from datetime import datetime

import pytest

from app.services import execution_quality as eq


def test_side_adjust_no_cancellation():
    rows = [
        {"order_type": "BUY", "slippage": 0.1, "strategy_type": "daytrading"},
        {"order_type": "SELL", "slippage": 0.1, "strategy_type": "daytrading"},
    ]
    r = eq.aggregate_execution_quality_v1(rows)["overall"]
    assert r["mean_cost_bp"] == 0.0
    assert r["mean_abs_bp"] == 10.0
    assert eq.slippage_cost_bp_v3("BUY", 0.1) == pytest.approx(10.0)
    assert eq.slippage_cost_bp_v3("SELL", 0.1) == pytest.approx(-10.0)


def test_matches_trade_executor_v2():
    te = pytest.importorskip("app.services.trade_executor")
    for side in ("BUY", "SELL", "HOLD"):
        for v in (0.1, -0.3, None, "x"):
            assert eq.slippage_cost_bp_v3(side, v) == te.slippage_cost_bp_v2(side, v)


def test_low_sample_null_and_groups():
    rows = [
        {"order_type": "BUY", "slippage": None, "strategy_type": "swing", "executed_quantity": 0},
        {"order_type": "BUY", "slippage": 0.2, "strategy_type": "daytrading", "executed_quantity": 5,
         "executed_at": datetime(2026, 10, 7, 9, 5), "fill_verified": True},
    ]
    r = eq.aggregate_execution_quality_v1(rows)
    assert r["overall"]["low_sample"] and r["overall"]["n_slippage"] == 1
    assert r["by_strategy"]["swing"]["mean_cost_bp"] is None
    assert r["by_hour"][9]["fill_verified_ratio"] == 1.0
    big = [{"order_type": "BUY", "slippage": 0.1}] * eq.LOW_SAMPLE_THRESHOLD
    assert not eq.aggregate_execution_quality_v1(big)["overall"]["low_sample"]


def test_invalid_inputs():
    for bad in (None, "x", float("nan"), float("inf")):
        assert eq.slippage_cost_bp_v3("BUY", bad) is None
    assert eq.slippage_cost_bp_v3("HOLD", 0.1) is None