Ajoute l’analyse des catégories de pièces

tests/test_part_categories.py

@@ -0,0 +1,126 @@
+"""Tests des agrégats par catégorie de pièce."""
+
+import csv
+from pathlib import Path
+
+from lib.rebrickable.part_categories import (
+    build_category_totals,
+    build_global_totals,
+    enrich_categories_with_sets,
+    group_rows_by_set,
+    load_category_names,
+    load_parts_catalog,
+)
+from lib.rebrickable.stats import read_rows
+
+
+def write_csv(path: Path, headers: list[str], rows: list[list[str]]) -> None:
+    """Écrit un CSV simple pour les besoins de tests."""
+    with path.open("w", newline="") as csv_file:
+        writer = csv.writer(csv_file)
+        writer.writerow(headers)
+        writer.writerows(rows)
+
+
+def test_build_category_totals_and_enrichment(tmp_path: Path) -> None:
+    """Calcule les parts par catégorie et marque les catégories structurelles."""
+    parts_path = tmp_path / "parts_filtered.csv"
+    write_csv(
+        parts_path,
+        [
+            "part_num",
+            "color_rgb",
+            "is_translucent",
+            "set_num",
+            "set_id",
+            "year",
+            "quantity_in_set",
+            "is_spare",
+            "is_minifig_part",
+        ],
+        [
+            ["p1", "aaaaaa", "false", "1000-1", "1000", "2020", "3", "false", "false"],
+            ["p2", "bbbbbb", "false", "1000-1", "1000", "2020", "2", "false", "true"],
+            ["p3", "cccccc", "false", "2000-1", "2000", "2021", "4", "false", "false"],
+        ],
+    )
+    parts_catalog_path = tmp_path / "parts.csv"
+    write_csv(parts_catalog_path, ["part_num", "name", "part_cat_id"], [["p1", "Brick A", "1"], ["p2", "Head", "99"], ["p3", "Slope", "99"]])
+    categories_path = tmp_path / "part_categories.csv"
+    write_csv(categories_path, ["id", "name"], [["1", "Baseplates"], ["99", "Bricks"]])
+    sets_path = tmp_path / "sets_enriched.csv"
+    write_csv(
+        sets_path,
+        ["set_num", "set_id", "name", "year", "in_collection"],
+        [["1000-1", "1000", "Set A", "2020", "true"], ["2000-1", "2000", "Set B", "2021", "false"]],
+    )
+
+    parts_rows = read_rows(parts_path)
+    grouped = group_rows_by_set(parts_rows)
+    categories_by_set_raw, categories_by_year = build_category_totals(
+        grouped,
+        load_parts_catalog(parts_catalog_path),
+        load_category_names(categories_path),
+    )
+    enriched = enrich_categories_with_sets(categories_by_set_raw, {row["set_num"]: row for row in read_rows(sets_path)})
+    global_rows = build_global_totals(enriched)
+
+    assert categories_by_set_raw == [
+        {
+            "set_num": "1000-1",
+            "category_id": "1",
+            "category_name": "Baseplates",
+            "quantity_non_spare": "3",
+            "quantity_minifig": "0",
+            "quantity_non_minifig": "3",
+            "share_non_spare": "0.6000",
+        },
+        {
+            "set_num": "1000-1",
+            "category_id": "99",
+            "category_name": "Bricks",
+            "quantity_non_spare": "2",
+            "quantity_minifig": "2",
+            "quantity_non_minifig": "0",
+            "share_non_spare": "0.4000",
+        },
+        {
+            "set_num": "2000-1",
+            "category_id": "99",
+            "category_name": "Bricks",
+            "quantity_non_spare": "4",
+            "quantity_minifig": "0",
+            "quantity_non_minifig": "4",
+            "share_non_spare": "1.0000",
+        },
+    ]
+    assert categories_by_year == [
+        {
+            "year": "2020",
+            "category_id": "1",
+            "category_name": "Baseplates",
+            "quantity_non_spare": "3",
+            "share_non_spare": "0.6000",
+            "is_structural": "true",
+        },
+        {
+            "year": "2020",
+            "category_id": "99",
+            "category_name": "Bricks",
+            "quantity_non_spare": "2",
+            "share_non_spare": "0.4000",
+            "is_structural": "false",
+        },
+        {
+            "year": "2021",
+            "category_id": "99",
+            "category_name": "Bricks",
+            "quantity_non_spare": "4",
+            "share_non_spare": "1.0000",
+            "is_structural": "false",
+        },
+    ]
+    assert enriched[0]["is_structural"] == "true"
+    assert enriched[1]["is_structural"] == "false"
+    assert global_rows[0]["category_id"] == "99"
+    assert global_rows[1]["category_id"] == "1"

tests/test_part_categories_plot.py

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+"""Tests des graphiques de répartition par catégorie."""
+
+import matplotlib
+from pathlib import Path
+
+from lib.plots.part_categories import (
+    plot_part_categories_heatmap,
+    plot_structural_share_timeline,
+    plot_top_part_categories_area,
+)
+
+
+matplotlib.use("Agg")
+
+
+def test_plot_part_categories_outputs_images(tmp_path: Path) -> None:
+    """Génère les trois visuels principaux."""
+    by_year = tmp_path / "part_categories_by_year.csv"
+    by_global = tmp_path / "part_categories_global.csv"
+    by_year.write_text(
+        "year,category_id,category_name,quantity_non_spare,share_non_spare,is_structural\n"
+        "2020,1,Baseplates,5,0.5,true\n"
+        "2020,2,Bricks,5,0.5,false\n"
+        "2021,1,Baseplates,2,0.25,true\n"
+        "2021,2,Bricks,6,0.75,false\n"
+    )
+    by_global.write_text(
+        "category_id,category_name,quantity_non_spare,share_non_spare,is_structural\n"
+        "2,Bricks,11,0.6875,false\n"
+        "1,Baseplates,7,0.4375,true\n"
+    )
+    area_dest = tmp_path / "figures" / "step29" / "top_part_categories_area.png"
+    heatmap_dest = tmp_path / "figures" / "step29" / "part_categories_heatmap.png"
+    structural_dest = tmp_path / "figures" / "step29" / "structural_share_timeline.png"
+
+    plot_top_part_categories_area(by_year, by_global, area_dest, top_n=2)
+    plot_part_categories_heatmap(by_year, heatmap_dest)
+    plot_structural_share_timeline(by_year, structural_dest)
+
+    assert area_dest.exists()
+    assert heatmap_dest.exists()
+    assert structural_dest.exists()
+    assert area_dest.stat().st_size > 0
+    assert heatmap_dest.stat().st_size > 0
+    assert structural_dest.stat().st_size > 0