Exclure les pièces de minifigs et intégrer les visuels de rareté

lib/plots/part_rarity.py

@@ -0,0 +1,86 @@
+"""Visualisation des pièces les plus rares observées dans les sets filtrés."""
+
+import csv
+from pathlib import Path
+from typing import List
+
+import matplotlib.pyplot as plt
+from matplotlib.offsetbox import AnnotationBbox, OffsetImage
+from PIL import Image
+
+from lib.filesystem import ensure_parent_dir
+
+
+def load_part_rarity(path: Path) -> List[dict]:
+    """Charge le CSV des pièces rares."""
+    rows: List[dict] = []
+    with path.open() as csv_file:
+        reader = csv.DictReader(csv_file)
+        for row in reader:
+            rows.append(row)
+    return rows
+
+
+def format_label(row: dict) -> str:
+    """Formate l’étiquette de l’axe vertical."""
+    return f"{row['part_num']} — {row['part_name']}"
+
+
+def load_part_image(row: dict, resources_dir: Path) -> Image.Image | None:
+    """Charge l'image associée à une pièce si elle est disponible."""
+    path = resources_dir / row["sample_set_id"] / "rare_parts" / f"{row['part_num']}.jpg"
+    if not path.exists():
+        return None
+    return Image.open(path)
+
+
+def plot_part_rarity(
+    path: Path,
+    destination_path: Path,
+    resources_dir: Path = Path("figures/rebrickable"),
+    show_images: bool = True,
+) -> None:
+    """Trace un bar chart horizontal des pièces les plus rares avec leurs visuels."""
+    rows = load_part_rarity(path)
+    selected = rows
+    labels = [format_label(row) for row in selected]
+    filtered_counts = [int(row["filtered_quantity"]) for row in selected]
+    other_counts = [int(row["other_sets_quantity"]) for row in selected]
+    positions = list(range(len(selected)))
+
+    fig, ax = plt.subplots(figsize=(13, 0.55 * len(selected) + 1.4))
+    ax.barh(positions, filtered_counts, color="#1f78b4", label="Sets filtrés")
+    ax.barh(positions, other_counts, left=filtered_counts, color="#b2df8a", label="Autres sets")
+    ax.set_yticks(positions)
+    ax.set_yticklabels(labels)
+    ax.set_xlabel("Occurrences de la pièce (rechanges incluses)")
+    ax.grid(axis="x", linestyle="--", alpha=0.4)
+    ax.legend()
+
+    if show_images:
+        max_count = max((f + o) for f, o in zip(filtered_counts, other_counts)) if selected else 0
+        pad = max_count * 0.15 if max_count > 0 else 1.0
+        ax.set_xlim(left=-pad, right=max_count + pad * 0.3)
+        for row, pos in zip(selected, positions):
+            image = load_part_image(row, resources_dir)
+            if image is None:
+                continue
+            target_height = 28
+            ratio = target_height / image.height
+            resized = image.resize((int(image.width * ratio), target_height))
+            imagebox = OffsetImage(resized)
+            ab = AnnotationBbox(
+                imagebox,
+                (-pad * 0.45, pos),
+                xycoords=("data", "data"),
+                box_alignment=(0.5, 0.5),
+                frameon=False,
+            )
+            ax.add_artist(ab)
+
+    fig.subplots_adjust(left=0.42)
+    fig.tight_layout()
+
+    ensure_parent_dir(destination_path)
+    fig.savefig(destination_path, dpi=150)
+    plt.close(fig)

