Création d'un fichier intermédiaire pour les statistiques sur les couleurs

tests/test_colors_by_set.py

@@ -0,0 +1,101 @@
+"""Tests d'agrégation des couleurs par set."""
+
+import csv
+from pathlib import Path
+
+from lib.rebrickable.colors_by_set import (
+    aggregate_colors_by_set,
+    build_colors_lookup,
+    load_parts,
+    write_colors_by_set,
+)
+
+
+def write_csv(path: Path, headers: list[str], rows: list[list[str]]) -> None:
+    """Écrit un CSV simple pour les besoins des tests."""
+    with path.open("w", newline="") as csv_file:
+        writer = csv.writer(csv_file)
+        writer.writerow(headers)
+        writer.writerows(rows)
+
+
+def test_aggregate_colors_by_set(tmp_path: Path) -> None:
+    """Regroupe les quantités par set et par couleur."""
+    parts_path = tmp_path / "parts_filtered.csv"
+    colors_path = tmp_path / "colors.csv"
+    destination_path = tmp_path / "colors_by_set.csv"
+    write_csv(
+        parts_path,
+        [
+            "part_num",
+            "color_rgb",
+            "is_translucent",
+            "set_num",
+            "set_id",
+            "year",
+            "quantity_in_set",
+            "is_spare",
+            "is_minifig_part",
+        ],
+        [
+            ["3001", "FFFFFF", "false", "1000-1", "1000", "2020", "2", "false", "false"],
+            ["3002", "FFFFFF", "false", "1000-1", "1000", "2020", "1", "true", "false"],
+            ["3003", "000000", "true", "1000-1", "1000", "2020", "4", "false", "true"],
+            ["4001", "FFFFFF", "false", "2000-1", "2000", "2021", "3", "false", "true"],
+        ],
+    )
+    write_csv(
+        colors_path,
+        ["id", "name", "rgb", "is_trans", "num_parts", "num_sets", "y1", "y2"],
+        [
+            ["1", "White", "FFFFFF", "False", "0", "0", "0", "0"],
+            ["2", "Trans-Black", "000000", "True", "0", "0", "0", "0"],
+        ],
+    )
+
+    parts = load_parts(parts_path)
+    colors_lookup = build_colors_lookup(colors_path)
+    aggregated = aggregate_colors_by_set(parts, colors_lookup)
+    write_colors_by_set(destination_path, aggregated)
+
+    with destination_path.open() as csv_file:
+        rows = list(csv.DictReader(csv_file))
+
+    assert rows == [
+        {
+            "set_num": "1000-1",
+            "set_id": "1000",
+            "year": "2020",
+            "color_rgb": "000000",
+            "is_translucent": "true",
+            "color_name": "Trans-Black",
+            "quantity_total": "4",
+            "quantity_non_spare": "4",
+            "quantity_minifig": "4",
+            "quantity_non_minifig": "0",
+        },
+        {
+            "set_num": "1000-1",
+            "set_id": "1000",
+            "year": "2020",
+            "color_rgb": "FFFFFF",
+            "is_translucent": "false",
+            "color_name": "White",
+            "quantity_total": "3",
+            "quantity_non_spare": "2",
+            "quantity_minifig": "0",
+            "quantity_non_minifig": "3",
+        },
+        {
+            "set_num": "2000-1",
+            "set_id": "2000",
+            "year": "2021",
+            "color_rgb": "FFFFFF",
+            "is_translucent": "false",
+            "color_name": "White",
+            "quantity_total": "3",
+            "quantity_non_spare": "3",
+            "quantity_minifig": "3",
+            "quantity_non_minifig": "0",
+        },
+    ]

tests/test_parts_inventory.py

@@ -26,10 +26,10 @@ def test_write_parts_filtered(tmp_path: Path) -> None:
 
     write_csv(
         sets_path,
-        ["set_num", "set_id", "name", "num_parts"],
+        ["set_num", "set_id", "name", "num_parts", "year"],
         [
-            ["1234-1", "1234", "Sample Set A", "9"],
-            ["5678-1", "5678", "Sample Set B", "2"],
+            ["1234-1", "1234", "Sample Set A", "9", "2020"],
+            ["5678-1", "5678", "Sample Set B", "2", "2021"],
         ],
     )
     write_csv(
@@ -98,8 +98,10 @@ def test_write_parts_filtered(tmp_path: Path) -> None:
             "is_translucent": "false",
             "set_num": "1234-1",
             "set_id": "1234",
+            "year": "2020",
             "quantity_in_set": "4",
             "is_spare": "false",
+            "is_minifig_part": "false",
         },
         {
             "part_num": "3002",
@@ -107,8 +109,10 @@ def test_write_parts_filtered(tmp_path: Path) -> None:
             "is_translucent": "true",
             "set_num": "1234-1",
             "set_id": "1234",
+            "year": "2020",
             "quantity_in_set": "1",
             "is_spare": "true",
+            "is_minifig_part": "false",
         },
         {
             "part_num": "mf-1",
@@ -116,8 +120,10 @@ def test_write_parts_filtered(tmp_path: Path) -> None:
             "is_translucent": "true",
             "set_num": "1234-1",
             "set_id": "1234",
+            "year": "2020",
             "quantity_in_set": "1",
             "is_spare": "false",
+            "is_minifig_part": "true",
         },
         {
             "part_num": "mf-2",
@@ -125,8 +131,10 @@ def test_write_parts_filtered(tmp_path: Path) -> None:
             "is_translucent": "false",
             "set_num": "1234-1",
             "set_id": "1234",
+            "year": "2020",
             "quantity_in_set": "2",
             "is_spare": "false",
+            "is_minifig_part": "true",
         },
         {
             "part_num": "3003",
@@ -134,7 +142,9 @@ def test_write_parts_filtered(tmp_path: Path) -> None:
             "is_translucent": "false",
             "set_num": "5678-1",
             "set_id": "5678",
+            "year": "2021",
             "quantity_in_set": "2",
             "is_spare": "false",
+            "is_minifig_part": "false",
         },
     ]