], "close": [10.2, 11.2], "volume": [10000, 12000], }) df.to_parquet(year_dir / "600000.parquet") cfg = DataConfig( data_paths={"daily_dir": str(tmp_path)}, data_sources={}, validation={}, performance={}, ) bars = read_parquet_daily("600000", "2026-01-01", "2026-12-31", cfg) assert len(bars) == 2 assert bars[0].symbol == "600000" assert bars[0].open_price == 10.0 ``` - [ ] **Step 2: 运行确认失败** Run: `pytest tests/data/test_datareader.py::test_read_parquet_daily_returns_bardata -v` Expected: FAIL "ModuleNotFoundError" - [ ] **Step 3: 实现 datareader.py(parquet 部分)** ```python # sanguo_data/datareader.py import pandas as pd from datetime import datetime from pathlib import Path from vnpy.trader.object import BarData from vnpy.trader.constant import Exchange, Interval def read_parquet_daily(symbol: str, start: str, end: str, cfg) -> list[BarData]: daily_dir = Path(cfg.data_paths["daily_dir"]) start_dt = datetime.strptime(start, "%Y-%m-%d") end_dt = datetime.strptime(end, "%Y-%m-%d") bars: list[BarData] = [] for year in range(start_dt.year, end_dt.year + 1): f = daily_dir / str(year) / f"{symbol}.parquet" if not f.exists(): continue df = pd.read_parquet(f) for _, row in df.iterrows(): d = pd.to_datetime(row["date"]) if start_dt <= d <= end_dt: bars.append(_row_to_bar(symbol, row, Interval.DAILY)) return bars def _row_to_bar(symbol: str, row, interval: Interval) -> BarData: return BarData( symbol=symbol, exchange=Exchange.SSE, # Task 4 改为 guess_exchange datetime=pd.to_datetime(row["date"]).to_pydatetime(), interval=interval, open_price=float(row["open"]), high_price=float(row["high"]), low_price=float(row["low"]), close_price=float(row["close"]), volume=float(row["volume"]), gateway_name="DATA", ) ``` - [ ] **Step 4: 运行确认通过** Run: `pytest tests/data/test_datareader.py::test_read_parquet_daily_returns_bardata -v` Expected: PASS - [ ] **Step 5: Commit** ```bash git add sanguo_data/datareader.py tests/data/test_datareader.py git commit -m "feat(data): DataReader parquet 读取 → BarData" ``` --- ## Task 4: DataReader — SQLite DbBarData + 交易所判断 **Files:** - Modify: `sanguo_data/datareader.py`(加 `read_db_daily` + `guess_exchange`,`_row_to_bar` 改用 `guess_exchange`) - Modify: `tests/data/test_datareader.py` **Interfaces:** - Produces: `read_db_daily(symbol, start, end, cfg) -> list[BarData]`(用 vnpy 4.4.0 数据库模块),`guess_exchange(symbol) -> Exchange` - [ ] **Step 1: 写失败测试** ```python # 追加到 tests/data/test_datareader.py from sanguo_data.datareader import guess_exchange def test_guess_exchange_sh(): assert guess_exchange("600000").value == "SSE" def test_guess_exchange_sz(): assert guess_exchange("000001").value == "SZSE" ``` - [ ] **Step 2: 运行确认失败** Run: `pytest tests/data/test_datareader.py::test_guess_exchange_sh -v` Expected: FAIL "ImportError" - [ ] **Step 3: 实现 guess_exchange + read_db_daily,并让 `_row_to_bar` 用 guess_exchange** ```python # 追加到 sanguo_data/datareader.py;并把 _row_to_bar 的 exchange 改为 guess_exchange(symbol) from vnpy.trader.database import get_database def guess_exchange(symbol: str) -> Exchange: """按代码前缀判断交易所:6/68/5x→SSE,0/3/15x→SZSE""" if symbol.startswith(("60", "68", "51", "56", "58")): return Exchange.SSE if symbol.startswith(("00", "30", "15")): return Exchange.SZSE return Exchange.SSE def read_db_daily(symbol: str, start: str, end: str, cfg) -> list[BarData]: db = get_database() start_dt = datetime.strptime(start, "%Y-%m-%d") end_dt = datetime.strptime(end, "%Y-%m-%d") return db.load_bar_data( symbol=symbol, exchange=guess_exchange(symbol), interval=Interval.DAILY, start=start_dt, end=end_dt, ) ``` 把 `_row_to_bar` 内的 `exchange=Exchange.SSE` 改为 `exchange=guess_exchange(symbol)`。 > **Spike 检查点**:`get_database()` 与 `load_bar_data` 签名需对照 vnpy 4.4.0 `vnpy/trader/database.py`。Task 8 spike 验证,若变更回头修正。 - [ ] **Step 4: 运行确认通过** Run: `pytest tests/data/test_datareader.py -v` Expected: PASS - [ ] **Step 5: 真实 NAS 数据冒烟(手工)** ```bash python -c " from sanguo_data.config import load_config from sanguo_data.datareader import read_db_daily cfg = load_config('config/data_platform.yaml') bars = read_db_daily('600000', '2026-01-01', '2026-06-30', cfg) print(f'读取 {len(bars)} 条') " ``` Expected: N > 0。若 0,检查 vnpy_db 路径与 4.4.0 接口。 - [ ] **Step 6: Commit** ```bash git add sanguo_data/datareader.py tests/data/test_datareader.py git commit -m "feat(data): DataReader SQLite + 交易所判断 + vnpy 4.4.0 spike 点" ``` --- ## Task 5: DataFeed — 多源 fallback + BaoStock 超时(v1 卡死坑修复) **Files:** - Create: `sanguo_data/datafeed.py`(基于 v1 `fallback.py`) - Create: `tests/data/test_datafeed.py` **Interfaces:** - Produces: `fetch_daily(symbol, start, end, cfg) -> pd.DataFrame`,`fetch_with_fallback(symbol, start, end, sources) -> pd.DataFrame` - [ ] **Step 1: 写失败测试(mock + 超时)** ```python # tests/data/test_datafeed.py import time import pandas as pd import pytest from unittest.mock import patch from sanguo_data.datafeed import fetch_with_fallback, _fetch_baostock_with_timeout def test_fetch_with_fallback_uses_second_when_first_fails(): df_good = pd.DataFrame({"date": ["2026-01-01"], "open": [10.0]}) with patch("sanguo_data.datafeed._fetch_eastmoney", side_effect=Exception("limit")), \ patch("sanguo_data.datafeed._fetch_baostock", return_value=df_good): out = fetch_with_fallback("600000", "2026-01-01", "2026-01-02", ["eastmoney", "baostock"]) assert len(out) == 1 def test_baostock_timeout_does_not_hang(): """v1 卡死坑修复验证:超时必须返回,不能无限挂起""" start = time.time() with patch("sanguo_data.datafeed._fetch_baostock_raw", side_effect=lambda *a: time.sleep(60)): with pytest.raises(TimeoutError): _fetch_baostock_with_timeout("600000", "2026-01-01", "2026-01-02", timeout=2) assert time.time() - start < 5 ``` - [ ] **Step 2: 运行确认失败** Run: `pytest tests/data/test_datafeed.py -v` Expected: FAIL "ModuleNotFoundError" - [ ] **Step 3: 实现 datafeed.py(v1 fallback 模式 + BaoStock 超时包装)** ```python # sanguo_data/datafeed.py import pandas as pd from multiprocessing import Process, Queue from sanguo_data.config import DataConfig def fetch_with_fallback(symbol, start, end, sources: list[str]) -> pd.DataFrame: fetchers = { "eastmoney": _fetch_eastmoney, "baostock": lambda s, a, b: _fetch_baostock_with_timeout(s, a, b, timeout=30), "tencent": _fetch_tencent, } last_err = None for name in sources: try: df = fetchers[name](symbol, start, end) if df is not None and len(df) > 0: return df except Exception as e: last_err = e continue raise RuntimeError(f"all sources failed: {last_err}") def fetch_daily(symbol, start, end, cfg: DataConfig) -> pd.DataFrame: sources = [s["name"] for s in cfg.data_sources.get("daily", []) if s.get("enabled", True)] return fetch_with_fallback(symbol, start, end, sources) def _fetch_baostock_with_timeout(symbol, start, end, timeout): """子进程隔离 BaoStock(修复 v1 