from __future__ import annotations

from abc import ABC, abstractmethod
from dataclasses import dataclass

import pandas as pd

from app.core.logger import setup_logger

logger = setup_logger("strategy")


@dataclass
class Signal:
    action: str  # buy / sell / hold
    stock_code: str
    qty: int = 0
    price: int = 0
    reason: str = ""
    confidence: float = 0.0
    strategy_id: int | None = None


class BaseStrategy(ABC):
    def __init__(self, stock_code: str, params: dict, strategy_id: int = 0) -> None:
        self.stock_code = stock_code
        self.params = params
        self.strategy_id = strategy_id
        self.name = self.__class__.__name__

    @abstractmethod
    def evaluate(self, current_price: dict, price_history: list[dict], holding_qty: int) -> Signal:
        ...

    @staticmethod
    def _to_dataframe(prices: list[dict]) -> pd.DataFrame:
        if not prices:
            return pd.DataFrame()
        df = pd.DataFrame(prices)
        for col in ["open", "high", "low", "close", "volume"]:
            if col in df.columns:
                df[col] = pd.to_numeric(df[col], errors="coerce")
        return df