from event_taxonomy.adapters import (
    bus_factor,
    dep_risk,
    doc_drift,
    knowledge_silo,
    perf_regression,
    roadmap_entropy,
    schema_evolution,
    semantic_diff,
    test_flakiness,
)
from event_taxonomy.schema import Severity


def test_bus_factor():
    f = bus_factor.normalize({
        "file": "core.py",
        "top_author": "alice",
        "top_author_pct": 85.0,
        "num_contributors": 2,
        "bus_factor": 1,
        "risk_label": "CRITICAL",
    })
    assert f.severity == Severity.CRITICAL
    assert f.file == "core.py"
    assert "alice" in f.message


def test_dep_risk():
    f = dep_risk.normalize({
        "name": "requests",
        "ecosystem": "pypi",
        "version": "2.28.0",
        "risk_label": "HIGH",
        "vuln_count": 2,
        "months_stale": 6,
    })
    assert f.severity == Severity.HIGH
    assert "requests" in f.message


def test_doc_drift():
    f = doc_drift.normalize({
        "kind": "docstring_param",
        "severity": "error",
        "message": "Param x not in signature",
        "file": "model.py",
        "lineno": 42,
        "symbol": "process",
    })
    assert f.severity == Severity.HIGH
    assert f.line == 42
    assert f.file == "model.py"


def test_knowledge_silo():
    f = knowledge_silo.normalize({
        "filepath": "auth.py",
        "total_commits": 50,
        "dominant_author": "bob",
        "dominant_commits": 45,
        "other_authors": {"alice": 5},
        "risk": "HIGH",
    })
    assert f.severity == Severity.HIGH
    assert "bob" in f.message


def test_perf_regression():
    f = perf_regression.normalize({
        "pattern": "n-plus-one-query",
        "severity": 8,
        "file": "api.py",
        "line": 123,
        "message": "DB call inside loop",
        "snippet": "for x in items: db.query(x)",
    })
    assert f.severity == Severity.CRITICAL
    assert f.file == "api.py"
    assert f.line == 123


def test_roadmap_entropy():
    f = roadmap_entropy.normalize({
        "entropy_score": 0.65,
        "risk_label": "high",
        "base_count": 10,
        "head_count": 15,
        "item_count_delta": 5,
        "description_churn": 0.25,
        "priority_shuffles": 3,
    })
    assert f.severity == Severity.HIGH
    assert "0.65" in f.message


def test_schema_evolution():
    f = schema_evolution.normalize({
        "operation": {"op_type": "drop_column", "args": ["users", "password"]},
        "risk_level": "dangerous",
        "rationale": "Dropping column causes data loss",
        "recommendation": "Back up first",
    })
    assert f.severity == Severity.CRITICAL
    assert f.recommendation == "Back up first"


def test_semantic_diff():
    f = semantic_diff.normalize({
        "path": "api.py",
        "categories": ["REFACTOR", "FEATURE"],
        "summary": "Modified api.py",
        "added": 45,
        "removed": 23,
    })
    assert f.severity == Severity.MEDIUM
    assert f.file == "api.py"


def test_semantic_diff_large_churn():
    f = semantic_diff.normalize({
        "path": "big.py",
        "categories": ["FEATURE"],
        "summary": "Rewrote big.py",
        "added": 200,
        "removed": 50,
    })
    assert f.severity == Severity.HIGH


def test_test_flakiness():
    f = test_flakiness.normalize({
        "test_id": "tests.integration::test_auth",
        "classname": "tests.integration",
        "total_runs": 20,
        "pass_count": 12,
        "fail_count": 8,
        "error_count": 0,
        "skip_count": 0,
        "flakiness_rate": 0.4,
        "avg_duration": 1.25,
        "duration_stddev": 0.35,
    })
    assert f.severity == Severity.HIGH
    assert "40%" in f.message