"""Database migrations and CSV import."""
import csv
import logging
from pathlib import Path
from datetime import datetime

from .database import TradingDatabase
from .models import Trade, DailySummary

logger = logging.getLogger(__name__)


def migrate_csv_to_db(db: TradingDatabase, csv_path: Path) -> int:
    """
    Migrate trades from CSV file to SQLite database.

    Args:
        db: TradingDatabase instance
        csv_path: Path to trade_log.csv

    Returns:
        Number of trades migrated
    """
    if not csv_path.exists():
        logger.info("No CSV file to migrate")
        return 0

    # Check if database already has trades
    existing_count = db.count_trades()
    if existing_count > 0:
        logger.info(
            f"Database already has {existing_count} trades, skipping migration"
        )
        return 0

    migrated = 0
    try:
        with open(csv_path, "r", newline="") as f:
            reader = csv.DictReader(f)

            for row in reader:
                trade = _csv_row_to_trade(row)
                if trade:
                    try:
                        db.insert_trade(trade)
                        migrated += 1
                    except Exception as e:
                        logger.warning(
                            f"Failed to migrate trade {row.get('trade_id')}: {e}"
                        )

        logger.info(f"Migrated {migrated} trades from CSV to database")

    except Exception as e:
        logger.error(f"CSV migration failed: {e}")

    return migrated


def _csv_row_to_trade(row: dict) -> Trade | None:
    """Convert a CSV row to a Trade object."""
    try:
        return Trade(
            trade_id=row["trade_id"],
            symbol=row["symbol"],
            side=row["side"],
            entry_price=float(row["entry_price"]),
            exit_price=_safe_float(row.get("exit_price")),
            size=float(row["size"]),
            size_usdt=float(row["size_usdt"]),
            pnl_usd=_safe_float(row.get("pnl_usd")),
            pnl_pct=_safe_float(row.get("pnl_pct")),
            entry_time=row["entry_time"],
            exit_time=row.get("exit_time") or None,
            hold_duration_hours=_safe_float(row.get("hold_duration_hours")),
            reason=row.get("reason") or None,
            order_id_entry=row.get("order_id_entry") or None,
            order_id_exit=row.get("order_id_exit") or None,
        )
    except (KeyError, ValueError) as e:
        logger.warning(f"Invalid CSV row: {e}")
        return None


def _safe_float(value: str | None) -> float | None:
    """Safely convert string to float."""
    if value is None or value == "":
        return None
    try:
        return float(value)
    except ValueError:
        return None


def rebuild_daily_summaries(db: TradingDatabase) -> int:
    """
    Rebuild daily summary table from trades.

    Args:
        db: TradingDatabase instance

    Returns:
        Number of daily summaries created
    """
    sql = """
    SELECT
        DATE(exit_time) as date,
        COUNT(*) as total_trades,
        SUM(CASE WHEN pnl_usd > 0 THEN 1 ELSE 0 END) as winning_trades,
        SUM(pnl_usd) as total_pnl_usd
    FROM trades
    WHERE exit_time IS NOT NULL
    GROUP BY DATE(exit_time)
    ORDER BY date
    """

    rows = db.connection.execute(sql).fetchall()
    count = 0

    for row in rows:
        summary = DailySummary(
            date=row["date"],
            total_trades=row["total_trades"],
            winning_trades=row["winning_trades"],
            total_pnl_usd=row["total_pnl_usd"] or 0.0,
            max_drawdown_usd=0.0,  # Calculated separately
        )
        db.upsert_daily_summary(summary)
        count += 1

    # Calculate max drawdowns
    _calculate_daily_drawdowns(db)

    logger.info(f"Rebuilt {count} daily summaries")
    return count


def _calculate_daily_drawdowns(db: TradingDatabase) -> None:
    """Calculate and update max drawdown for each day."""
    sql = """
    SELECT trade_id, DATE(exit_time) as date, pnl_usd
    FROM trades
    WHERE exit_time IS NOT NULL
    ORDER BY exit_time
    """

    rows = db.connection.execute(sql).fetchall()

    # Track cumulative PnL and drawdown per day
    daily_drawdowns: dict[str, float] = {}
    cumulative_pnl = 0.0
    peak_pnl = 0.0

    for row in rows:
        date = row["date"]
        pnl = row["pnl_usd"] or 0.0

        cumulative_pnl += pnl
        peak_pnl = max(peak_pnl, cumulative_pnl)
        drawdown = peak_pnl - cumulative_pnl

        if date not in daily_drawdowns:
            daily_drawdowns[date] = 0.0
        daily_drawdowns[date] = max(daily_drawdowns[date], drawdown)

    # Update daily summaries with drawdown
    for date, drawdown in daily_drawdowns.items():
        db.connection.execute(
            "UPDATE daily_summary SET max_drawdown_usd = ? WHERE date = ?",
            (drawdown, date),
        )
    db.connection.commit()


def run_migrations(db: TradingDatabase, csv_path: Path) -> None:
    """
    Run all migrations.

    Args:
        db: TradingDatabase instance
        csv_path: Path to trade_log.csv for migration
    """
    logger.info("Running database migrations...")

    # Migrate CSV data if exists
    migrate_csv_to_db(db, csv_path)

    # Rebuild daily summaries
    rebuild_daily_summaries(db)

    logger.info("Migrations complete")