"""
End-to-end pipeline test for fixture 3 (lone_wolf).

Loads the YAML spec, runs the synthetic generator, applies the
identity-clusterer placeholder (each attacker → its own cluster), and
scores against the expected bounds. This is the simplest of the six
fixtures and is deliberately the first one wired up — its ground truth
is all singletons, so an identity clusterer trivially passes, which
proves the DSL → factory → metrics pipeline works before any real
algorithm is built.

Once the connected-components clusterer (CAMPAIGN_CLUSTERING.md §4)
lands, the same fixture must continue to pass.
"""
from __future__ import annotations

from pathlib import Path

import pytest

from tests.clustering.fixture_harness import (
    assert_fixture_bounds,
    identity_clusterer,
)
from tests.clustering.metrics import score
from tests.factories.campaign_factory import generate, load_yaml

FIXTURE_DIR = Path(__file__).parent.parent / "fixtures" / "campaigns"


def test_lone_wolf_pipeline_passes_bounds() -> None:
    spec = load_yaml(FIXTURE_DIR / "lone_wolf.yaml")
    corpus = generate(spec, seed=0)
    assert_fixture_bounds(corpus, identity_clusterer, FIXTURE_DIR / "lone_wolf.expected.yaml")


def test_lone_wolf_corpus_shape() -> None:
    """Sanity: 1 wolf + 8 noise scanners = 9 attackers, 9 sessions."""
    spec = load_yaml(FIXTURE_DIR / "lone_wolf.yaml")
    corpus = generate(spec, seed=0)
    assert len(corpus.attackers) == 9
    assert len(corpus.sessions) == 9
    truth_campaigns = {a.truth_campaign_id for a in corpus.attackers}
    assert len(truth_campaigns) == 9


def test_identity_clusterer_fails_on_a_real_campaign() -> None:
    """
    Sanity for the harness, NOT a test of the clusterer: a real
    multi-actor campaign should make the placeholder identity clusterer
    fail completeness, since each truth-campaign gets fragmented into
    one-member clusters. If this didn't fail, our metrics would be
    blind to false splits — and that's the entire point of fixtures 4
    and 5 in the design doc.
    """
    spec = {
        "campaign": {
            "id": "c-real",
            "actors": [
                {"id": "a-1", "asn": 14061},
                {"id": "a-2", "asn": 14061},
            ],
            "phases": [
                {"name": "delivery", "actor": "a-1"},
                {"name": "discovery", "actor": "a-2"},
            ],
            "duration_days": 1,
        }
    }
    corpus = generate(spec, seed=0)
    pred = identity_clusterer(corpus)
    metrics = score(corpus.truth_labels(), pred)
    assert metrics["completeness"] < 1.0
    assert metrics["homogeneity"] == pytest.approx(1.0)