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- Introduced `filter_rematch_slot_indices` to exclude preserved slots from rematching, improving the accuracy of slot assignments. - Added `_slot_priority_for_rematch` to prioritize existing slot assignments during rematching, enhancing the robustness of the rematch process. - Updated `_run_roadmap_rematch_loop` to utilize the new filtering and prioritization logic, ensuring better handling of rematch scenarios. - Enhanced tests in `test_planning_path_rematch.py` to validate the new filtering behavior and ensure correct exercise restoration when not rejected. - Bumped version to reflect the new features and improvements.
339 lines
9.6 KiB
Python
339 lines
9.6 KiB
Python
"""Tests Auto-Rematch nach Pfad-QS (Phase A)."""
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from planning_path_rematch import collect_rematch_slot_indices, rematch_roadmap_slots
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from planning_progression_roadmap import ProgressionRoadmapContext, StageSpecArtifact
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def _stage_specs():
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return [
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StageSpecArtifact(major_step_index=0, learning_goal="Grundlage"),
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StageSpecArtifact(major_step_index=1, learning_goal="Vertiefung"),
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StageSpecArtifact(major_step_index=2, learning_goal="Anwendung"),
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]
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def test_collect_rematch_slot_indices_from_stripped_with_major_index():
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specs = _stage_specs()
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stripped = [
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{
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"step_index": 1,
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"roadmap_major_step_index": 1,
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"issue": "technique_scope",
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"reasons": ["Passt nicht zur Haupttechnik"],
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}
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]
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indices, reasons = collect_rematch_slot_indices(
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stripped_off_topic=stripped,
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off_topic_steps=[],
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optimization_hints=[],
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stage_specs=specs,
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)
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assert indices == {1}
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assert "Haupttechnik" in reasons[1]
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def test_collect_rematch_slot_indices_resolves_step_index_to_major():
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specs = _stage_specs()
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off_topic = [
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{
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"step_index": 2,
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"issue": "stage_mismatch",
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"reasons": ["Ziel passt nicht"],
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}
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]
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indices, reasons = collect_rematch_slot_indices(
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stripped_off_topic=[],
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off_topic_steps=off_topic,
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optimization_hints=[],
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stage_specs=specs,
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)
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assert indices == {2}
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assert reasons[2] == "Ziel passt nicht"
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def test_collect_rematch_slot_indices_from_optimization_hints():
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specs = _stage_specs()
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hints = [
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{
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"action": "rematch_slot",
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"roadmap_major_step_index": 0,
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"reason": "QS-Tier-1",
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}
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]
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indices, _ = collect_rematch_slot_indices(
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stripped_off_topic=[],
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off_topic_steps=[],
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optimization_hints=hints,
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stage_specs=specs,
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)
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assert indices == {0}
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def test_collect_rematch_slot_indices_from_roadmap_unfilled():
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specs = _stage_specs()
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indices, reasons = collect_rematch_slot_indices(
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stripped_off_topic=[],
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off_topic_steps=[],
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optimization_hints=[],
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stage_specs=specs,
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roadmap_unfilled=[(1, specs[1])],
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)
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assert indices == {1}
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assert "Roadmap-Stufe" in reasons[1]
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def test_rematch_roadmap_slots_replaces_only_target_slot():
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specs = _stage_specs()
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ctx = ProgressionRoadmapContext(
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goal_query="Mawashi Geri",
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max_steps=3,
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stage_specs=specs,
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)
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steps = [
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{
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"exercise_id": 10,
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"title": "Slot 0 OK",
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"roadmap_major_step_index": 0,
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},
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{
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"exercise_id": 20,
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"title": "Mae Geri falsch",
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"roadmap_major_step_index": 1,
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},
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{
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"exercise_id": 30,
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"title": "Slot 2 OK",
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"roadmap_major_step_index": 2,
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},
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]
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def _fake_match(cur, *, stage_spec, used, **kwargs):
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assert stage_spec.major_step_index == 1
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assert 20 in used
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assert 10 in used
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assert 30 in used
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return (
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{
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"exercise_id": 21,
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"title": "Sprungkraft Mawashi",
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"roadmap_major_step_index": 1,
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},
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None,
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)
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ordered, log, unfilled = rematch_roadmap_slots(
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None,
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tenant=None,
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body=None,
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goal_query="Mawashi Geri",
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max_steps=3,
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semantic_brief=None,
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path_target_profile=None,
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path_intent="",
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roadmap_ctx=ctx,
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steps=steps,
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slot_indices={1},
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rematch_reasons={1: "technique_scope"},
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match_slot_fn=_fake_match,
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)
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assert len(ordered) == 3
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assert ordered[0]["exercise_id"] == 10
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assert ordered[1]["exercise_id"] == 21
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assert ordered[2]["exercise_id"] == 30
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assert len(log) == 1
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assert log[0]["action"] == "replaced"
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assert log[0]["replaced_exercise_id"] == 20
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assert log[0]["new_exercise_id"] == 21
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assert not unfilled
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def test_rematch_excludes_replaced_exercise_from_used():
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specs = _stage_specs()
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ctx = ProgressionRoadmapContext(
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goal_query="Mawashi Geri",
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max_steps=3,
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stage_specs=specs,
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)
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steps = [
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{"exercise_id": 10, "title": "OK", "roadmap_major_step_index": 0},
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{"exercise_id": 99, "title": "Mae Geri", "roadmap_major_step_index": 1},
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]
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seen_used = []
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def _fake_match(cur, *, used, stage_spec, **kwargs):
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seen_used.append(set(used))
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return (
