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test-cleanup: fix 21 failures, prune stale tests, consolidate fragmented files (#66)
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* test-cleanup: fix 21 failures, prune stale tests, consolidate fragmented files * test-cleanup: remove permanently-skipped M4/perf tests, fix pydantic ConfigDict warning * docs: update changelog and release notes for test-cleanup changes * ci: fix editorial governance workflow stale test file reference
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mwisnowski
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34 changed files with 5329 additions and 2202 deletions
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@ -18,7 +18,6 @@ from __future__ import annotations
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import json
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from pathlib import Path
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import pandas as pd
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import pytest
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from deck_builder.combos import detect_combos, detect_synergies
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@ -26,7 +25,6 @@ from tagging.combo_schema import (
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load_and_validate_combos,
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load_and_validate_synergies,
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)
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from tagging.combo_tag_applier import apply_combo_tags
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# ============================================================================
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@ -39,11 +37,6 @@ def _write_json(path: Path, obj: dict):
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path.write_text(json.dumps(obj), encoding="utf-8")
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def _write_csv(dirpath: Path, color: str, rows: list[dict]):
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df = pd.DataFrame(rows)
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df.to_csv(dirpath / f"{color}_cards.csv", index=False)
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# ============================================================================
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# Section 1: Combo Detection Tests
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# ============================================================================
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@ -180,109 +173,4 @@ def test_validate_combos_schema_invalid(tmp_path: Path):
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load_and_validate_combos(str(path))
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# ============================================================================
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# Section 3: Tag Applier Tests
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# ============================================================================
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# Tests for applying combo tags to cards, including bidirectional tagging,
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# name normalization, and split card face matching.
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# Note: These tests are marked as skipped due to M4 architecture changes.
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# ============================================================================
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@pytest.mark.skip(reason="M4: apply_combo_tags no longer accepts colors/csv_dir parameters - uses unified Parquet")
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def test_apply_combo_tags_bidirectional(tmp_path: Path):
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# Arrange: create a minimal CSV for blue with two combo cards
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csv_dir = tmp_path / "csv"
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csv_dir.mkdir(parents=True)
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rows = [
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{"name": "Thassa's Oracle", "themeTags": "[]", "creatureTypes": "[]"},
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{"name": "Demonic Consultation", "themeTags": "[]", "creatureTypes": "[]"},
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{"name": "Zealous Conscripts", "themeTags": "[]", "creatureTypes": "[]"},
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]
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_write_csv(csv_dir, "blue", rows)
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# And a combos.json in a temp location
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combos_dir = tmp_path / "config" / "card_lists"
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combos_dir.mkdir(parents=True)
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combos = {
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"list_version": "0.1.0",
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"generated_at": None,
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"pairs": [
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{"a": "Thassa's Oracle", "b": "Demonic Consultation"},
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{"a": "Kiki-Jiki, Mirror Breaker", "b": "Zealous Conscripts"},
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],
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}
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combos_path = combos_dir / "combos.json"
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combos_path.write_text(json.dumps(combos), encoding="utf-8")
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# Act
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counts = apply_combo_tags(colors=["blue"], combos_path=str(combos_path), csv_dir=str(csv_dir))
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# Assert
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assert counts.get("blue", 0) > 0
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df = pd.read_csv(csv_dir / "blue_cards.csv")
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# Oracle should list Consultation
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row_oracle = df[df["name"] == "Thassa's Oracle"].iloc[0]
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assert "Demonic Consultation" in row_oracle["comboTags"]
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# Consultation should list Oracle
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row_consult = df[df["name"] == "Demonic Consultation"].iloc[0]
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assert "Thassa's Oracle" in row_consult["comboTags"]
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# Zealous Conscripts is present but not its partner in this CSV; we still record the partner name
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row_conscripts = df[df["name"] == "Zealous Conscripts"].iloc[0]
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assert "Kiki-Jiki, Mirror Breaker" in row_conscripts.get("comboTags")
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@pytest.mark.skip(reason="M4: apply_combo_tags no longer accepts colors/csv_dir parameters - uses unified Parquet")
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def test_name_normalization_curly_apostrophes(tmp_path: Path):
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csv_dir = tmp_path / "csv"
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csv_dir.mkdir(parents=True)
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# Use curly apostrophe in CSV name, straight in combos
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rows = [
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{"name": "Thassa's Oracle", "themeTags": "[]", "creatureTypes": "[]"},
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{"name": "Demonic Consultation", "themeTags": "[]", "creatureTypes": "[]"},
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]
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_write_csv(csv_dir, "blue", rows)
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combos_dir = tmp_path / "config" / "card_lists"
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combos_dir.mkdir(parents=True)
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combos = {
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"list_version": "0.1.0",
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"generated_at": None,
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"pairs": [{"a": "Thassa's Oracle", "b": "Demonic Consultation"}],
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}
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combos_path = combos_dir / "combos.json"
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combos_path.write_text(json.dumps(combos), encoding="utf-8")
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counts = apply_combo_tags(colors=["blue"], combos_path=str(combos_path), csv_dir=str(csv_dir))
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assert counts.get("blue", 0) >= 1
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df = pd.read_csv(csv_dir / "blue_cards.csv")
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row = df[df["name"] == "Thassa's Oracle"].iloc[0]
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assert "Demonic Consultation" in row["comboTags"]
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@pytest.mark.skip(reason="M4: apply_combo_tags no longer accepts colors/csv_dir parameters - uses unified Parquet")
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def test_split_card_face_matching(tmp_path: Path):
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csv_dir = tmp_path / "csv"
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csv_dir.mkdir(parents=True)
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# Card stored as split name in CSV
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rows = [
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{"name": "Fire // Ice", "themeTags": "[]", "creatureTypes": "[]"},
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{"name": "Isochron Scepter", "themeTags": "[]", "creatureTypes": "[]"},
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]
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_write_csv(csv_dir, "izzet", rows)
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combos_dir = tmp_path / "config" / "card_lists"
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combos_dir.mkdir(parents=True)
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combos = {
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"list_version": "0.1.0",
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"generated_at": None,
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"pairs": [{"a": "Ice", "b": "Isochron Scepter"}],
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}
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combos_path = combos_dir / "combos.json"
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combos_path.write_text(json.dumps(combos), encoding="utf-8")
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counts = apply_combo_tags(colors=["izzet"], combos_path=str(combos_path), csv_dir=str(csv_dir))
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assert counts.get("izzet", 0) >= 1
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df = pd.read_csv(csv_dir / "izzet_cards.csv")
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row = df[df["name"] == "Fire // Ice"].iloc[0]
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assert "Isochron Scepter" in row["comboTags"]
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