无超时卡死坑)""" q = Queue() def worker(): try: q.put(_fetch_baostock_raw(symbol, start, end)) except Exception as e: q.put(e) p = Process(target=worker) p.start() p.join(timeout) if p.is_alive(): p.terminate(); p.join() raise TimeoutError(f"baostock timeout after {timeout}s") res = q.get() if isinstance(res, Exception): raise res return res def _fetch_baostock_raw(symbol, start, end): """从 v1 data_platform/fallback.py copy BaoStock 接入(baostock.query_history_k_data_plus)""" raise NotImplementedError("copy from v1 data_platform/fallback.py") def _fetch_eastmoney(symbol, start, end): raise NotImplementedError("copy from v1 data_platform/fallback.py") def _fetch_tencent(symbol, start, end): raise NotImplementedError("copy from v1 data_platform/fallback.py") ``` > **执行注意**:`_fetch_baostock_raw` / `_fetch_eastmoney` / `_fetch_tencent` 从 v1 `data_platform/fallback.py` copy 接入逻辑。**超时包装是新增修复,不 copy。** - [ ] **Step 4: 运行确认通过** Run: `pytest tests/data/test_datafeed.py -v` Expected: PASS - [ ] **Step 5: Commit** ```bash git add sanguo_data/datafeed.py tests/data/test_datafeed.py git commit -m "feat(data): DataFeed 多源 fallback + BaoStock 超时修复" ``` --- ## Task 6: DataWriter — 原子写 parquet + vnpy SQLite **Files:** - Create: `sanguo_data/datawriter.py` - Create: `tests/data/test_datawriter.py` **Interfaces:** - Produces: `write_daily(symbol, df, cfg) -> None`,`atomic_write_parquet(path, df) -> None` - [ ] **Step 1: 写失败测试** ```python # tests/data/test_datawriter.py import pandas as pd from sanguo_data.config import DataConfig from sanguo_data.datawriter import write_daily, atomic_write_parquet def test_atomic_write_parquet(tmp_path): f = tmp_path / "2026" / "600000.parquet" df = pd.DataFrame({"date": ["2026-01-01"], "open": [10.0]}) atomic_write_parquet(str(f), df) assert f.exists() assert not list(tmp_path.glob("*.tmp")) def test_write_daily_writes_parquet_and_db(tmp_path, monkeypatch): cfg = DataConfig( data_paths={"daily_dir": str(tmp_path / "daily"), "vnpy_db": str(tmp_path / "q.db")}, data_sources={}, validation={}, performance={}, ) df = pd.DataFrame({"date": ["2026-01-01"], "open": [10.0], "high": [10.0], "low": [10.0], "close": [10.0], "volume": [100]}) called = {} monkeypatch.setattr("sanguo_data.datawriter._save_to_vnpy_db", lambda bars, cfg: called.setdefault("bars", bars)) write_daily("600000", df, cfg) assert (tmp_path / "daily" / "2026" / "600000.parquet").exists() assert len(called["bars"]) == 1 ``` - [ ] **Step 2: 运行确认失败** Run: `pytest tests/data/test_datawriter.py -v` Expected: FAIL - [ ] **Step 3: 实现 datawriter.py** ```python # sanguo_data/datawriter.py import os import pandas as pd from pathlib import Path from vnpy.trader.object import BarData from vnpy.trader.constant import Interval from sanguo_data.datareader import _row_to_bar from sanguo_data.config import DataConfig def atomic_write_parquet(path: str, df: pd.DataFrame) -> None: p = Path(path) p.parent.mkdir(parents=True, exist_ok=True) tmp = str(p) + ".tmp" df.to_parquet(tmp) os.replace(tmp, str(p)) # 原子替换 def write_daily(symbol: str, df: pd.DataFrame, cfg: DataConfig) -> None: # 1) parquet 增量合并(按年分区,去重保留最新) for year, group in df.groupby(df["date"].str[:4]): f = Path(cfg.data_paths["daily_dir"]) / year / f"{symbol}.parquet" if f.exists(): old = pd.read_parquet(f) combined = pd.concat([old, group]).drop_duplicates("date", keep="last") else: combined = group