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feat(data): 封装ST股票列表接口(stock_st)

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- 新增 api_stock_st.py，实现ST股票数据获取和日期遍历同步
- 更新 sync.py，将ST股票同步加入第7步流程
- 移除 base_sync.py 中未使用的 get_last_n_trading_days 导入
This commit is contained in:
liaozhaorun
2026-03-03 22:04:22 +08:00
parent 472b2b665a
commit 317ecd87e7
8 changed files with 1543 additions and 73 deletions
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1089
docs/plan/training_module_plan.md Normal file
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12
src/data/api_wrappers/__init__.py
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@@ -11,16 +11,19 @@ Available APIs:
- api_trade_cal: Trading calendar (交易日历)
- api_namechange: Stock name change history (股票曾用名)
- api_bak_basic: Stock historical list (股票历史列表)
- api_stock_st: ST stock list (ST股票列表)
Example:
>>> from src.data.api_wrappers import get_daily, get_stock_basic, get_trade_cal, get_bak_basic
>>> from src.data.api_wrappers import get_pro_bar, sync_pro_bar, get_daily_basic, sync_daily_basic
>>> from src.data.api_wrappers import get_stock_st, sync_stock_st
>>> data = get_daily('000001.SZ', start_date='20240101', end_date='20240131')
>>> pro_data = get_pro_bar('000001.SZ', start_date='20240101', end_date='20240131')
>>> daily_basic = get_daily_basic(trade_date='20240101')
>>> stocks = get_stock_basic()
>>> calendar = get_trade_cal('20240101', '20240131')
>>> bak_basic = get_bak_basic(trade_date='20240101')
>>> stock_st = get_stock_st(trade_date='20240101')
"""
from src.data.api_wrappers.api_daily import (
@@ -49,6 +52,11 @@ from src.data.api_wrappers.financial_data.api_income import (
from src.data.api_wrappers.api_bak_basic import get_bak_basic, sync_bak_basic
from src.data.api_wrappers.api_namechange import get_namechange, sync_namechange
from src.data.api_wrappers.api_stock_basic import get_stock_basic, sync_all_stocks
from src.data.api_wrappers.api_stock_st import (
get_stock_st,
sync_stock_st,
StockSTSync,
)
from src.data.api_wrappers.api_trade_cal import (
get_trade_cal,
get_trading_days,
@@ -92,4 +100,8 @@ __all__ = [
"get_first_trading_day",
"get_last_trading_day",
"sync_trade_cal_cache",
# ST stock list
"get_stock_st",
"sync_stock_st",
"StockSTSync",
]

53
src/data/api_wrappers/api.md
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@@ -566,3 +566,56 @@ df = pro.query('daily_basic', ts_code='', trade_date='20180726',fields='ts_code,
17 000708.SZ 20180726 0.5575 0.70 10.3674 1.0276
18 002626.SZ 20180726 0.6187 0.83 22.7580 4.2446
19 600816.SH 20180726 0.6745 0.65 11.0778 3.2214
ST股票列表
接口：stock_st，可以通过数据工具调试和查看数据。
描述：获取ST股票列表，可根据交易日期获取历史上每天的ST列表
权限：3000积分起
提示：每天上午9:20更新，单次请求最大返回1000行数据，可循环提取,本接口数据从20160101开始,太早历史无法补齐
输入参数
名称 类型 必选 描述
ts_code str N 股票代码
trade_date str N 交易日期（格式：YYYYMMDD下同）
start_date str N 开始时间
end_date str N 结束时间
输出参数
名称 类型 默认显示 描述
ts_code str Y 股票代码
name str Y 股票名称
trade_date str Y 交易日期
type str Y 类型
type_name str Y 类型名称
接口用法
pro = ts.pro_api()
#获取20250813日所有的ST股票
df = pro.stock_st(trade_date='20250813')
数据样例
ts_code name trade_date type type_name
0 300313.SZ *ST天山 20250813 ST 风险警示板
1 605081.SH *ST太和 20250813 ST 风险警示板
2 300391.SZ *ST长药 20250813 ST 风险警示板
3 300343.SZ ST联创 20250813 ST 风险警示板
4 300044.SZ ST赛为 20250813 ST 风险警示板
.. ... ... ... ... ...
