import pandas as pd

from futures_overlay import optimize_futures_overlay


def test_optimize_futures_overlay_returns_empty_when_no_cash():
    weights = pd.Series({"SPY": 0.6, "TLT": 0.3, "CASH": 0.0})
    betas = pd.Series({"SPY": 1.0, "TLT": 0.2})
    cfg = {
        "with_futures": True,
        "overlay_mode": "beta_hedge",
        "futures_universe": ["MES", "ES"],
        "futures_safety_multiplier": 3.0,
        "futures_margin_headroom": 0.05,
        "futures_target_beta": 0.0,
    }

    result = optimize_futures_overlay(weights, betas, capital=100000.0, cfg=cfg)
    assert result.contracts == {}
    assert result.margin_used == 0.0


def test_optimize_futures_overlay_preserves_core_weights():
    weights = pd.Series({"SPY": 0.6, "TLT": 0.3, "CASH": 0.1})
    betas = pd.Series({"SPY": 1.0, "TLT": 0.1})
    cfg = {
        "with_futures": True,
        "overlay_mode": "beta_hedge",
        "futures_universe": ["MES", "ES"],
        "futures_safety_multiplier": 3.0,
        "futures_margin_headroom": 0.05,
        "futures_target_beta": 0.0,
    }

    result = optimize_futures_overlay(weights, betas, capital=100000.0, cfg=cfg)
    assert weights["CASH"] == 0.1
    assert isinstance(result.contracts, dict)
    assert result.overlay_mode == "hedge"


def test_optimize_futures_overlay_respects_margin_headroom():
    weights = pd.Series({"SPY": 0.6, "TLT": 0.3, "CASH": 0.05})
    betas = pd.Series({"SPY": 1.0, "TLT": 0.2})
    cfg = {
        "with_futures": True,
        "overlay_mode": "beta_hedge",
        "futures_universe": ["MES", "ES"],
        "futures_safety_multiplier": 3.0,
        "futures_margin_headroom": 0.05,
        "futures_target_beta": 0.0,
    }

    result = optimize_futures_overlay(weights, betas, capital=100000.0, cfg=cfg)
    assert result.margin_used <= 100000.0 * weights["CASH"]