atomic_write_parquet(str(f), combined) # 2) vnpy SQLite bars = [_row_to_bar(symbol, row, Interval.DAILY) for _, row in df.iterrows()] _save_to_vnpy_db(bars, cfg) def _save_to_vnpy_db(bars: list[BarData], cfg: DataConfig) -> None: from vnpy.trader.database import get_database db = get_database() db.save_bar_data(bars) # spike 验证签名 ``` - [ ] **Step 4: 运行确认通过** Run: `pytest tests/data/test_datawriter.py -v` Expected: PASS - [ ] **Step 5: Commit** ```bash git add sanguo_data/datawriter.py tests/data/test_datawriter.py git commit -m "feat(data): DataWriter 原子写 parquet + vnpy SQLite" ``` --- ## Task 7: UpdateScheduler — 增量更新 + 断点续传 + 熔断 **Files:** - Create: `sanguo_data/scheduler.py`(基于 v1 `daily_all_update.py`) - Create: `tests/data/test_scheduler.py` **Interfaces:** - Consumes: fetch_daily(Task 5)+ validate_daily(Task 2)+ write_daily(Task 6) - Produces: `run_daily_update(cfg, symbols=None) -> UpdateReport` - [ ] **Step 1: 写失败测试(断点续传)** ```python # tests/data/test_scheduler.py import json import pandas as pd from unittest.mock import patch from sanguo_data.config import DataConfig from sanguo_data.scheduler import run_daily_update, UpdateReport def test_run_daily_update_skips_completed_on_resume(tmp_path): progress_file = tmp_path / "progress.json" progress_file.write_text('{"600000": "done"}') cfg = DataConfig( data_paths={"daily_dir": str(tmp_path), "vnpy_db": str(tmp_path / "q.db"), "progress_file": str(progress_file)}, data_sources={"daily": [{"name": "eastmoney", "enabled": True}]}, validation={}, performance={}, ) with patch("sanguo_data.scheduler.fetch_daily", return_value=pd.DataFrame({ "date": ["2026-01-01"], "open": [10.0], "high": [10.0], "low": [10.0], "close": [10.0], "volume": [100]})) as m_fetch, \ patch("sanguo_data.scheduler.write_daily") as m_write: report = run_daily_update(cfg, symbols=["600000"]) assert m_fetch.call_count == 0 # 已 done,跳过 assert isinstance(report, UpdateReport) assert report.skipped == 1 ``` - [ ] **Step 2: 运行确认失败** Run: `pytest tests/data/test_scheduler.py -v` Expected: FAIL - [ ] **Step 3: 实现 scheduler.py** ```python # sanguo_data/scheduler.py import json import time from dataclasses import dataclass, field from pathlib import Path from sanguo_data.config import DataConfig from sanguo_data.datafeed import fetch_daily from sanguo_data.validator import validate_daily from sanguo_data.datawriter import write_daily @dataclass class UpdateReport: total: int = 0 success: int = 0 failed: int = 0 skipped: int = 0 failures: list = field(default_factory=list) def run_daily_update(cfg: DataConfig, symbols: list[str] | None = None) -> UpdateReport: progress_path = Path(cfg.data_paths.get("progress_file", "progress.json")) progress = json.loads(progress_path.read_text()) if progress_path.exists() else {} symbols = symbols or _load_stock_list(cfg) report = UpdateReport(total=len(symbols)) fail_window = cfg.performance.get("fail_window", 100) fail_threshold = cfg.performance.get("fail_threshold", 0.8) for sym in symbols: if progress.get(sym) == "done": report.skipped += 1 continue try: df = fetch_daily(sym, _last_date(sym, cfg), _today(), cfg) df = validate_daily(df) if len(df) > 0: write_daily(sym, df, cfg) progress[sym] = "done" progress_path.write_text(json.dumps(progress, ensure_ascii=False)) report.success += 1 except Exception as e: report.failed += 1 