170 300175.SZ ST朗源 20250813 ST 风险警示板
171 603721.SH *ST天择 20250813 ST 风险警示板
172 600289.SH ST信通 20250813 ST 风险警示板
173 000929.SZ *ST兰黄 20250813 ST 风险警示板
174 000638.SZ *ST万方 20250813 ST 风险警示板

147
src/data/api_wrappers/api_stock_st.py Normal file
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@@ -0,0 +1,147 @@
"""ST股票列表接口。
获取ST股票列表数据，可根据交易日期获取历史上每天的ST列表。
数据从20160101开始可用，每天上午9:20更新。
"""
import pandas as pd
from typing import Optional
from src.data.client import TushareClient
from src.data.api_wrappers.base_sync import DateBasedSync
def get_stock_st(
trade_date: Optional[str] = None,
start_date: Optional[str] = None,
end_date: Optional[str] = None,
ts_code: Optional[str] = None,
) -> pd.DataFrame:
"""Fetch ST stock list from Tushare.
This interface retrieves the daily ST stock list including stock codes,
names, and ST type information. Data is available from 20160101 onwards.
Updates at 9:20 AM daily.
Args:
trade_date: Specific trade date in YYYYMMDD format
start_date: Start date for date range query (YYYYMMDD format)
end_date: End date for date range query (YYYYMMDD format)
ts_code: Stock code filter (optional, e.g., '000001.SZ')
Returns:
pd.DataFrame with columns:
- ts_code: Stock code
- name: Stock name
- trade_date: Trade date (YYYYMMDD)
- type: Type code
- type_name: Type name (风险警示板)
Example:
>>> # Get all ST stocks for a single date
>>> data = get_stock_st(trade_date='20240101')
>>>
>>> # Get date range data
>>> data = get_stock_st(start_date='20240101', end_date='20240131')
>>>
>>> # Get specific stock ST history
>>> data = get_stock_st(ts_code='000001.SZ')
"""
client = TushareClient()
# Build parameters
params = {}
if trade_date:
params["trade_date"] = trade_date
if start_date:
params["start_date"] = start_date
if end_date:
params["end_date"] = end_date
if ts_code:
params["ts_code"] = ts_code
# Fetch data
data = client.query("stock_st", **params)
return data
class StockSTSync(DateBasedSync):
"""ST股票列表批量同步管理器，支持全量/增量同步。
继承自 DateBasedSync，按日期顺序获取数据。
数据从 2016 年开始可用，单次请求最大返回1000行数据。
Example:
>>> sync = StockSTSync()
>>> results = sync.sync_all() # 增量同步
>>> results = sync.sync_all(force_full=True) # 全量同步
>>> preview = sync.preview_sync() # 预览
"""
table_name = "stock_st"
default_start_date = "20160101"
# 表结构定义
TABLE_SCHEMA = {
"ts_code": "VARCHAR(16) NOT NULL",
"name": "VARCHAR(50)",
"trade_date": "DATE NOT NULL",
"type": "VARCHAR(10)",
"type_name": "VARCHAR(50)",
}
# 索引定义
TABLE_INDEXES = [
("idx_stock_st_date_code", ["trade_date", "ts_code"]),
]
# 主键定义
PRIMARY_KEY = ("trade_date", "ts_code")
def fetch_single_date(self, trade_date: str) -> pd.DataFrame:
"""获取单日的ST股票列表数据。
Args:
trade_date: 交易日期（YYYYMMDD）
Returns:
包含当日ST股票列表的 DataFrame
"""
return get_stock_st(trade_date=trade_date)
def sync_stock_st(
start_date: Optional[str] = None,
end_date: Optional[str] = None,
force_full: bool = False,
) -> pd.DataFrame:
"""Sync ST stock list to DuckDB with intelligent incremental sync.
