"""Fix metrica `win`: una trade è win solo se il PnL è positivo NETTO delle fee, non sul
lordo. Prima del fix `is_win = trade_return > 0` (lordo): un take-profit colpito con un
movimento più piccolo del round-trip fee veniva contato come win pur perdendo denaro,
gonfiando l'accuracy (es. MR01/DIP01 BTC in regime piatto: TP entro le fee)."""
import pandas as pd
from src.live.strategy_worker import StrategyWorker
from src.live.strategy_loader import load_strategy


def _worker(tmp, fee_rt=0.001):
    w = StrategyWorker(strategy=load_strategy("MR01_bollinger_fade"), asset="BTC", tf="1h",
                       capital=1000.0, data_dir=tmp)
    w._notify = lambda *a, **k: None
    w.fee_rt = fee_rt
    w.in_position = True
    w.direction = 1
    w.entry_price = 100.0
    return w


def _last_close(w):
    import json
    rows = [json.loads(l) for l in w.trades_path.read_text().strip().splitlines()]
    return [r for r in rows if r.get("event") == "CLOSE"][-1]


def test_tiny_favorable_move_is_loss_after_fees(tmp_path):
    """Mossa lorda +0,05% < fee RT 0,10%: prezzo salito, ma netto negativo -> NON è win."""
    w = _worker(tmp_path, fee_rt=0.001)
    w._close_position(100.05, "take_profit")     # +0.05% lordo, sotto le fee
    c = _last_close(w)
    assert c["net_return"] < 0
    assert c["win"] is False                      # prima del fix era True
    assert w.total_wins == 0


def test_move_beyond_fees_is_win(tmp_path):
    """Mossa lorda +0,30% > fee 0,10%: netto positivo -> win."""
    w = _worker(tmp_path, fee_rt=0.001)
    w._close_position(100.30, "take_profit")
    c = _last_close(w)
    assert c["net_return"] > 0
    assert c["win"] is True
    assert w.total_wins == 1


def test_loss_is_not_win(tmp_path):
    """Prezzo sceso su long: perdita netta -> non win."""
    w = _worker(tmp_path, fee_rt=0.001)
    w._close_position(99.0, "stop_loss")
    c = _last_close(w)
    assert c["win"] is False
    assert w.total_wins == 0