mirror of
https://ghfast.top/https://github.com/aeroxw/easy_tdx_max.git
synced 2026-09-12 18:04:20 +08:00
Justin Gu
eb8a7a5675
- App factory with lifespan management and CORS middleware
- Market router: security list, quotes, market stat, fund-flow
- Bars router: kline, index kline, minute, transaction
- Finance router: xdxr, finance, company info, financial records
- Block router: block file parsing
- Chanlun router: POST /chanlun/analyze
- Realtime router: WebSocket /ws/realtime/{symbol}
- CLI: easy-tdx serve command
- 16 unit tests, all passing offline (no network)
114 lines
3.8 KiB
Python
114 lines
3.8 KiB
Python
"""K线 / 分时 / 逐笔成交路由。"""
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from __future__ import annotations
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from typing import Any
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from fastapi import APIRouter, Depends, Query
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from easy_tdx.web.deps import get_client
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from easy_tdx.web.schemas import DataFrameResponse, KlineCategoryEnum
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router = APIRouter(tags=["bars"])
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def _market(market: str) -> Any:
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from easy_tdx.models.enums import Market
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return Market[market.upper()]
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def _category(category: str) -> Any:
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from easy_tdx.models.enums import KlineCategory
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# Support both int and string name
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try:
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return KlineCategory(int(category))
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except (ValueError, TypeError):
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return KlineCategory[KlineCategoryEnum[category.upper()].name]
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def _df_resp(df: Any) -> DataFrameResponse:
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return DataFrameResponse.from_dataframe(df)
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@router.get("/bars", response_model=DataFrameResponse)
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async def security_bars(
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market: str = Query(..., description="市场: SZ, SH, BJ"),
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code: str = Query(..., min_length=6, max_length=6),
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category: str = Query(
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"DAY",
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description="K线周期: MIN_1, MIN_5, MIN_15, MIN_30, MIN_60, DAY, WEEK, MONTH, YEAR",
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),
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start: int = Query(0, ge=0),
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count: int = Query(800, ge=1, le=800),
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client: Any = Depends(get_client),
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) -> DataFrameResponse:
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"""获取股票K线数据。"""
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df = await client.get_security_bars(_market(market), code, _category(category), start, count)
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return _df_resp(df)
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@router.get("/bars/index", response_model=DataFrameResponse)
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async def index_bars(
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market: str = Query(..., description="市场: SZ, SH"),
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code: str = Query(..., min_length=6, max_length=6),
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category: str = Query("DAY", description="K线周期"),
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start: int = Query(0, ge=0),
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count: int = Query(800, ge=1, le=800),
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client: Any = Depends(get_client),
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) -> DataFrameResponse:
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"""获取指数K线数据。"""
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df = await client.get_index_bars(_market(market), code, _category(category), start, count)
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return _df_resp(df)
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@router.get("/minute", response_model=DataFrameResponse)
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async def minute_time(
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market: str = Query(..., description="市场: SZ, SH"),
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code: str = Query(..., min_length=6, max_length=6),
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client: Any = Depends(get_client),
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) -> DataFrameResponse:
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"""获取今日分时数据。"""
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df = await client.get_minute_time_data(_market(market), code)
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return _df_resp(df)
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@router.get("/minute/history", response_model=DataFrameResponse)
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async def history_minute_time(
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market: str = Query(..., description="市场: SZ, SH"),
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code: str = Query(..., min_length=6, max_length=6),
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date: int = Query(..., description="日期 YYYYMMDD"),
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client: Any = Depends(get_client),
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) -> DataFrameResponse:
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"""获取历史某日分时数据。"""
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df = await client.get_history_minute_time_data(_market(market), code, date)
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return _df_resp(df)
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@router.get("/transaction", response_model=DataFrameResponse)
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async def transaction_data(
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market: str = Query(..., description="市场: SZ, SH"),
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code: str = Query(..., min_length=6, max_length=6),
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start: int = Query(0, ge=0),
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count: int = Query(800, ge=1, le=800),
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client: Any = Depends(get_client),
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) -> DataFrameResponse:
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"""获取当日逐笔成交。"""
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df = await client.get_transaction_data(_market(market), code, start, count)
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return _df_resp(df)
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@router.get("/transaction/history", response_model=DataFrameResponse)
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async def history_transaction_data(
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market: str = Query(..., description="市场: SZ, SH"),
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code: str = Query(..., min_length=6, max_length=6),
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date: int = Query(..., description="日期 YYYYMMDD"),
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start: int = Query(0, ge=0),
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count: int = Query(800, ge=1, le=800),
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client: Any = Depends(get_client),
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) -> DataFrameResponse:
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"""获取历史逐笔成交。"""
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df = await client.get_history_transaction_data(_market(market), code, date, start, count)
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return _df_resp(df)
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