Logic:
- If table doesn't exist: create table + composite index (trade_date, ts_code) + full sync
- If table exists: incremental sync from last_date + 1
Args:
start_date: Start date for sync (YYYYMMDD format, default: 20160101 for full, last_date+1 for incremental)
end_date: End date for sync (YYYYMMDD format, default: today)
force_full: If True, force full reload from 20160101
Returns:
pd.DataFrame with synced data
"""
sync_manager = StockSTSync()
return sync_manager.sync_all(
start_date=start_date,
end_date=end_date,
force_full=force_full,
)
if __name__ == "__main__":
# Test sync
result = sync_stock_st(end_date="20240102")
print(f"Synced {len(result)} records")
if not result.empty:
print("\nSample data:")
print(result.head())

1
src/data/api_wrappers/api_trade_cal.py
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@@ -14,7 +14,6 @@ from src.config.settings import get_settings
_cache_synced = False
# Trading calendar cache file path
def _get_cache_path() -> Path:
"""Get the cache file path for trade calendar."""

50
src/data/api_wrappers/base_sync.py
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@@ -325,7 +325,9 @@ class BaseDataSync(ABC):
try:
print(f"[{class_name}] Probe: {probe_description}")
print(f"[{class_name}] Probe: Inserting {len(probe_data)} sample records...")
print(
f"[{class_name}] Probe: Inserting {len(probe_data)} sample records..."
)
# 插入样本数据
storage.save(self.table_name, probe_data, mode="append")
@@ -355,7 +357,9 @@ class BaseDataSync(ABC):
print(f"[{class_name}] Probe: SUCCESS - Table verified and cleaned")
return True
else:
print(f"[{class_name}] Probe: WARNING - {remaining} rows remaining after cleanup")
print(
f"[{class_name}] Probe: WARNING - {remaining} rows remaining after cleanup"
)
return True # 仍然继续，因为主要目的是验证结构
except Exception as e:
@@ -400,7 +404,9 @@ class BaseDataSync(ABC):
return
if not self.TABLE_SCHEMA:
print(f"[{self.__class__.__name__}] TABLE_SCHEMA not defined, skipping table creation")
print(
f"[{self.__class__.__name__}] TABLE_SCHEMA not defined, skipping table creation"
)
return
# 构建列定义
@@ -410,7 +416,7 @@ class BaseDataSync(ABC):
# 添加主键约束
if self.PRIMARY_KEY:
pk_cols = ', '.join(f'"{col}"' for col in self.PRIMARY_KEY)
pk_cols = ", ".join(f'"{col}"' for col in self.PRIMARY_KEY)
columns_def.append(f"PRIMARY KEY ({pk_cols})")
columns_sql = ", ".join(columns_def)
@@ -426,13 +432,17 @@ class BaseDataSync(ABC):
# 创建索引
for idx_name, idx_cols in self.TABLE_INDEXES:
try:
idx_cols_sql = ', '.join(f'"{col}"' for col in idx_cols)
idx_cols_sql = ", ".join(f'"{col}"' for col in idx_cols)
storage._connection.execute(
f'CREATE INDEX IF NOT EXISTS "{idx_name}" ON "{self.table_name}"({idx_cols_sql})'
)
print(f"[{self.__class__.__name__}] Created index '{idx_name}' on {idx_cols}")
print(
f"[{self.__class__.__name__}] Created index '{idx_name}' on {idx_cols}"
)
except Exception as e:
print(f"[{self.__class__.__name__}] Error creating index {idx_name}: {e}")
print(
f"[{self.__class__.__name__}] Error creating index {idx_name}: {e}"
)
@abstractmethod
def preview_sync(
@@ -863,28 +873,30 @@ class StockBasedSync(BaseDataSync):
# 首次同步探测：验证表结构是否正常
if self._should_probe_table():
print(f"[{class_name}] Table '{self.table_name}' is empty or doesn't exist, probing...")
print(
f"[{class_name}] Table '{self.table_name}' is empty or doesn't exist, probing..."
)
# 使用第一只股票的完整日期范围数据进行探测
probe_stock = stock_codes[0]
probe_data = self.fetch_single_stock(
probe_stock, sync_start_date, end_date
)
probe_data = self.fetch_single_stock(probe_stock, sync_start_date, end_date)
probe_desc = f"stock={probe_stock}, range={sync_start_date} to {end_date}"
probe_success = self._probe_table_and_cleanup(probe_data, probe_desc)
if not probe_success:
print(f"[{class_name}] Probe failed! Stopping sync to prevent data corruption.")
print(
f"[{class_name}] Probe failed! Stopping sync to prevent data corruption."