lib/rebrickable/part_rarity.py

@@ -0,0 +1,176 @@
+"""Mesure la rareté des pièces présentes dans les sets filtrés."""
+
+import csv
+from pathlib import Path
+from typing import Dict, Iterable, List, Sequence, Set
+
+from lib.filesystem import ensure_parent_dir
+from lib.rebrickable.parts_inventory import index_inventory_parts_by_inventory, select_latest_inventories
+from lib.rebrickable.stats import read_rows
+
+
+IGNORED_PART_CATEGORY_IDS = {"28", "58", "74", "75"}
+MINIFIG_PART_CATEGORY_IDS = {"13", "27", "59", "60", "61", "65", "70", "71", "72", "73"}
+
+
+def load_parts_catalog(path: Path) -> Dict[str, dict]:
+    """Indexe les pièces par référence avec leur catégorie et leur nom."""
+    catalog: Dict[str, dict] = {}
+    with path.open() as csv_file:
+        reader = csv.DictReader(csv_file)
+        for row in reader:
+            catalog[row["part_num"]] = row
+    return catalog
+
+
+def load_part_categories(path: Path) -> Dict[str, str]:
+    """Associe les identifiants de catégorie à leur libellé."""
+    categories: Dict[str, str] = {}
+    with path.open() as csv_file:
+        reader = csv.DictReader(csv_file)
+        for row in reader:
+            categories[row["id"]] = row["name"]
+    return categories
+
+
+def load_filtered_sets(path: Path) -> Dict[str, dict]:
+    """Charge les sets filtrés avec leurs métadonnées."""
+    lookup: Dict[str, dict] = {}
+    for row in read_rows(path):
+        lookup[row["set_num"]] = row
+    return lookup
+
+
+def aggregate_filtered_parts(
+    rows: Iterable[dict],
+    parts_catalog: Dict[str, dict],
+    ignored_categories: Set[str] = IGNORED_PART_CATEGORY_IDS,
+    ignored_minifig_categories: Set[str] = MINIFIG_PART_CATEGORY_IDS,
+) -> Dict[str, dict]:
+    """Agrège les quantités par pièce pour les sets filtrés (rechanges incluses)."""
+    aggregated: Dict[str, dict] = {}
+    for row in rows:
+        if row["is_minifig_part"] == "true":
+            continue
+        part = parts_catalog[row["part_num"]]
+        if part["part_cat_id"] in ignored_categories:
+            continue
+        if part["part_cat_id"] in ignored_minifig_categories:
+            continue
+        entry = aggregated.get(row["part_num"])
+        if entry is None:
+            entry = {"quantity": 0, "set_numbers": set()}
+            aggregated[row["part_num"]] = entry
+        entry["quantity"] += int(row["quantity_in_set"])
+        entry["set_numbers"].add(row["set_num"])
+    return aggregated
+
+
+def compute_other_set_usage(
+    inventories_path: Path,
+    inventory_parts_path: Path,
+    parts_catalog: Dict[str, dict],
+    filtered_set_numbers: Set[str],
+    ignored_categories: Set[str] = IGNORED_PART_CATEGORY_IDS,
+    ignored_minifig_categories: Set[str] = MINIFIG_PART_CATEGORY_IDS,
+) -> Dict[str, int]:
+    """Compte les occurrences des pièces dans le reste du catalogue (rechanges incluses)."""
+    inventories = select_latest_inventories(inventories_path)
+    parts_by_inventory = index_inventory_parts_by_inventory(inventory_parts_path)
+    totals: Dict[str, int] = {}
+    for set_num, inventory in inventories.items():
+        if set_num in filtered_set_numbers:
+            continue
+        for row in parts_by_inventory.get(inventory["id"], []):
+            part = parts_catalog[row["part_num"]]
+            if part["part_cat_id"] in ignored_categories:
+                continue
+            if part["part_cat_id"] in ignored_minifig_categories:
+                continue
+            totals[row["part_num"]] = totals.get(row["part_num"], 0) + int(row["quantity"])
+    return totals
+
+
+def build_part_rarity(
+    parts_filtered_path: Path,
+    inventories_path: Path,
+    inventory_parts_path: Path,
+    parts_catalog_path: Path,
+    part_categories_path: Path,
+    filtered_sets_path: Path,
+) -> List[dict]:
+    """Construit le classement de rareté des pièces filtrées."""
+    parts_catalog = load_parts_catalog(parts_catalog_path)
+    categories = load_part_categories(part_categories_path)
+    filtered_sets = load_filtered_sets(filtered_sets_path)
+    filtered_set_numbers = set(filtered_sets.keys())
+    filtered_rows = read_rows(parts_filtered_path)
+    filtered_usage = aggregate_filtered_parts(filtered_rows, parts_catalog)
+    other_usage = compute_other_set_usage(
+        inventories_path,
+        inventory_parts_path,
+        parts_catalog,
+        filtered_set_numbers,
+    )
+    rows: List[dict] = []
+    for part_num, entry in filtered_usage.items():
+        part = parts_catalog[part_num]
+        other_quantity = other_usage.get(part_num, 0)
+        total_quantity = entry["quantity"] + other_quantity
+        sample_set_num = sorted(entry["set_numbers"])[0]
+        sample_set_id = filtered_sets[sample_set_num]["set_id"]
+        rows.append(
+            {
+                "part_num": part_num,
+                "part_name": part["name"],
+                "part_cat_id": part["part_cat_id"],
+                "part_category": categories[part["part_cat_id"]],
+                "sample_set_num": sample_set_num,
+                "sample_set_id": sample_set_id,
+                "filtered_quantity": str(entry["quantity"]),
+                "filtered_set_count": str(len(entry["set_numbers"])),
+                "other_sets_quantity": str(other_quantity),
+                "catalog_total_quantity": str(total_quantity),
+                "filtered_share": f"{entry['quantity'] / total_quantity:.4f}",
+            }
+        )
+    rows.sort(key=lambda row: (int(row["other_sets_quantity"]), int(row["catalog_total_quantity"]), row["part_num"]))
+    return rows
+
+
+def write_part_rarity(destination_path: Path, rows: Sequence[dict]) -> None:
+    """Écrit le CSV complet des pièces classées par rareté."""
+    ensure_parent_dir(destination_path)
+    fieldnames = [
+        "part_num",
+        "part_name",
+        "part_cat_id",
+        "part_category",
+        "sample_set_num",
+        "sample_set_id",
+        "filtered_quantity",
+        "filtered_set_count",
+        "other_sets_quantity",
+        "catalog_total_quantity",
+        "filtered_share",
+    ]
+    with destination_path.open("w", newline="") as csv_file:
+        writer = csv.DictWriter(csv_file, fieldnames=fieldnames)
+        writer.writeheader()
+        for row in rows:
+            writer.writerow(row)
+
+
+def select_until_reused(rows: Sequence[dict]) -> List[dict]:
+    """Retient les pièces exclusives puis la première réutilisée dans d’autres sets."""
+    selected: List[dict] = []
+    for row in rows:
+        selected.append(row)
+        if int(row["other_sets_quantity"]) > 0:
+            break
+    return selected
+
+
+def load_part_rarity(path: Path) -> List[dict]:
+    """Charge le CSV de rareté des pièces."""
+    return read_rows(path)