"""Détection des têtes de minifigs à plusieurs visages et agrégats associés."""

import csv
from pathlib import Path
from typing import Dict, Iterable, List, Sequence

from lib.filesystem import ensure_parent_dir
from lib.rebrickable.stats import read_rows


DUAL_FACE_KEYWORDS = [
    "dual sided",
    "dual-sided",
    "double sided",
    "double-sided",
    "2 sided",
    "2-sided",
    "two sided",
    "two-sided",
    "dual print",
    "dual face",
    "double face",
    "two faces",
    "alt face",
    "alternate face",
]


def load_parts_catalog(path: Path) -> Dict[str, dict]:
    """Indexe les pièces par référence."""
    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_sets(path: Path) -> Dict[str, dict]:
    """Indexe les sets enrichis par set_num."""
    sets: Dict[str, dict] = {}
    for row in read_rows(path):
        sets[row["set_num"]] = row
    return sets


def detect_dual_face(name: str) -> str:
    """Détecte une tête dual-face via des mots-clés."""
    lowered = name.lower()
    for keyword in DUAL_FACE_KEYWORDS:
        if keyword in lowered:
            return "true"
    return "false"


def build_head_faces(
    minifigs_by_set_path: Path,
    parts_catalog_path: Path,
    sets_enriched_path: Path,
) -> List[dict]:
    """Construit la liste des têtes annotées selon la présence de visages multiples."""
    heads = read_rows(minifigs_by_set_path)
    catalog = load_parts_catalog(parts_catalog_path)
    sets_lookup = load_sets(sets_enriched_path)
    annotated: List[dict] = []
    for row in heads:
        part = catalog[row["part_num"]]
        set_row = sets_lookup[row["set_num"]]
        is_dual = detect_dual_face(part["name"])
        annotated.append(
            {
                "set_num": row["set_num"],
                "set_id": set_row["set_id"],
                "year": set_row["year"],
                "name": set_row["name"],
                "in_collection": set_row["in_collection"],
                "part_num": row["part_num"],
                "part_name": part["name"],
                "fig_num": row["fig_num"],
                "known_character": row["known_character"],
                "gender": row["gender"],
                "is_dual_face": is_dual,
            }
        )
    annotated.sort(key=lambda row: (row["set_num"], row["part_num"]))
    return annotated


def aggregate_by_year(rows: Iterable[dict]) -> List[dict]:
    """Agrège les têtes dual-face par année."""
    counts: Dict[str, dict] = {}
    for row in rows:
        year_entry = counts.get(row["year"])
        if year_entry is None:
            year_entry = {
                "year": row["year"],
                "total_heads": 0,
                "dual_heads": 0,
            }
            counts[row["year"]] = year_entry
        year_entry["total_heads"] += 1
        if row["is_dual_face"] == "true":
            year_entry["dual_heads"] += 1
    aggregated: List[dict] = []
    for year, entry in counts.items():
        aggregated.append(
            {
                "year": year,
                "total_heads": str(entry["total_heads"]),
                "dual_heads": str(entry["dual_heads"]),
                "share_dual": f"{entry['dual_heads'] / entry['total_heads']:.4f}",
            }
        )
    aggregated.sort(key=lambda row: int(row["year"]))
    return aggregated


def aggregate_by_set(rows: Iterable[dict]) -> List[dict]:
    """Agrège les têtes dual-face par set."""
    counts: Dict[str, dict] = {}
    for row in rows:
        entry = counts.get(row["set_num"])
        if entry is None:
            entry = {
                "set_num": row["set_num"],
                "set_id": row["set_id"],
                "name": row["name"],
                "year": row["year"],
                "in_collection": row["in_collection"],
                "total_heads": 0,
                "dual_heads": 0,
            }
            counts[row["set_num"]] = entry
        entry["total_heads"] += 1
        if row["is_dual_face"] == "true":
            entry["dual_heads"] += 1
    aggregated: List[dict] = []
    for entry in counts.values():
        aggregated.append(
            {
                "set_num": entry["set_num"],
                "set_id": entry["set_id"],
                "name": entry["name"],
                "year": entry["year"],
                "in_collection": entry["in_collection"],
                "total_heads": str(entry["total_heads"]),
                "dual_heads": str(entry["dual_heads"]),
                "share_dual": f"{entry['dual_heads'] / entry['total_heads']:.4f}",
            }
        )
    aggregated.sort(key=lambda row: (-int(row["dual_heads"]), -float(row["share_dual"]), row["set_num"]))
    return aggregated


def aggregate_by_character(rows: Iterable[dict]) -> List[dict]:
    """Agrège les têtes dual-face par personnage connu."""
    counts: Dict[str, dict] = {}
    for row in rows:
        character = row["known_character"] or "Inconnu"
        entry = counts.get(character)
        if entry is None:
            entry = {
                "known_character": character,
                "gender": row["gender"],
                "total_heads": 0,
                "dual_heads": 0,
            }
            counts[character] = entry
        entry["total_heads"] += 1
        if row["is_dual_face"] == "true":
            entry["dual_heads"] += 1
    aggregated: List[dict] = []
    for character, entry in counts.items():
        aggregated.append(
            {
                "known_character": character,
                "gender": entry["gender"],
                "total_heads": str(entry["total_heads"]),
                "dual_heads": str(entry["dual_heads"]),
                "share_dual": f"{entry['dual_heads'] / entry['total_heads']:.4f}",
            }
        )
    aggregated.sort(key=lambda row: (-int(row["dual_heads"]), row["known_character"]))
    return aggregated


def write_csv(destination_path: Path, rows: Sequence[dict], fieldnames: Sequence[str]) -> None:
    """Écrit un CSV générique."""
    ensure_parent_dir(destination_path)
    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)