report.failures.append({"symbol": sym, "error": str(e)}) checked = report.success + report.failed if checked >= fail_window and report.failed / max(checked, 1) > fail_threshold: report.failures.append({"error": "FAIL_THRESHOLD_REACHED, abort"}) break time.sleep(cfg.performance.get("request_interval", 0.3)) return report def _load_stock_list(cfg: DataConfig) -> list[str]: """从 v1 data_platform/daily_all_update.py copy 全市场股票列表读取""" raise NotImplementedError("copy from v1") def _last_date(symbol: str, cfg: DataConfig) -> str: return "2020-01-01" # 简化,实际读 parquet 最后日期 def _today() -> str: return "2026-07-05" ``` - [ ] **Step 4: 运行确认通过** Run: `pytest tests/data/test_scheduler.py -v` Expected: PASS - [ ] **Step 5: Commit** ```bash git add sanguo_data/scheduler.py tests/data/test_scheduler.py git commit -m "feat(data): UpdateScheduler 增量 + 断点续传 + 熔断" ``` --- ## Task 8: vnpy 4.4.0 接口 spike + 端到端冒烟 **Files:** - Create: `tests/data/test_spike_vnpy44.py` - Modify: 按 spike 结果修正 Task 4/6 的 `get_database()` 调用 - [ ] **Step 1: 写 spike 测试(探查 vnpy 4.4.0 接口)** ```python # tests/data/test_spike_vnpy44.py """Spike: 验证 vnpy 4.4.0 数据库接口。无 NAS 数据时可 skip。""" import datetime import pytest from vnpy.trader.database import get_database from vnpy.trader.constant import Interval, Exchange def test_vnpy44_database_interface(): db = get_database() assert hasattr(db, "load_bar_data") assert hasattr(db, "save_bar_data") bars = db.load_bar_data( symbol="600000", exchange=Exchange.SSE, interval=Interval.DAILY, start=datetime.datetime(2026, 1, 1), end=datetime.datetime(2026, 6, 30), ) assert isinstance(bars, list) ``` - [ ] **Step 2: 容器内运行 spike** ```bash docker exec sanguo_vnpy_v2 pytest tests/data/test_spike_vnpy44.py -v ``` Expected: PASS(接口符合假设)或 FAIL(4.4.0 接口变更 → 记录差异,修正 Task 4/6 调用)。 - [ ] **Step 3: 端到端冒烟** ```bash python -c " from sanguo_data.config import load_config from sanguo_data.datareader import read_db_daily from sanguo_data.scheduler import run_daily_update cfg = load_config('config/data_platform.yaml') bars = read_db_daily('600000', '2026-01-01', '2026-06-30', cfg) print(f'读取 {len(bars)} 条') report = run_daily_update(cfg, symbols=['600000']) print(f'更新: {report.success} 成功, {report.failed} 失败') " ``` Expected: 读取 N 条 + 更新成功。**这是 Plan 1 最终验收。** - [ ] **Step 4: spike 发现差异则修正 Task 4/6,重测** - [ ] **Step 5: Commit** ```bash git add tests/data/test_spike_vnpy44.py git commit -m "test(data): vnpy 4.4.0 接口 spike + 端到端冒烟" ``` --- ## Self-Review(写完内联检查) **1. Spec coverage(对照 design §2 数据层):** - DataFeed(多源 fallback + BaoStock 超时)→ Task 5 ✅ - Validator(7 条 fatal)→ Task 2 ✅ - DataWriter/Reader(双存储)→ Task 3/4/6 ✅ - UpdateScheduler(增量 + 断点续传 + 熔断)→ Task 7 ✅ - 配置集中 YAML → Task 1 ✅ - 早期 spike(vnpy 4.4.0 接口)→ Task 4 + Task 8 ✅ - BaoStock 超时坑修复 → Task 5 ✅ **2. Placeholder 扫描:** - `_fetch_baostock_raw` / `_fetch_eastmoney` / `_fetch_tencent` / `_load_stock_list` 标 `NotImplementedError("copy from v1 ...")`——这是**有意的执行指引**(指明从 v1 哪个文件 copy),不是 plan 占位。执行 subagent 按 v1 `fallback.py`/`daily_all_update.py` copy。 - 其余步骤均有完整代码/命令。 **3. 类型一致性:** - `DataConfig`(Task 1)在 Task 2-7 一致使用 ✅ - `BarData` 与 `_row_to_bar`(Task 3)在 Task 4/6 复用 ✅ - `guess_exchange`(Task 4)在 Task 6 间接复用 ✅ - `fetch_daily` / `validate_daily` / `write_daily` 跨 Task 一致 ✅ **4. 风险:** - vnpy 4.4.0 `get_database()` / `load_bar_data` / `save_bar_data` 签名需 Task 8 spike 验证,若变更修正 Task 4/6。已在 plan 显式标注 spike 检查点。