手动刷新与自动补跑共用可用数据判定:日线推算或上一交易日快照记为部分/准备中成功,避免前端误报刷新失败。HTTP JSON 解析错误不再把请求正文写入日志。 Co-authored-by: Cursor <cursoragent@cursor.com> Co-authored-by: multica-agent <github@multica.ai>
157 lines
6.1 KiB
Python
157 lines
6.1 KiB
Python
from __future__ import annotations
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import json
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import time
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import urllib.error
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import urllib.request
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from typing import Any, Callable
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from datahub.adapters.base import AdapterError, MarketAdapter
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from datahub.normalize import (
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normalize_auction,
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normalize_calendar,
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normalize_daily,
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normalize_index_daily,
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normalize_moneyflow,
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normalize_stock,
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normalize_valuation,
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)
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TUSHARE_URL = "http://api.tushare.pro"
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TUSHARE_FIELDS = {
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"trade_cal": "exchange,cal_date,is_open,pretrade_date",
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"stock_basic": "ts_code,symbol,name,area,industry,market,list_status,list_date",
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"daily": "ts_code,trade_date,open,high,low,close,pct_chg,vol,amount",
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"daily_basic": "ts_code,trade_date,turnover_rate,volume_ratio,total_mv,circ_mv,pe_ttm,pb,ps_ttm,dv_ttm",
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"adj_factor": "ts_code,trade_date,adj_factor",
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"index_daily": "ts_code,trade_date,open,high,low,close,pct_chg,vol,amount",
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"moneyflow": (
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"ts_code,trade_date,buy_sm_amount,sell_sm_amount,buy_md_amount,sell_md_amount,"
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"buy_lg_amount,sell_lg_amount,buy_elg_amount,sell_elg_amount,net_mf_amount"
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),
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"stk_auction": "ts_code,trade_date,vol,price,amount,pre_close,turnover_rate,volume_ratio,float_share",
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}
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DATASET_API = {
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"calendar": "trade_cal",
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"stocks": "stock_basic",
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"daily": "daily",
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"valuation": "daily_basic",
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"adj_factor": "adj_factor",
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"index_daily": "index_daily",
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"moneyflow": "moneyflow",
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"auction": "stk_auction",
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}
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DEFAULT_INDEX_CODES = ("000001.SH", "399001.SZ", "399006.SZ", "000300.SH")
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class TushareAdapter(MarketAdapter):
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name = "tushare"
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def __init__(
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self,
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token: str,
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timeout: int = 30,
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transport: Callable[[str, dict[str, Any], str], list[dict[str, Any]]] | None = None,
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) -> None:
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self.token = token
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self.timeout = timeout
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self._transport = transport
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def probe(self) -> dict[str, Any]:
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if not self.token:
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return {"provider": self.name, "configured": False, "state": "unconfigured"}
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started = time.perf_counter()
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try:
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rows = self.fetch("calendar", {"exchange": "SSE", "start_date": "20200102", "end_date": "20200102"})
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except AdapterError as exc:
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return {
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"provider": self.name,
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"configured": True,
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"state": "error",
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"message": str(exc),
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"latency_ms": round((time.perf_counter() - started) * 1000),
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}
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return {
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"provider": self.name,
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"configured": True,
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"state": "ok" if rows else "empty",
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"latency_ms": round((time.perf_counter() - started) * 1000),
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}
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def fetch(self, dataset: str, params: dict[str, Any]) -> list[dict[str, Any]]:
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api_name = DATASET_API.get(dataset, dataset)
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fields = TUSHARE_FIELDS.get(api_name, "")
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query_params = dict(params)
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if api_name == "stock_basic" and "list_status" not in query_params:
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query_params["list_status"] = "L"
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if api_name == "trade_cal" and "exchange" not in query_params:
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query_params["exchange"] = "SSE"
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if api_name == "index_daily" and "ts_code" not in query_params:
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# Caller typically loops codes; a missing code would pull nothing useful.
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query_params.setdefault("ts_code", DEFAULT_INDEX_CODES[0])
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return self._query(api_name, query_params, fields)
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def fetch_index_daily(self, trade_date: str, codes: tuple[str, ...] = DEFAULT_INDEX_CODES) -> list[dict[str, Any]]:
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rows: list[dict[str, Any]] = []
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for ts_code in codes:
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rows.extend(self.fetch("index_daily", {"ts_code": ts_code, "trade_date": trade_date}))
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return rows
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def normalize(self, dataset: str, rows: list[dict[str, Any]]) -> list[dict[str, Any]]:
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mapping = {
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"calendar": normalize_calendar,
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"trade_cal": normalize_calendar,
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"stocks": normalize_stock,
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"stock_basic": normalize_stock,
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"daily": normalize_daily,
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"valuation": normalize_valuation,
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"daily_basic": normalize_valuation,
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"moneyflow": normalize_moneyflow,
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"auction": normalize_auction,
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"stk_auction": normalize_auction,
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"index_daily": normalize_index_daily,
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}
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fn = mapping.get(dataset)
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if fn is None:
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if dataset == "adj_factor":
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return [
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{
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"ts_code": str(row.get("ts_code") or "").upper(),
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"trade_date": str(row.get("trade_date") or ""),
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"adj_factor": row.get("adj_factor"),
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}
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for row in rows
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]
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raise AdapterError(f"unsupported dataset: {dataset}")
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return [fn(row) for row in rows]
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def _query(self, api_name: str, params: dict[str, Any], fields: str) -> list[dict[str, Any]]:
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if self._transport is not None:
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return self._transport(api_name, params, fields)
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if not self.token:
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raise AdapterError("Tushare token 未配置")
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payload = json.dumps(
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{"api_name": api_name, "token": self.token, "params": params, "fields": fields}
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).encode("utf-8")
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request = urllib.request.Request(
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TUSHARE_URL,
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data=payload,
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headers={"Content-Type": "application/json", "User-Agent": "XiaobaiDatahub/0.1"},
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method="POST",
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)
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try:
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with urllib.request.urlopen(request, timeout=self.timeout) as response:
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result = json.loads(response.read().decode("utf-8"))
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except json.JSONDecodeError:
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raise AdapterError("Tushare returned invalid json") from None
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except (urllib.error.URLError, TimeoutError) as exc:
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raise AdapterError(f"Tushare request failed: {exc}") from exc
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if result.get("code") != 0:
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raise AdapterError(result.get("msg") or "Tushare returned an unknown error")
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data = result.get("data") or {}
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columns = data.get("fields") or []
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return [dict(zip(columns, item)) for item in data.get("items") or []]
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