from __future__ import annotations

from arbitrade.perf.guardrails import evaluate_guardrails
from arbitrade.perf.latency import run_latency_profile


def test_run_latency_profile_contains_expected_shape() -> None:
    profile = run_latency_profile(iterations=50)

    scenarios = profile.get("scenarios")
    assert isinstance(scenarios, dict)
    assert set(scenarios) == {
        "book_update_burst",
        "execution_spike",
        "reconnect_storm",
    }

    for payload in scenarios.values():
        assert isinstance(payload, dict)
        stages = payload.get("stages")
        assert isinstance(stages, dict)
        assert "end_to_end" in stages


def test_evaluate_guardrails_flags_regression() -> None:
    baseline = {
        "scenarios": {
            "book_update_burst": {
                "stages": {
                    "end_to_end": {"p95_ms": 1.0, "p99_ms": 1.0},
                }
            }
        }
    }
    current = {
        "scenarios": {
            "book_update_burst": {
                "stages": {
                    "end_to_end": {"p95_ms": 4.0, "p99_ms": 4.0},
                }
            }
        }
    }
    thresholds = {"default": {"p95_ms": 2.0, "p99_ms": 2.0}}

    failures = evaluate_guardrails(baseline=baseline, current=current, thresholds=thresholds)

    assert failures
    assert "latency regression" in failures[0]