"""Screener engine — ScreenContext (Phase 0) + Screener/combine (Phase 2)."""

from __future__ import annotations

import datetime as dt
import sqlite3
from dataclasses import dataclass, replace

import pandas as pd


@dataclass(frozen=True)
class ScreenContext:
    """1회 실행 동안 공유되는 읽기 전용 데이터 컨테이너."""
    master: pd.DataFrame                       # index=ticker
    prices: pd.DataFrame                       # cols: ticker,date,open,high,low,close,volume,value
    flow:   pd.DataFrame                       # cols: ticker,date,foreign_net,institution_net
    kospi:  pd.Series                          # index=date(str), name="kospi"
    asof:   dt.date

    @classmethod
    def load(cls, conn: sqlite3.Connection, asof: dt.date,
             lookback_days: int = 252 * 2) -> "ScreenContext":
        cutoff = (asof - dt.timedelta(days=int(lookback_days * 1.5))).isoformat()
        asof_iso = asof.isoformat()

        master = pd.read_sql_query(
            "SELECT * FROM krx_master",
            conn, index_col="ticker",
        )
        prices = pd.read_sql_query(
            "SELECT ticker,date,open,high,low,close,volume,value "
            "FROM krx_daily_prices WHERE date BETWEEN ? AND ? ORDER BY date",
            conn, params=(cutoff, asof_iso),
        )
        flow = pd.read_sql_query(
            "SELECT ticker,date,foreign_net,institution_net "
            "FROM krx_flow WHERE date BETWEEN ? AND ? ORDER BY date",
            conn, params=(cutoff, asof_iso),
        )

        # KOSPI 지수: MVP에서는 005930(삼성전자) 종가를 시장 대용으로 사용.
        # 후속 슬라이스에서 ^KS11 별도 캐시.
        kospi = pd.Series(dtype=float, name="kospi")
        if "005930" in master.index and not prices.empty:
            sub = prices[prices["ticker"] == "005930"].set_index("date")["close"]
            kospi = sub.copy()
            kospi.name = "kospi"

        return cls(master=master, prices=prices, flow=flow, kospi=kospi, asof=asof)

    def restrict(self, tickers) -> "ScreenContext":
        tickers = pd.Index(tickers)
        return replace(
            self,
            master=self.master.loc[self.master.index.intersection(tickers)],
            prices=self.prices[self.prices["ticker"].isin(tickers)],
            flow=self.flow[self.flow["ticker"].isin(tickers)],
        )

    def latest_close(self) -> pd.Series:
        if self.prices.empty:
            return pd.Series(dtype=float)
        return self.prices.sort_values("date").groupby("ticker")["close"].last()

    def latest_high(self) -> pd.Series:
        if self.prices.empty:
            return pd.Series(dtype=float)
        return self.prices.sort_values("date").groupby("ticker")["high"].last()