import json
import subprocess
from pathlib import Path

OUTPUT = Path("/app/output.json")
ROOT = Path("/app")


def load_output():
    assert OUTPUT.is_file()
    return json.loads(OUTPUT.read_text())


def run_reference():
    result = subprocess.run(
        ["python3", "/tests/fixtures/regression_probe.py", "/app", "/tmp/recomputed.json"],
        cwd="/tests", capture_output=True, text=True, timeout=30,
    )
    assert result.returncode == 0, result.stderr
    return json.loads(Path("/tmp/recomputed.json").read_text())


def test_gate_schema_and_files():
    payload = load_output()
    assert payload["output_schema_version"] == "tbench.early_stopping.repair.v1"
    assert set(payload["cases"]) == {"deferred_patience", "post_min_epochs", "min_steps_only", "recovery_after_defer"}
    assert set(payload["fit_loop_gates"]) == {"epoch_pending", "step_pending", "all_met", "no_minimums"}
    assert (ROOT / "vendor/pytorch-lightning/src/lightning/pytorch/callbacks/early_stopping.py").is_file()
    assert (ROOT / "vendor/pytorch-lightning/src/lightning/pytorch/loops/fit_loop.py").is_file()
    assert (ROOT / "run_regression.py").is_file()


def test_core_independent_recompute():
    expected = json.loads((Path("/tests/fixtures/expected.json")).read_text())
    assert load_output() == expected
    assert run_reference() == expected


def test_core_deferred_and_ordinary_stop():
    payload = load_output()["summary"]
    assert payload["deferred_stop"] is False
    assert payload["ordinary_stop"] is True
    assert payload["recovered"] is True


def test_core_min_steps_boundary():
    case = load_output()["cases"]["min_steps_only"]
    assert case[-1]["should_stop"] is True
    assert case[-1]["stopping_reason"] == "PATIENCE_EXHAUSTED"
    assert case[-1]["stopped_epoch"] == 1


def test_core_fit_loop_gate_matrix():
    gates = load_output()["fit_loop_gates"]
    assert gates["epoch_pending"] == {"met_min_epochs": False, "met_min_steps": True, "can_stop_early": False}
    assert gates["step_pending"] == {"met_min_epochs": True, "met_min_steps": False, "can_stop_early": False}
    assert gates["all_met"] == {"met_min_epochs": True, "met_min_steps": True, "can_stop_early": True}
    assert gates["no_minimums"] == {"met_min_epochs": True, "met_min_steps": True, "can_stop_early": True}


def test_edge_source_contract():
    callback = (ROOT / "vendor/pytorch-lightning/src/lightning/pytorch/callbacks/early_stopping.py").read_text()
    fit_loop = (ROOT / "vendor/pytorch-lightning/src/lightning/pytorch/loops/fit_loop.py").read_text()
    assert "trainer.strategy.reduce_boolean_decision" in callback
    assert "trainer.fit_loop._met_min_epochs" in callback
    assert "self.stopping_reason = EarlyStoppingReason.NOT_STOPPED" in callback
    assert "def _met_min_epochs" in fit_loop
    assert "def _met_min_steps" in fit_loop
    assert "return self._met_min_epochs and self._met_min_steps" in fit_loop