from __future__ import annotations

import json
from datetime import datetime
from typing import Any


class MarketRepositoryMixin:
    def upsert_stock_master(self, rows: list[dict[str, Any]]) -> int:
        now = datetime.now().astimezone().isoformat(timespec="seconds")
        values = [
            (
                row.get("ts_code", ""),
                str(row.get("ts_code", "")).split(".")[0],
                row.get("name") or "--",
                row.get("industry") or "",
                row.get("market") or "",
                str(row.get("list_date") or ""),
                now,
            )
            for row in rows if row.get("ts_code")
        ]
        with self.connect() as connection:
            connection.executemany(
                """
                INSERT INTO stock_master
                    (ts_code, code, name, industry, market, list_date, updated_at)
                VALUES (?, ?, ?, ?, ?, ?, ?)
                ON CONFLICT(ts_code) DO UPDATE SET
                    code=excluded.code, name=excluded.name, industry=excluded.industry,
                    market=excluded.market, list_date=excluded.list_date, updated_at=excluded.updated_at
                """,
                values,
            )
        return len(values)

    def list_stock_master(self) -> list[dict[str, Any]]:
        with self.connect() as connection:
            rows = connection.execute(
                "SELECT ts_code, code, name, industry, market, list_date FROM stock_master"
            ).fetchall()
        return [dict(row) for row in rows]

    def upsert_daily_bars(self, rows: list[dict[str, Any]]) -> int:
        values = [
            (
                str(row.get("trade_date") or ""), row.get("ts_code", ""),
                float(row.get("open") or 0), float(row.get("high") or 0),
                float(row.get("low") or 0), float(row.get("close") or 0),
                float(row.get("pct_chg") or 0), float(row.get("vol") or 0),
                float(row.get("amount") or 0),
            )
            for row in rows if row.get("trade_date") and row.get("ts_code")
        ]
        with self.connect() as connection:
            connection.executemany(
                """
                INSERT INTO daily_bars
                    (trade_date, ts_code, open, high, low, close, pct_chg, vol, amount)
                VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?)
                ON CONFLICT(trade_date, ts_code) DO UPDATE SET
                    open=excluded.open, high=excluded.high, low=excluded.low,
                    close=excluded.close, pct_chg=excluded.pct_chg,
                    vol=excluded.vol, amount=excluded.amount
                """,
                values,
            )
        return len(values)

    def daily_bars_for_date(self, trade_date: str) -> list[dict[str, Any]]:
        with self.connect() as connection:
            rows = connection.execute(
                "SELECT * FROM daily_bars WHERE trade_date = ? ORDER BY ts_code",
                (trade_date,),
            ).fetchall()
        return [dict(row) for row in rows]
    def get_snapshot(self, trade_date: str) -> dict[str, Any] | None:
        with self.connect() as connection:
            row = connection.execute(
                "SELECT payload FROM dashboard_snapshots WHERE trade_date = ?",
                (trade_date,),
            ).fetchone()
        if not row:
            return None
        try:
            return json.loads(row["payload"])
        except json.JSONDecodeError:
            return None

    def get_latest_real_snapshot(
        self, trade_date: str, strictly_before: bool = False
    ) -> dict[str, Any] | None:
        operator = "<" if strictly_before else "<="
        with self.connect() as connection:
            row = connection.execute(
                f"""
                SELECT payload FROM dashboard_snapshots
                WHERE trade_date {operator} ? AND source != 'demo'
                ORDER BY trade_date DESC LIMIT 1
                """,
                (trade_date,),
            ).fetchone()
        if not row:
            return None
        try:
            return json.loads(row["payload"])
        except json.JSONDecodeError:
            return None

    def save_snapshot(self, trade_date: str, source: str, payload: dict[str, Any]) -> None:
        updated_at = datetime.now().astimezone().isoformat(timespec="seconds")
        record_count = sum(
            len(payload.get(key) or [])
            for key in ("limits", "broken", "down_limits", "yesterday_limits")
        )
        content = json.dumps(payload, ensure_ascii=False, separators=(",", ":"))
        with self.connect() as connection:
            connection.execute(
                """
                INSERT INTO dashboard_snapshots
                    (trade_date, source, payload, record_count, updated_at)
                VALUES (?, ?, ?, ?, ?)
                ON CONFLICT(trade_date) DO UPDATE SET
                    source = excluded.source,
                    payload = excluded.payload,
                    record_count = excluded.record_count,
                    updated_at = excluded.updated_at
                """,
                (trade_date, source, content, record_count, updated_at),
            )

    def get_data_snapshot(self, kind: str, cache_key: str) -> dict[str, Any] | None:
        with self.connect() as connection:
            row = connection.execute(
                "SELECT payload FROM data_snapshots WHERE kind = ? AND cache_key = ?",
                (kind, cache_key),
            ).fetchone()
        if not row:
            return None
        try:
            return json.loads(row["payload"])
        except json.JSONDecodeError:
            return None

