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DinQuant/backend_api_python/app/data_sources/cn_stock.py
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2026-04-07 22:47:07 +08:00
"""
中国A股数据源 — 多层 fallback
有 TWELVE_DATA_API_KEY:
所有周期 → Twelve Data(主) → 腾讯日/周线 → yfinance → AkShare
无 API Key:
分钟/小时 → yfinance → AkShare
日/周线 → 腾讯 fqkline → yfinance → AkShare
"""
from __future__ import annotations
from typing import Dict, List, Any, Optional
from app.data_sources.base import BaseDataSource
from app.data_sources.tencent import normalize_cn_code, fetch_quote, parse_quote_to_ticker, fetch_kline, tencent_kline_rows_to_dicts
from app.data_sources.asia_stock_kline import (
normalize_chart_timeframe,
fetch_twelvedata_klines,
fetch_yfinance_klines,
fetch_akshare_minute_klines,
fetch_akshare_weekly_klines,
)
from app.utils.logger import get_logger
logger = get_logger(__name__)
class CNStockDataSource(BaseDataSource):
"""A股数据源(TwelveData + Tencent + yfinance + AkShare"""
name = "CNStock/multi-source"
def get_ticker(self, symbol: str) -> Dict[str, Any]:
code = normalize_cn_code(symbol)
parts = fetch_quote(code)
if not parts:
return {"last": 0, "symbol": code}
t = parse_quote_to_ticker(parts)
return {
"last": t.get("last", 0),
"change": t.get("change", 0),
"changePercent": t.get("changePercent", 0),
"high": t.get("high", 0),
"low": t.get("low", 0),
"open": t.get("open", 0),
"previousClose": t.get("previousClose", 0),
"name": t.get("name", ""),
"symbol": code,
}
def get_kline(
self,
symbol: str,
timeframe: str,
limit: int,
before_time: Optional[int] = None,
) -> List[Dict[str, Any]]:
code = normalize_cn_code(symbol)
tf = normalize_chart_timeframe(timeframe)
lim = max(int(limit or 300), 1)
# Tier 1: Twelve Data (paid, most reliable)
rows = fetch_twelvedata_klines(
is_hk=False, tencent_code=code, timeframe=tf, limit=lim, before_time=before_time
)
if rows:
return self.filter_and_limit(rows, limit=lim, before_time=before_time)
# Tier 2: Tencent for daily/weekly (fast, free)
if tf in ("1D", "1W"):
tf_map = {"1D": "day", "1W": "week"}
period = tf_map.get(tf, "day")
raw_rows = fetch_kline(code, period=period, count=lim, adj="qfq")
out = tencent_kline_rows_to_dicts(raw_rows)
if out:
return self.filter_and_limit(out, limit=lim, before_time=before_time)
# Tier 3: yfinance (works when Yahoo not rate-limited)
rows = fetch_yfinance_klines(
is_hk=False, tencent_code=code, timeframe=tf, limit=lim, before_time=before_time
)
if rows:
return self.filter_and_limit(rows, limit=lim, before_time=before_time)
# Tier 4: AkShare (fragile overseas, last resort)
if tf in ("1m", "5m", "15m", "30m", "1H", "4H"):
rows = fetch_akshare_minute_klines(
is_hk=False, tencent_code=code, timeframe=tf, limit=lim, before_time=before_time
)
elif tf == "1W":
rows = fetch_akshare_weekly_klines(
is_hk=False, tencent_code=code, limit=lim, before_time=before_time
)
else:
rows = []
return self.filter_and_limit(rows, limit=lim, before_time=before_time)