)
raise RuntimeError(
f"Table '{self.table_name}' probe failed. "
"Please check database schema and column mappings."
)
if self._should_probe_table():
print(f"[{class_name}] Table '{self.table_name}' is empty or doesn't exist, probing...")
print(
f"[{class_name}] Table '{self.table_name}' is empty or doesn't exist, probing..."
)
# 使用第一只股票的完整日期范围数据进行探测
probe_stock = stock_codes[0]
probe_data = self.fetch_single_stock(
probe_stock, sync_start_date, end_date
)
probe_data = self.fetch_single_stock(probe_stock, sync_start_date, end_date)
probe_desc = f"stock={probe_stock}, range={sync_start_date} to {end_date}"
self._probe_table_and_cleanup(probe_data, probe_desc)
@@ -1335,10 +1347,8 @@ class DateBasedSync(BaseDataSync):
if self._should_probe_table():
print(f"[{class_name}] Table '{self.table_name}' is empty, probing...")
# 使用最近一个交易日的完整数据进行探测
from src.data.api_wrappers.api_trade_cal import get_last_n_trading_days
last_days = get_last_n_trading_days(1, sync_end)
if last_days:
probe_date = last_days[0]
probe_date = get_last_trading_day(sync_start, sync_end)
if probe_date:
probe_data = self.fetch_single_date(probe_date)
probe_desc = f"date={probe_date}, all stocks"
self._probe_table_and_cleanup(probe_data, probe_desc)

91
src/data/sync.py
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@@ -46,6 +46,7 @@ from src.data.api_wrappers.api_daily import sync_daily, preview_daily_sync
from src.data.api_wrappers.api_pro_bar import sync_pro_bar
from src.data.api_wrappers.api_bak_basic import sync_bak_basic
from src.data.api_wrappers.api_daily_basic import sync_daily_basic
from src.data.api_wrappers.api_stock_st import sync_stock_st
def preview_sync(
@@ -161,6 +162,7 @@ def sync_all_data(
4. Pro Bar 数据 (sync_pro_bar)
5. 每日指标数据 (sync_daily_basic)
6. 历史股票列表 (sync_bak_basic)
7. ST股票列表 (sync_stock_st)
【不包含的同步（需单独调用）】
- 财务数据: 利润表、资产负债表、现金流量表（季度更新）
@@ -195,53 +197,53 @@ def sync_all_data(
print("=" * 60)
# 1. Sync trade calendar (always needed first)
print("\n[1/5] Syncing trade calendar cache...")
print("\n[1/7] Syncing trade calendar cache...")
try:
from src.data.api_wrappers import sync_trade_cal_cache
sync_trade_cal_cache()
results["trade_cal"] = pd.DataFrame()
print("[1/5] Trade calendar: OK")
print("[1/7] Trade calendar: OK")
except Exception as e:
print(f"[1/5] Trade calendar: FAILED - {e}")
print(f"[1/7] Trade calendar: FAILED - {e}")
results["trade_cal"] = pd.DataFrame()
# 2. Sync stock basic info
print("\n[2/5] Syncing stock basic info...")
print("\n[2/7] Syncing stock basic info...")
try:
sync_all_stocks()
results["stock_basic"] = pd.DataFrame()
print("[2/5] Stock basic: OK")
print("[2/7] Stock basic: OK")
except Exception as e:
print(f"[2/5] Stock basic: FAILED - {e}")
print(f"[2/7] Stock basic: FAILED - {e}")
results["stock_basic"] = pd.DataFrame()
# 3. Sync daily market data
print("\n[3/5] Syncing daily market data...")