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{"exercise_id": 42, "title": "Neu", "roadmap_major_step_index": stage_spec.major_step_index},
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None,
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)
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rematch_roadmap_slots(
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None,
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tenant=None,
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body=None,
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goal_query="Mawashi",
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max_steps=3,
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semantic_brief=None,
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path_target_profile=None,
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path_intent="",
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roadmap_ctx=ctx,
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steps=steps,
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slot_indices={1},
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rematch_reasons={1: "technique_scope"},
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match_slot_fn=_fake_match,
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)
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assert 99 in seen_used[0]
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def test_rematch_unfilled_leaves_placeholder_step():
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specs = _stage_specs()
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ctx = ProgressionRoadmapContext(
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goal_query="Mae Geri",
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max_steps=3,
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stage_specs=specs,
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)
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steps = [
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{"exercise_id": 10, "title": "OK", "roadmap_major_step_index": 0},
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{"exercise_id": 99, "title": "Falsch", "roadmap_major_step_index": 1},
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]
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def _no_match(cur, *, stage_spec, **kwargs):
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return None, stage_spec
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ordered, log, unfilled = rematch_roadmap_slots(
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None,
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tenant=None,
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body=None,
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goal_query="Mae Geri",
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max_steps=3,
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semantic_brief=None,
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path_target_profile=None,
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path_intent="",
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roadmap_ctx=ctx,
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steps=steps,
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slot_indices={1},
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rematch_reasons={1: "stage_mismatch"},
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match_slot_fn=_no_match,
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rejected_by_major={1: {99}},
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)
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assert len(ordered) == 2
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slot1 = ordered[1]
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assert slot1["exercise_id"] is None
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assert slot1["slot_status"] == "unfilled"
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assert slot1["roadmap_match_source"] == "unfilled"
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assert log[0]["action"] == "rematch_unfilled"
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assert len(unfilled) == 1
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def test_prune_filled_from_roadmap_unfilled():
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from planning_exercise_path_builder import _prune_filled_from_roadmap_unfilled
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spec = StageSpecArtifact(major_step_index=5, learning_goal="Zielgenauigkeit")
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steps = [{"exercise_id": 99, "roadmap_major_step_index": 5}]
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kept = _prune_filled_from_roadmap_unfilled(steps, [(4, spec)])
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assert kept == []
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unfilled_steps = [{"exercise_id": None, "roadmap_major_step_index": 5}]
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kept2 = _prune_filled_from_roadmap_unfilled(unfilled_steps, [(4, spec)])
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assert len(kept2) == 1
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def test_rematch_keeps_same_exercise_when_not_rejected():
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"""Regression: slot_assignment_history blockierte gültige Wiederzuordnung → leere Slots."""
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specs = _stage_specs()
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ctx = ProgressionRoadmapContext(
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goal_query="Mae Geri",
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max_steps=3,
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stage_specs=specs,
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)
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steps = [
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{"exercise_id": 10, "title": "OK", "roadmap_major_step_index": 0},
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{"exercise_id": 42, "title": "Gut", "roadmap_major_step_index": 1},
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]
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def _same_match(cur, *, stage_spec, slot_priority_exercise_id=None, **kwargs):
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assert slot_priority_exercise_id == 42
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return (
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{"exercise_id": 42, "title": "Gut", "roadmap_major_step_index": stage_spec.major_step_index},
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None,
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)
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ordered, log, unfilled = rematch_roadmap_slots(
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None,
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tenant=None,
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body=None,
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goal_query="Mae Geri",
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max_steps=3,
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semantic_brief=None,
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path_target_profile=None,
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path_intent="",
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roadmap_ctx=ctx,
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steps=steps,
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slot_indices={1},
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rematch_reasons={1: "refine_stage_spec"},
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match_slot_fn=_same_match,
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rejected_by_major={},
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)
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assert ordered[1]["exercise_id"] == 42
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assert log[0]["action"] == "replaced"
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assert not unfilled
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def test_rematch_restores_when_match_fails_and_not_rejected():
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specs = _stage_specs()
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ctx = ProgressionRoadmapContext(
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goal_query="Mae Geri",
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max_steps=3,
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stage_specs=specs,
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)
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steps = [
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{"exercise_id": 10, "title": "OK", "roadmap_major_step_index": 0},
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{"exercise_id": 42, "title": "Gut", "roadmap_major_step_index": 1},
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]
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def _no_match(cur, *, stage_spec, **kwargs):
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return None, stage_spec
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ordered, log, unfilled = rematch_roadmap_slots(
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None,
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tenant=None,
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body=None,
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goal_query="Mae Geri",
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max_steps=3,
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semantic_brief=None,
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path_target_profile=None,
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path_intent="",
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roadmap_ctx=ctx,
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steps=steps,
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slot_indices={1},
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rematch_reasons={1: "refine_stage_spec"},
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match_slot_fn=_no_match,
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rejected_by_major={},
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)
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assert ordered[1]["exercise_id"] == 42
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assert log[0]["action"] == "restored"
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assert not unfilled
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def test_filter_rematch_skips_preserved_slots():
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from planning_path_rematch import filter_rematch_slot_indices
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steps = [
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{
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"exercise_id": 10,
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"roadmap_major_step_index": 0,
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"roadmap_match_source": "slot_best_match",
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"slot_status": "preserved",
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},
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{"exercise_id": 20, "roadmap_major_step_index": 1},
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]
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filtered = filter_rematch_slot_indices(
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steps,
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{0, 1},
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stripped_off_topic=[],
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off_topic_steps=[],
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)
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assert filtered == {1}
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