"""东方财富 CHOICE API 季度财务摘要抓取工具。"""
from __future__ import annotations

import pandas as pd
import requests

from utils.fin_summary import BASE_URL, HEADERS, TIMEOUT


_REPORT_NAME = "RPT_HSF9_FIN_SUMMARYQUARTERNEW"
_COLUMNS = "HSF9_FIN_SUMMARYQUARTER"


def _build_filter(
    secucode: str,
    years: int,
    report_dates: list[str] | None,
) -> str:
    if report_dates is not None:
        dates = ",".join(f"'{date}'" for date in report_dates)
        return f'(secuCode="{secucode}")(REPORTDATE in ({dates}))'

    today = pd.Timestamp.today()
    start = (today - pd.DateOffset(years=years)).strftime("%Y-%m-%d")
    end = today.strftime("%Y-%m-%d")
    return (
        f'(secuCode="{secucode}")'
        f"((REPORTDATE>='{start}')(REPORTDATE<='{end}')"
        '(dateType in ("1","2","3","4","7"))(|IS_NEWEST="1"))'
        '(TYPE_CODE in ("1"))'
    )


def _fetch_one(
    secucode: str,
    years: int,
    report_dates: list[str] | None,
) -> pd.DataFrame:
    params = {
        "reportName": _REPORT_NAME,
        "columns": _COLUMNS,
        "filter": _build_filter(secucode, years, report_dates),
        "pageNumber": "1",
        "pageSize": "500",
        "sortTypes": "-1,1" if report_dates is None else "-1",
        "sortColumns": "REPORTDATE,TYPE" if report_dates is None else "REPORTDATE",
        "source": "CHOICE",
        "client": "SW",
    }
    response = requests.post(BASE_URL, headers=HEADERS, data=params, timeout=TIMEOUT)
    response.raise_for_status()
    payload = response.json()
    if not payload.get("success"):
        raise RuntimeError(f"{secucode}: 接口返回失败: {payload}")

    rows = payload.get("result", {}).get("data") or []
    df = pd.DataFrame(rows)
    if not df.empty:
        df["SECUCODE"] = secucode
    return df


def get_fin_quarterly_summary(
    secucodes: list[str],
    years: int = 3,
    report_dates: list[str] | None = None,
) -> pd.DataFrame:
    """抓取指定股票的季度财务摘要并按股票代码和报告期去重、倒序排列。"""
    codes = [code.strip() for code in secucodes if code.strip()]
    if not codes:
        return pd.DataFrame()

    frames: list[pd.DataFrame] = []
    for code in codes:
        df = _fetch_one(code, years, report_dates)
        if not df.empty:
            frames.append(df)

    if not frames:
        return pd.DataFrame()

    result = pd.concat(frames, ignore_index=True)
    if {"SECUCODE", "REPORT_DATE"}.issubset(result.columns):
        result = result.drop_duplicates(["SECUCODE", "REPORT_DATE"], keep="first")
        result = result.sort_values(
            ["SECUCODE", "REPORT_DATE"], ascending=[True, False]
        )
    return result.reset_index(drop=True)