import csv
from collections import defaultdict


def load_data(filepath: str) -> list[dict]:
    records = []
    with open(filepath, mode='r', encoding='utf-8') as f:
        reader = csv.reader(f)
        for row in reader:
            if not row: continue
            name, category, price, quantity, date = row
            records.append({
                "name": name.strip(),
                "category": category.strip(),
                "price": float(price),
                "quantity": int(quantity),
                "date": date.strip()
            })
    return records


def clean_data(records: list[dict]) -> list[dict]:
    cleaned = []
    for r in records:
        if r['price'] >= 0 and r['quantity'] >= 0:
            r['category'] = r['category'].lower()
            cleaned.append(r)
    return cleaned


def filter_by_category(records: list[dict], category: str) -> list[dict]:
    return [r for r in records if r['category'] == category.lower()]


def filter_by_price_range(records: list[dict], min_price: float, max_price: float) -> list[dict]:
    return [r for r in records if min_price <= r['price'] <= max_price]


def total_revenue(records: list[dict]) -> float:
    return sum(r['price'] * r['quantity'] for r in records)


def category_revenue(records: list[dict]) -> dict[str, float]:
    rev_map = defaultdict(float)
    for r in records:
        rev_map[r['category']] += r['price'] * r['quantity']
    return dict(rev_map)


def top_n_items(records: list[dict], n: int) -> list[tuple[str, int]]:
    counts = defaultdict(int)
    for r in records:
        counts[r['name']] += r['quantity']
    sorted_items = sorted(counts.items(), key=lambda x: x[1], reverse=True)
    return sorted_items[:n]


def monthly_sales(records: list[dict]) -> dict[str, float]:
    monthly_rev = defaultdict(float)
    for r in records:
        month = r['date'][:7]  # Извлекает YYYY-MM
        monthly_rev[month] += r['price'] * r['quantity']
    return dict(sorted(monthly_rev.items()))


def best_selling_category(records: list[dict]) -> str:
    cat_rev = category_revenue(records)
    if not cat_rev: return ""
    return max(cat_rev, key=cat_rev.get)


def export_summary(records: list[dict], output_path: str) -> None:
    rev = total_revenue(records)
    best_cat = best_selling_category(records)
    top3 = top_n_items(records, 3)
    monthly = monthly_sales(records)

    with open(output_path, 'w', encoding='utf-8') as f:
        f.write("СВОДНЫЙ ОТЧЕТ ПО ПРОДАЖАМ\n")
        f.write("=" * 30 + "\n")
        f.write(f"Общая выручка: {rev:.2f}\n")
        f.write(f"Лучшая категория: {best_cat}\n\n")
        f.write("Топ-3 товара (по количеству):\n")
        for name, qty in top3:
            f.write(f"- {name}: {qty} шт.\n")
        f.write("\nВыручка по месяцам:\n")
        for month, m_rev in monthly.items():
            f.write(f"- {month}: {m_rev:.2f}\n")


def main() -> None:
    data = load_data("data/sales.csv")
    data = clean_data(data)
    filtered = filter_by_price_range(data, 10, 500)
    rev = total_revenue(filtered)
    category_revenue(filtered)
    best_cat = best_selling_category(filtered)
    top3 = top_n_items(filtered, 3)
    monthly = monthly_sales(filtered)
    print(f"--- Результаты анализа (фильтр: 10-500 руб) ---")
    print(f"Общая выручка: {rev:.2f}")
    print(f"Лучшая категория: {best_cat.capitalize()}")
    print(f"Топ-3 товара: {top3}")
    print(f"Выручка по месяцам: {monthly}")
    export_summary(filtered, "report.txt")
    print(f"\nОтчет успешно сохранен в report.txt")
if __name__ == "__main__":
    main()