from __future__ import annotations

import importlib.util
from pathlib import Path
import sys

import pandas as pd

_SCRIPT_PATH = Path(__file__).resolve().parents[2] / "scripts" / "ensemble_overlay_backtest.py"
_SPEC = importlib.util.spec_from_file_location("ensemble_overlay_backtest", _SCRIPT_PATH)
assert _SPEC and _SPEC.loader
_MODULE = importlib.util.module_from_spec(_SPEC)
sys.modules[_SPEC.name] = _MODULE
_SPEC.loader.exec_module(_MODULE)
build_ensemble_returns = _MODULE.build_ensemble_returns
summarize_ensemble = _MODULE.summarize_ensemble


def test_build_ensemble_returns_uses_lagged_rolling_sharpe() -> None:
    dates = pd.date_range("2024-01-01", periods=6, freq="B")
    returns = pd.DataFrame(
        {
            "date": dates,
            "a": [0.0, 0.01, 0.015, 0.02, -0.02, -0.02],
            "b": [0.0, -0.01, -0.015, -0.02, 0.02, 0.02],
        }
    )
    ensemble, weights = build_ensemble_returns(returns, window=3)
    # Before enough history, fallback is equal weight.
    assert weights.loc[0, "a"] == 0.5
    assert weights.loc[1, "b"] == 0.5
    # Once trailing Sharpe is available, positive trailing performer gets all the weight.
    assert weights.loc[4, "a"] == 1.0
    assert weights.loc[4, "b"] == 0.0
    assert ensemble.loc[4, "ensemble_return"] == returns.loc[4, "a"]


def test_summarize_ensemble_reports_yearly_returns() -> None:
    dates = pd.to_datetime(["2024-12-30", "2024-12-31", "2025-01-02"])
    ensemble = pd.DataFrame({"date": dates, "ensemble_return": [0.0, 0.01, 0.02]})
    summary = summarize_ensemble(ensemble, initial_equity=100.0)
    assert round(summary["total_return_pct"], 4) == 3.02
    assert "2024" in summary["yearly_returns_pct"]
    assert "2025" in summary["yearly_returns_pct"]