"""Signal-driven multi-stock strategy."""
import backtrader as bt
import pandas as pd


class AlphaStrategy(bt.Strategy):
    """Trade feeds based on precomputed ``signal`` line.

    Supports two builder modes:
    - ThresholdBuilder: per-stock threshold (passed ``(signal_value, in_position)``)
    - RankEqualWeightBuilder: cross-sectional ranking (passed ``{symbol: signal}`` dict)
    """

    def __init__(self, builder):
        self.builder = builder

    def next(self):
        # Collect all signals
        signals: dict[str, float] = {}
        for data in self.datas:
            sig = data.signal[0]
            if not pd.isna(sig):
                signals[data._name] = float(sig)

        if not signals:
            return

        # Detect builder type: if RankEqualWeightBuilder, use cross-sectional mode
        from portfolio.builder import RankEqualWeightBuilder
        if isinstance(self.builder, RankEqualWeightBuilder):
            actions = self.builder.build(signals)
            for data in self.datas:
                name = data._name
                if name not in actions:
                    continue
                action = actions[name]
                if action.action == "buy":
                    self.order_target_percent(data=data, target=action.size_pct)
                elif action.action == "sell":
                    self.close(data=data)
        else:
            # Legacy per-stock ThresholdBuilder
            for data in self.datas:
                name = data._name
                if name not in signals:
                    continue
                in_position = bool(self.getposition(data).size)
                action = self.builder.build(signals[name], in_position)
                if action.action == "buy":
                    self.order_target_percent(data=data, target=action.size_pct)
                elif action.action == "sell":
                    self.close(data=data)