    def get_latest_data_snapshot(
        self,
        kind: str,
        cache_key_prefix: str,
        maximum_cache_key: str,
        exclude_source: str = "",
    ) -> dict[str, Any] | None:
        source_clause = " AND source != ?" if exclude_source else ""
        parameters: list[Any] = [kind, f"{cache_key_prefix}%", maximum_cache_key]
        if exclude_source:
            parameters.append(exclude_source)
        with self.connect() as connection:
            row = connection.execute(
                f"""
                SELECT payload FROM data_snapshots
                WHERE kind = ? AND cache_key LIKE ? AND cache_key <= ?{source_clause}
                ORDER BY cache_key DESC LIMIT 1
                """,
                parameters,
            ).fetchone()
        if not row:
            return None
        try:
            return json.loads(row["payload"])
        except json.JSONDecodeError:
            return None

    def save_data_snapshot(
        self, kind: str, cache_key: str, source: str, payload: dict[str, Any]
    ) -> None:
        updated_at = datetime.now().astimezone().isoformat(timespec="seconds")
        content = json.dumps(payload, ensure_ascii=False, separators=(",", ":"))
        with self.connect() as connection:
            connection.execute(
                """
                INSERT INTO data_snapshots (kind, cache_key, source, payload, updated_at)
                VALUES (?, ?, ?, ?, ?)
                ON CONFLICT(kind, cache_key) DO UPDATE SET
                    source = excluded.source,
                    payload = excluded.payload,
                    updated_at = excluded.updated_at
                """,
                (kind, cache_key, source, content, updated_at),
            )

    def search_stock_master(self, query: str, limit: int = 12) -> list[dict[str, Any]]:
        text = str(query or "").strip()
        if not text:
            return []
        escaped = text.replace("\\", "\\\\").replace("%", "\\%").replace("_", "\\_")
        with self.connect() as connection:
            rows = connection.execute(
                """
                SELECT ts_code, code, name, industry, market, list_date
                FROM stock_master
                WHERE code = ? OR name = ? OR name LIKE ? ESCAPE '\\'
                ORDER BY
                    CASE WHEN code = ? THEN 0 WHEN name = ? THEN 1 ELSE 2 END,
                    list_date DESC,
                    code
                LIMIT ?
                """,
                (text, text, f"%{escaped}%", text, text, max(1, min(30, int(limit)))),
            ).fetchall()
        return [dict(row) for row in rows]

    def list_snapshot_payloads(self, end_date: str, limit: int = 260) -> list[dict[str, Any]]:
        with self.connect() as connection:
            rows = connection.execute(
                """
                SELECT trade_date, payload FROM dashboard_snapshots
                WHERE trade_date <= ? ORDER BY trade_date DESC LIMIT ?
                """,
                (end_date, limit),
            ).fetchall()
        result: list[dict[str, Any]] = []
        for row in reversed(rows):
            try:
                payload = json.loads(row["payload"])
            except json.JSONDecodeError:
                continue
            payload["_snapshot_date"] = row["trade_date"]
            result.append(payload)
        return result

    def start_sync(self, trade_date: str, source: str) -> int:
        started_at = datetime.now().astimezone().isoformat(timespec="seconds")
        with self.connect() as connection:
            cursor = connection.execute(
                """
                INSERT INTO sync_runs (trade_date, source, status, started_at)
                VALUES (?, ?, 'running', ?)
                """,
                (trade_date, source, started_at),
            )
            return int(cursor.lastrowid)

    def finish_sync(
        self,
        sync_id: int,
        status: str,
        record_count: int = 0,
        message: str = "",
        source: str | None = None,
    ) -> None:
        finished_at = datetime.now().astimezone().isoformat(timespec="seconds")
        with self.connect() as connection:
            connection.execute(
                """
                UPDATE sync_runs
                SET status = ?, finished_at = ?, record_count = ?, message = ?,
                    source = COALESCE(?, source)
                WHERE id = ?
                """,
                (status, finished_at, record_count, message[:1000], source, sync_id),
            )

    def status(self) -> dict[str, Any]:
        with self.connect() as connection:
            last_sync = connection.execute(
                """
                SELECT id, trade_date, source, status, started_at, finished_at,
                       record_count, message
                FROM sync_runs ORDER BY id DESC LIMIT 1
                """
            ).fetchone()
            snapshot_stats = connection.execute(
                """
                SELECT COUNT(*) AS dates, COALESCE(SUM(record_count), 0) AS records,
                       MAX(updated_at) AS updated_at
                FROM dashboard_snapshots
                """
            ).fetchone()
            watchlist_count = connection.execute("SELECT COUNT(*) FROM watchlist").fetchone()[0]
            note_count = connection.execute("SELECT COUNT(*) FROM review_notes").fetchone()[0]

        return {
            "database": str(self.path.name),
            "snapshot_dates": int(snapshot_stats["dates"]),
            "snapshot_records": int(snapshot_stats["records"]),
            "updated_at": snapshot_stats["updated_at"],
            "last_sync": dict(last_sync) if last_sync else None,
            "watchlist_count": int(watchlist_count),
            "note_count": int(note_count),
        }