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claude_dev 9595879655 docs: 新增 Plan 1 数据层实施计划

8 个 TDD task：脚手架+配置 / validator / DataReader(parquet+SQLite) /
DataFeed(多源fallback+BaoStock超时) / DataWriter(原子写) /
UpdateScheduler(增量+断点续传+熔断) / vnpy 4.4.0 spike + 端到端冒烟
含 self-review 与执行指引

2026-07-05 11:31:20 +08:00

28 KiB

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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

# 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

# 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", {}),
    )

# sanguo_data/__init__.py
from .config import DataConfig, load_config
__all__ = ["DataConfig", "load_config"]

Step 4: 创建 config/data_platform.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

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

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）

# 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],
    })

# 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）：

# 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

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）

# 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）

# 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

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

# 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

# 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）

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

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）

# 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）

# 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

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

# 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

# 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

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）

# 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

# 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

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）

# 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

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

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

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。

28 KiB Raw Blame History Unescape Escape

Plan 1: 数据层实施计划

Global Constraints

File Structure

Task 1: 项目脚手架 + YAML 配置

Task 2: Validator（copy v1 + 测试）

Task 3: DataReader — parquet 读取

Task 4: DataReader — SQLite DbBarData + 交易所判断

Task 5: DataFeed — 多源 fallback + BaoStock 超时（v1 卡死坑修复）

Task 6: DataWriter — 原子写 parquet + vnpy SQLite

Task 7: UpdateScheduler — 增量更新 + 断点续传 + 熔断

Task 8: vnpy 4.4.0 接口 spike + 端到端冒烟

Self-Review（写完内联检查）

28 KiB

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