shinkan-jinkendo/backend/tests/test_planning_path_rematch.py

"""Tests Auto-Rematch nach Pfad-QS (Phase A)."""
from planning_path_rematch import collect_rematch_slot_indices, rematch_roadmap_slots
from planning_progression_roadmap import ProgressionRoadmapContext, StageSpecArtifact


def _stage_specs():
    return [
        StageSpecArtifact(major_step_index=0, learning_goal="Grundlage"),
        StageSpecArtifact(major_step_index=1, learning_goal="Vertiefung"),
        StageSpecArtifact(major_step_index=2, learning_goal="Anwendung"),
    ]


def test_collect_rematch_slot_indices_from_stripped_with_major_index():
    specs = _stage_specs()
    stripped = [
        {
            "step_index": 1,
            "roadmap_major_step_index": 1,
            "issue": "technique_scope",
            "reasons": ["Passt nicht zur Haupttechnik"],
        }
    ]
    indices, reasons = collect_rematch_slot_indices(
        stripped_off_topic=stripped,
        off_topic_steps=[],
        optimization_hints=[],
        stage_specs=specs,
    )
    assert indices == {1}
    assert "Haupttechnik" in reasons[1]


def test_collect_rematch_slot_indices_resolves_step_index_to_major():
    specs = _stage_specs()
    off_topic = [
        {
            "step_index": 2,
            "issue": "stage_mismatch",
            "reasons": ["Ziel passt nicht"],
        }
    ]
    indices, reasons = collect_rematch_slot_indices(
        stripped_off_topic=[],
        off_topic_steps=off_topic,
        optimization_hints=[],
        stage_specs=specs,
    )
    assert indices == {2}
    assert reasons[2] == "Ziel passt nicht"


def test_collect_rematch_slot_indices_from_optimization_hints():
    specs = _stage_specs()
    hints = [
        {
            "action": "rematch_slot",
            "roadmap_major_step_index": 0,
            "reason": "QS-Tier-1",
        }
    ]
    indices, _ = collect_rematch_slot_indices(
        stripped_off_topic=[],
        off_topic_steps=[],
        optimization_hints=hints,
        stage_specs=specs,
    )
    assert indices == {0}


def test_rematch_roadmap_slots_replaces_only_target_slot():
    specs = _stage_specs()
    ctx = ProgressionRoadmapContext(
        goal_query="Mawashi Geri",
        max_steps=3,
        stage_specs=specs,
    )
    steps = [
        {
            "exercise_id": 10,
            "title": "Slot 0 OK",
            "roadmap_major_step_index": 0,
        },
        {
            "exercise_id": 20,
            "title": "Mae Geri falsch",
            "roadmap_major_step_index": 1,
        },
        {
            "exercise_id": 30,
            "title": "Slot 2 OK",
            "roadmap_major_step_index": 2,
        },
    ]

    def _fake_match(cur, *, stage_spec, used, **kwargs):
        assert stage_spec.major_step_index == 1
        assert 20 in used
        assert 10 in used
        assert 30 in used
        return (
            {
                "exercise_id": 21,
                "title": "Sprungkraft Mawashi",
                "roadmap_major_step_index": 1,
            },
            None,
        )

    ordered, log, unfilled = rematch_roadmap_slots(
        None,
        tenant=None,
        body=None,
        goal_query="Mawashi Geri",
        max_steps=3,
        semantic_brief=None,
        path_target_profile=None,
        path_intent="",
        roadmap_ctx=ctx,
        steps=steps,
        slot_indices={1},
        rematch_reasons={1: "technique_scope"},
        match_slot_fn=_fake_match,
    )

    assert len(ordered) == 3
    assert ordered[0]["exercise_id"] == 10
    assert ordered[1]["exercise_id"] == 21
    assert ordered[2]["exercise_id"] == 30
    assert len(log) == 1
    assert log[0]["action"] == "replaced"
    assert log[0]["replaced_exercise_id"] == 20
    assert log[0]["new_exercise_id"] == 21
    assert not unfilled


def test_rematch_excludes_replaced_exercise_from_used():
    specs = _stage_specs()
    ctx = ProgressionRoadmapContext(
        goal_query="Mawashi Geri",
        max_steps=3,
        stage_specs=specs,
    )
    steps = [
        {"exercise_id": 10, "title": "OK", "roadmap_major_step_index": 0},
        {"exercise_id": 99, "title": "Mae Geri", "roadmap_major_step_index": 1},
    ]
    seen_used = []

    def _fake_match(cur, *, used, stage_spec, **kwargs):
        seen_used.append(set(used))
        return (
            {"exercise_id": 42, "title": "Neu", "roadmap_major_step_index": stage_spec.major_step_index},
            None,
        )

    rematch_roadmap_slots(
        None,
        tenant=None,
        body=None,
        goal_query="Mawashi",
        max_steps=3,
        semantic_brief=None,
        path_target_profile=None,
        path_intent="",
        roadmap_ctx=ctx,
        steps=steps,
        slot_indices={1},
        rematch_reasons={1: "technique_scope"},
        match_slot_fn=_fake_match,
    )
    assert 99 in seen_used[0]