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Ajoute l’étape 25 de répartition des minifigs par genre
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@@ -34,6 +34,28 @@ def aggregate_by_character(rows: Iterable[dict]) -> List[dict]:
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return aggregates
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def aggregate_by_gender(rows: Iterable[dict]) -> List[dict]:
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"""Compte les minifigs distinctes par genre (fig_num unique)."""
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genders_by_fig: Dict[str, str] = {}
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counts: Dict[str, int] = defaultdict(int)
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for row in rows:
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fig_num = row["fig_num"].strip()
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gender = row.get("gender", "").strip().lower()
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normalized = gender if gender in ("male", "female") else "unknown"
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if fig_num == "":
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continue
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if fig_num in genders_by_fig:
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continue
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genders_by_fig[fig_num] = normalized
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counts[normalized] += 1
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aggregates: List[dict] = []
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ordered = ["female", "male", "unknown"]
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for gender in ordered:
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if gender in counts:
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aggregates.append({"gender": gender, "minifig_count": str(counts[gender])})
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return aggregates
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def write_character_counts(path: Path, rows: Sequence[dict]) -> None:
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"""Écrit le CSV des comptes par personnage."""
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ensure_parent_dir(path)
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@@ -45,6 +67,17 @@ def write_character_counts(path: Path, rows: Sequence[dict]) -> None:
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writer.writerow(row)
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def write_gender_counts(path: Path, rows: Sequence[dict]) -> None:
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"""Écrit le CSV des comptes par genre."""
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ensure_parent_dir(path)
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fieldnames = ["gender", "minifig_count"]
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with path.open("w", newline="") as csv_file:
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writer = csv.DictWriter(csv_file, fieldnames=fieldnames)
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writer.writeheader()
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for row in rows:
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writer.writerow(row)
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def load_sets_enriched(path: Path) -> Dict[str, str]:
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"""Indexe les années par set_num."""
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lookup: Dict[str, str] = {}
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