from __future__ import annotations

import re

from app.domain import Category


CATEGORY_META: dict[Category, tuple[str, str]] = {
    Category.PRODUCTS: ("🛒", "Продукты"),
    Category.ENTERTAINMENT: ("🎉", "Развлечения"),
    Category.CAR: ("🚗", "Машина"),
    Category.CREDITS: ("🏦", "Кредиты"),
    Category.RENOVATION: ("🛠", "Ремонт"),
    Category.OTHER: ("📦", "Другое"),
    Category.INCOME: ("💚", "Доход"),
}

# Сначала проверяются более специфичные слова. Список легко расширять без миграции БД.
CATEGORY_KEYWORDS: dict[Category, tuple[str, ...]] = {
    Category.PRODUCTS: (
        "ярче", "мария ра", "пятерочка", "пятёрочка", "магнит", "лента",
        "ашан", "metro", "продукт", "еда", "молоко", "хлеб", "мясо",
        "овощ", "фрукт", "кофе", "кафе", "ресторан", "доставка еды",
        "алкоголь", "пиво", "вино", "супермаркет",
    ),
    Category.ENTERTAINMENT: (
        "кино", "театр", "концерт", "бар", "клуб", "игра", "steam",
        "подписка", "музей", "развлеч", "боулинг", "караоке", "хобби",
    ),
    Category.CAR: (
        "бензин", "топливо", "азс", "газпромнефть", "лукойл", "g-drive",
        "шиномонтаж", "автосервис", "мойка", "запчаст", "масло", "осаго",
        "парковка", "штраф гибдд", "машин", "авто",
    ),
    Category.CREDITS: (
        "кредит", "ипотек", "долг", "рассроч", "процент банку", "заём", "займ",
    ),
    Category.RENOVATION: (
        "ремонт квартир", "стройматериал", "обои", "краска", "ламинат",
        "сантехник", "электрик", "мебель", "инструмент", "стройка", "леруа", "ремонт",
    ),
}


def normalize(text: str) -> str:
    text = text.casefold().replace("ё", "е")
    return re.sub(r"[^a-zа-я0-9]+", " ", text).strip()


def classify(description: str) -> Category:
    normalized_text = normalize(description)
    normalized = f" {normalized_text} "
    words = normalized_text.split()
    for category, keywords in CATEGORY_KEYWORDS.items():
        for keyword in keywords:
            normalized_keyword = normalize(keyword)
            is_phrase = " " in normalized_keyword
            exact_phrase = is_phrase and f" {normalized_keyword} " in normalized
            word_match = not is_phrase and any(
                word == normalized_keyword
                or (len(normalized_keyword) >= 4 and word.startswith(normalized_keyword))
                for word in words
            )
            if exact_phrase or word_match:
                return category
    return Category.OTHER


def category_label(category: Category) -> str:
    icon, name = CATEGORY_META[category]
    return f"{icon} {name}"


EXPENSE_CATEGORIES = tuple(category for category in Category if category is not Category.INCOME)


# system_key, icon, visible name, keywords. These are seeded for every family budget.
DEFAULT_SUBCATEGORIES: dict[Category, tuple[tuple[str, str, str, tuple[str, ...]], ...]] = {
    Category.PRODUCTS: (
        ("products_food", "🥦", "Еда", ("продукт", "еда", "ярче", "магнит", "пятер", "лента", "молоко", "хлеб", "мясо", "овощ", "фрукт")),
        ("products_alcohol", "🍷", "Алкоголь", ("алкоголь", "пиво", "вино", "водка")),
        ("products_cafe", "☕", "Кафе и рестораны", ("кафе", "ресторан", "кофе", "доставка еды")),
        ("products_household", "🧻", "Бытовые товары", ("бытовая химия", "хозтовар", "порошок", "салфетк")),
    ),
    Category.ENTERTAINMENT: (
        ("entertainment_cinema", "🎬", "Кино и театр", ("кино", "театр", "концерт", "музей")),
        ("entertainment_games", "🎮", "Игры", ("игра", "steam", "playstation", "xbox")),
        ("entertainment_subscriptions", "📺", "Подписки", ("подписка", "кинопоиск", "ivi", "netflix")),
        ("entertainment_hobby", "🎨", "Хобби", ("хобби", "боулинг", "караоке")),
    ),
    Category.CAR: (
        ("car_fuel", "⛽", "Бензин", ("бензин", "топливо", "азс", "газпромнефть", "лукойл", "g drive")),
        ("car_repair", "🔧", "Ремонт", ("автосервис", "ремонт машины", "ремонт авто", "шиномонтаж")),
        ("car_parts", "⚙️", "Запчасти", ("запчаст", "масло", "аккумулятор", "шина", "резина")),
        ("car_service", "🅿️", "Мойка и парковка", ("мойка", "парковка")),
        ("car_insurance", "🛡", "Страховка", ("осаго", "каско", "страховка авто")),
    ),
    Category.CREDITS: (
        ("credits_mortgage", "🏠", "Ипотека", ("ипотек",)),
        ("credits_bank", "💳", "Кредиты", ("кредит", "процент банку")),
        ("credits_installment", "📆", "Рассрочки", ("рассроч",)),
    ),
    Category.RENOVATION: (
        ("renovation_materials", "🧱", "Материалы", ("стройматериал", "обои", "краска", "ламинат", "леруа")),
        ("renovation_furniture", "🪑", "Мебель", ("мебель", "диван", "шкаф", "стол")),
        ("renovation_work", "👷", "Работы", ("сантехник", "электрик", "ремонт квартир", "стройка")),
        ("renovation_tools", "🧰", "Инструменты", ("инструмент", "дрель", "шуруповерт")),
    ),
    Category.OTHER: (),
}


def suggest_subcategory(category: Category, description: str) -> str | None:
    normalized_text = normalize(description)
    words = normalized_text.split()
    padded = f" {normalized_text} "
    for system_key, _icon, _name, keywords in DEFAULT_SUBCATEGORIES.get(category, ()):
        for keyword in keywords:
            normalized_keyword = normalize(keyword)
            if " " in normalized_keyword:
                if f" {normalized_keyword} " in padded:
                    return system_key
            elif any(
                word == normalized_keyword
                or (len(normalized_keyword) >= 4 and word.startswith(normalized_keyword))
                for word in words
            ):
                return system_key
    return None