"""Tests for transparent filtering rules."""

from __future__ import annotations

from swe_data_processing.heuristics import classify_metrics, length_bucket


def _metrics(*, failed: int = 0, calls: int = 10, streak: int = 0, tokens=50_000):
    return {
        "sample_id": "sample-1",
        "instance_id": "repo-1",
        "source_group": "example_group",
        "source_parquet": "/data/example.parquet",
        "resolved": 1,
        "length": {"turn_count": 30, "token_count": tokens},
        "tools": {
            "tool_call_count": calls,
            "failed_tool_call_count": failed,
            "failed_tool_call_rate": failed / calls if calls else 0.0,
            "longest_consecutive_failure_run": streak,
            "error_positions": {
                "early_count": failed,
                "early_fraction": 1.0 if failed else 0.0,
                "occupied_bins_5": min(failed, 5),
            },
            "error_type_counts": {},
            "error_tool_counts": {},
        },
        "structure": {
            "invalid_turn_count": 0,
            "malformed_tool_definition_count": 0,
            "malformed_tool_call_count": 0,
            "unknown_tool_call_count": 0,
            "missing_tool_result_count": 0,
            "orphan_tool_result_count": 0,
        },
    }


def test_length_buckets_match_training_limits() -> None:
    assert length_bucket(None) == "TOKENIZER_REQUIRED"
    assert length_bucket(81_920) == "LE_81920"
    assert length_bucket(81_921) == "81921_TO_131072"
    assert length_bucket(131_073) == "131073_TO_262144"
    assert length_bucket(262_145) == "GT_262144"


def test_five_consecutive_failures_is_hard_reject() -> None:
    decision = classify_metrics(_metrics(failed=5, calls=20, streak=5), 10)
    assert "FIVE_CONSECUTIVE_TOOL_FAILURES" in decision["hard_reject_reasons"]
    assert decision["recommended_action"] == "DROP_DEFINITE_TOOL_PROBLEM"


def test_early_cluster_is_review_only() -> None:
    decision = classify_metrics(_metrics(failed=3, calls=20, streak=2), 10)
    assert decision["hard_reject_reasons"] == []
    assert decision["review_flags"] == ["EARLY_FAILURE_CLUSTER"]
    assert decision["recommended_action"] == "REVIEW_HEURISTIC_HIT"


def test_relative_count_outlier_is_not_automatic_drop() -> None:
    decision = classify_metrics(_metrics(failed=10, calls=100, streak=2), 10)
    assert decision["hard_reject_reasons"] == []
    assert "EXTREME_ERROR_COUNT" in decision["review_flags"]


def test_distributed_failures_require_review_instead_of_automatic_drop() -> None:
    decision = classify_metrics(_metrics(failed=8, calls=40, streak=2), 20)
    assert decision["hard_reject_reasons"] == []
    assert "PERSISTENT_DISTRIBUTED_FAILURES" in decision["review_flags"]


def test_failed_outcome_is_never_recommended_for_training() -> None:
    metrics = _metrics()
    metrics["resolved"] = 0
    decision = classify_metrics(metrics, 10)
    assert decision["outcome_use"] == "EXCLUDE_FROM_SUCCESS_SFT"
    assert decision["recommended_action"] == "EXCLUDE_FAILED_OUTCOME"


def test_decision_keeps_source_provenance_for_targeted_review() -> None:
    decision = classify_metrics(_metrics(), 10)
    assert decision["source_group"] == "example_group"
    assert decision["source_parquet"] == "/data/example.parquet"