try:
# 确保表存在
from src.data.api_wrappers.api_daily import DailySync
DailySync().ensure_table_exists()
daily_result = sync_daily(
force_full=force_full,
max_workers=max_workers,
dry_run=dry_run,
)
results["daily"] = daily_result
total_daily_records = (
sum(len(df) for df in daily_result.values()) if daily_result else 0
)
print(
f"[3/5] Daily data: OK ({total_daily_records} records from {len(daily_result)} stocks)"
)
except Exception as e:
print(f"[3/5] Daily data: FAILED - {e}")
results["daily"] = pd.DataFrame()
# print("\n[3/7] Syncing daily market data...")
# try:
# # 确保表存在
# from src.data.api_wrappers.api_daily import DailySync
#
# DailySync().ensure_table_exists()
#
# daily_result = sync_daily(
# force_full=force_full,
# max_workers=max_workers,
# dry_run=dry_run,
# )
# results["daily"] = daily_result
# total_daily_records = (
# sum(len(df) for df in daily_result.values()) if daily_result else 0
# )
# print(
# f"[3/7] Daily data: OK ({total_daily_records} records from {len(daily_result)} stocks)"
# )
# except Exception as e:
# print(f"[3/7] Daily data: FAILED - {e}")
# results["daily"] = pd.DataFrame()
# 4. Sync Pro Bar data
print("\n[4/6] Syncing Pro Bar data (with adj, tor, vr)...")
print("\n[4/7] Syncing Pro Bar data (with adj, tor, vr)...")
try:
# 确保表存在
from src.data.api_wrappers.api_pro_bar import ProBarSync
@@ -258,15 +260,15 @@ def sync_all_data(
sum(len(df) for df in pro_bar_result.values()) if pro_bar_result else 0
)
print(
f"[4/6] Pro Bar data: OK ({total_pro_bar_records} records from {len(pro_bar_result)} stocks)"
f"[4/7] Pro Bar data: OK ({total_pro_bar_records} records from {len(pro_bar_result)} stocks)"
)
except Exception as e:
print(f"[4/6] Pro Bar data: FAILED - {e}")
print(f"[4/7] Pro Bar data: FAILED - {e}")
results["pro_bar"] = pd.DataFrame()
# 5. Sync daily basic indicators
print(
"\n[5/6] Syncing daily basic indicators (PE, PB, turnover rate, market value)..."
"\n[5/7] Syncing daily basic indicators (PE, PB, turnover rate, market value)..."
)
try:
# 确保表存在
@@ -276,13 +278,13 @@ def sync_all_data(
daily_basic_result = sync_daily_basic(force_full=force_full, dry_run=dry_run)
results["daily_basic"] = daily_basic_result
print(f"[5/6] Daily basic: OK ({len(daily_basic_result)} records)")
print(f"[5/7] Daily basic: OK ({len(daily_basic_result)} records)")
except Exception as e:
print(f"[5/6] Daily basic: FAILED - {e}")
print(f"[5/7] Daily basic: FAILED - {e}")
results["daily_basic"] = pd.DataFrame()
# 6. Sync stock historical list (bak_basic)
print("\n[6/6] Syncing stock historical list (bak_basic)...")
print("\n[6/7] Syncing stock historical list (bak_basic)...")
try:
# 确保表存在
from src.data.api_wrappers.api_bak_basic import BakBasicSync
@@ -291,11 +293,26 @@ def sync_all_data(
bak_basic_result = sync_bak_basic(force_full=force_full)
results["bak_basic"] = bak_basic_result
print(f"[6/6] Bak basic: OK ({len(bak_basic_result)} records)")
print(f"[6/7] Bak basic: OK ({len(bak_basic_result)} records)")
except Exception as e:
print(f"[6/6] Bak basic: FAILED - {e}")
print(f"[6/7] Bak basic: FAILED - {e}")
results["bak_basic"] = pd.DataFrame()
# 7. Sync ST stock list
print("\n[7/7] Syncing ST stock list...")
try:
# 确保表存在
from src.data.api_wrappers.api_stock_st import StockSTSync
StockSTSync().ensure_table_exists()
stock_st_result = sync_stock_st(force_full=force_full)
results["stock_st"] = stock_st_result
print(f"[7/7] ST stock list: OK ({len(stock_st_result)} records)")
except Exception as e:
print(f"[7/7] ST stock list: FAILED - {e}")
results["stock_st"] = pd.DataFrame()
# Summary
print("\n" + "=" * 60)
print("[sync_all_data] Sync Summary")

143
tests/test_stock_st.py Normal file
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@@ -0,0 +1,143 @@
"""Test suite for stock_st API wrapper."""
import pytest
import pandas as pd
from unittest.mock import patch, MagicMock
from src.data.api_wrappers.api_stock_st import get_stock_st, sync_stock_st, StockSTSync
class TestStockST:
"""Test suite for stock_st API wrapper."""
