"""
东方财富财务摘要 API (FastAPI 封装)
GET /fin/summary?stocks=603233.SH:10500736,600519.SH:xxxxxx
GET /fin/summary?stocks=603233.SH  (只传代码, 自动查 ORG_CODE, 不稳)

返回 JSON: {success, count, columns, data, errors}
"""
from __future__ import annotations

from typing import Optional

from fastapi import FastAPI, Query, HTTPException
from fastapi.responses import JSONResponse
import pandas as pd

# 复用 fin_summary.py 里的核心逻辑
from utils.fin_summary import get_fin_summary, _fetch_org_codes
from utils.fin_quarterly import get_fin_quarterly_summary


app = FastAPI(
    title="EMWeb API",
    description="东方财富 CHOICE API 数据抓取服务",
    version="0.1.0",
)


def _parse_stocks(raw: str) -> tuple[list[str], Optional[dict[str, str]]]:
    """
    解析 ?stocks= 参数.
      "603233.SH:10500736,600519.SH:xxxxxx" -> (codes, {code: org_code})
      "603233.SH,600519.SH"                 -> (codes, None) -> 自动查
      "603233.SH:10500736"                  -> (codes, {code: org_code}) 单只
    """
    codes: list[str] = []
    org_map: dict[str, str] = {}
    has_any_org = False
    for part in raw.split(","):
        part = part.strip()
        if not part:
            continue
        if ":" in part:
            code, org = part.split(":", 1)
            code = code.strip()
            org = org.strip()
            codes.append(code)
            if org:
                org_map[code] = org
                has_any_org = True
        else:
            codes.append(part.strip())
    if has_any_org and len(org_map) != len(codes):
        # 部分给了 ORG_CODE 部分没给 -> 退化为全部自动查
        return codes, None
    return codes, (org_map if has_any_org else None)


def _df_to_json_payload(df: pd.DataFrame) -> dict:
    """DataFrame -> JSON-safe dict."""
    import math
    safe = df.copy()
    # 处理 NaN / NaT / Timestamp / inf -> None
    for col in safe.columns:
        if pd.api.types.is_datetime64_any_dtype(safe[col]):
            safe[col] = safe[col].astype(str).replace("NaT", None)
    safe = safe.where(pd.notnull(safe), None)

    # 二次清理: inf / -inf / 极大值
    records = safe.to_dict(orient="records")
    cleaned = []
    for row in records:
        new_row = {}
        for k, v in row.items():
            if v is None:
                new_row[k] = None
            elif isinstance(v, float):
                if math.isnan(v) or math.isinf(v):
                    new_row[k] = None
                else:
                    new_row[k] = v
            else:
                new_row[k] = v
        cleaned.append(new_row)
    return {
        "success": True,
        "count": int(len(cleaned)),
        "columns": list(safe.columns),
        "data": cleaned,
    }


@app.get("/")
def root():
    return {
        "name": "EMWeb API",
        "version": "0.1.0",
        "endpoints": {
            "GET /fin/summary": "拉取财务摘要(报告期)",
            "GET /fin/quarterly-summary": "拉取季度财务摘要",
            "GET /health": "健康检查",
        },
        "usage": {
            "fin_summary": "/fin/summary?stocks=603233.SH:10500736&years=10",
            "fin_quarterly_summary": "/fin/quarterly-summary?stocks=603233.SH&years=3",
        },
    }


@app.get("/health")
def health():
    return {"status": "ok"}


@app.get("/fin/summary")
def fin_summary(
    stocks: str = Query(
        ...,
        description=(
            "股票列表, 逗号分隔. 支持仅代码自动查询；其中 '603233.SH' "
            "会自动解析为 ORG_CODE '10500736'。也可使用代码:ORG_CODE，"
            "如 '603233.SH:10500736,600519.SH:xxxxxx'"
        ),
        examples=["603233.SH", "603233.SH:10500736"],
    ),
    years: int = Query(10, ge=1, le=20, description="拉取多少年的历史"),
    date_type_codes: str = Query(
        "1,5,6",
        description="报告期代码, 逗号分隔. 1=一季报, 5=中报, 6=年报",
    ),
    is_newest: bool = Query(True, description="是否只要最新合并报表"),
):
    """拉取多只股票的财务摘要数据, 返回 JSON."""
    codes, org_map = _parse_stocks(stocks)
    if not codes:
        raise HTTPException(400, detail="stocks 参数不能为空")

    # 自动查 ORG_CODE
    if org_map is None:
        try:
            org_map = _fetch_org_codes(codes)
        except Exception as e:  # noqa: BLE001
            raise HTTPException(
                400,
                detail=(
                    f"自动查询失败: {e}. 请改用 '代码:ORG_CODE' 格式, "
                    f"ORG_CODE 可在 Reqable 抓包切换股票时拿到."
                ),
            )

    df = get_fin_summary(
        org_map,
        years=years,
        date_type_codes=date_type_codes,
        is_newest=is_newest,
        verbose=False,
    )
    if df.empty:
        return JSONResponse(
            status_code=404,
            content={
                "success": False,
                "count": 0,
                "message": "无数据, 请检查 ORG_CODE 或放宽筛选条件",
                "codes_requested": codes,
                "data": [],
            },
        )

    payload = _df_to_json_payload(df)
    payload["codes_requested"] = codes
    payload["years"] = years
    payload["date_type_codes"] = date_type_codes
    return payload


@app.get("/fin/quarterly-summary")
def fin_quarterly_summary(
    stocks: str = Query(
        ...,
        description="股票代码，逗号分隔，例如 '603233.SH,600519.SH'。仅支持代码，不需要 ORG_CODE。",
        examples=["603233.SH"],
    ),
    years: int = Query(3, ge=1, le=20, description="未传 report_dates 时拉取最近多少年的季度数据"),
    report_dates: Optional[str] = Query(
        None,
        description=(
            "可选，逗号分隔的 YYYY-MM-DD 报告期。未传时取最近 years 年季度数据；"
            "传入时精确筛选报告期，并按股票代码和报告期自动去重。"
        ),
        examples=["2025-03-31,2024-12-31"],
    ),
):
    """拉取季度财务摘要；指定报告期时执行精确报告期筛选。"""
    codes = [code.strip() for code in stocks.split(",") if code.strip()]
    if not codes:
        raise HTTPException(400, detail="stocks 参数不能为空")

    dates = None
    if report_dates is not None:
        dates = [date.strip() for date in report_dates.split(",") if date.strip()]
        if not dates:
            raise HTTPException(400, detail="report_dates 参数不能为空")

    df = get_fin_quarterly_summary(codes, years=years, report_dates=dates)
    if df.empty:
        return JSONResponse(
            status_code=404,
            content={
                "success": False,
                "count": 0,
                "message": "无季度财务摘要数据, 请检查股票代码或筛选条件",
                "codes_requested": codes,
                "years": years,
                "data": [],
            },
        )

    payload = _df_to_json_payload(df)
    payload["codes_requested"] = codes
    payload["years"] = years
    return payload


if __name__ == "__main__":
    import uvicorn
    uvicorn.run(app, host="0.0.0.0", port=8765, log_level="info")