@patch("src.data.api_wrappers.api_stock_st.TushareClient")
def test_get_by_date(self, mock_client_class):
"""Test fetching ST stock list by date."""
# Setup mock
mock_client = MagicMock()
mock_client_class.return_value = mock_client
mock_client.query.return_value = pd.DataFrame(
{
"ts_code": ["300313.SZ", "605081.SH", "300391.SZ"],
"name": ["*ST天山", "*ST太和", "*ST长药"],
"trade_date": ["20240101", "20240101", "20240101"],
"type": ["ST", "ST", "ST"],
"type_name": ["风险警示板", "风险警示板", "风险警示板"],
}
)
# Test
result = get_stock_st(trade_date="20240101")
# Assert
assert not result.empty
assert len(result) == 3
assert "ts_code" in result.columns
assert "name" in result.columns
assert "trade_date" in result.columns
assert "type" in result.columns
assert "type_name" in result.columns
mock_client.query.assert_called_once()
@patch("src.data.api_wrappers.api_stock_st.TushareClient")
def test_get_by_stock(self, mock_client_class):
"""Test fetching ST history by stock code."""
# Setup mock
mock_client = MagicMock()
mock_client_class.return_value = mock_client
mock_client.query.return_value = pd.DataFrame(
{
"ts_code": ["300313.SZ", "300313.SZ"],
"name": ["*ST天山", "*ST天山"],
"trade_date": ["20240101", "20240102"],
"type": ["ST", "ST"],
"type_name": ["风险警示板", "风险警示板"],
}
)
# Test
result = get_stock_st(
ts_code="300313.SZ", start_date="20240101", end_date="20240102"
)
# Assert
assert not result.empty
assert len(result) == 2
mock_client.query.assert_called_once()
@patch("src.data.api_wrappers.api_stock_st.TushareClient")
def test_empty_response(self, mock_client_class):
"""Test handling empty response."""
mock_client = MagicMock()
mock_client_class.return_value = mock_client
mock_client.query.return_value = pd.DataFrame()
result = get_stock_st(trade_date="20240101")
assert result.empty
@patch("src.data.api_wrappers.api_stock_st.TushareClient")
def test_get_by_date_range(self, mock_client_class):
"""Test fetching ST stock list by date range."""
# Setup mock
mock_client = MagicMock()
mock_client_class.return_value = mock_client
mock_client.query.return_value = pd.DataFrame(
{
"ts_code": ["300313.SZ"],
"name": ["*ST天山"],
"trade_date": ["20240101"],
"type": ["ST"],
"type_name": ["风险警示板"],
}
)
# Test
result = get_stock_st(start_date="20240101", end_date="20240131")
# Assert
assert not result.empty
mock_client.query.assert_called_once()
class TestStockSTSync:
"""Test suite for StockSTSync class."""
def test_sync_class_attributes(self):
"""Test that sync class has correct attributes."""
sync = StockSTSync()
assert sync.table_name == "stock_st"
assert sync.default_start_date == "20160101"
assert "ts_code" in sync.TABLE_SCHEMA
assert "trade_date" in sync.TABLE_SCHEMA
assert "name" in sync.TABLE_SCHEMA
assert "type" in sync.TABLE_SCHEMA
assert "type_name" in sync.TABLE_SCHEMA
assert sync.PRIMARY_KEY == ("trade_date", "ts_code")
@patch("src.data.api_wrappers.api_stock_st.TushareClient")
def test_fetch_single_date(self, mock_client_class):
"""Test fetching single date data."""
# Setup mock
mock_client = MagicMock()
mock_client_class.return_value = mock_client
mock_client.query.return_value = pd.DataFrame(
{
"ts_code": ["300313.SZ"],
"name": ["*ST天山"],
"trade_date": ["20240101"],
"type": ["ST"],
"type_name": ["风险警示板"],
}
)
# Test
sync = StockSTSync()
result = sync.fetch_single_date("20240101")
# Assert
assert not result.empty
assert len(result) == 1
if __name__ == "__main__":
pytest.main([__file__, "-v"])