from __future__ import annotations

from collections.abc import Iterator
from dataclasses import dataclass
from datetime import datetime, timezone

import requests

from personal_data.data import DeduplicateMode
from personal_data.fetchers import Scraper
from personal_data.secrets import wanikani_api_key


@dataclass(frozen=True)
class WaniKaniSummaryFetcher(Scraper):
    dataset_name: str = 'wanikani_summary'

    @staticmethod
    def deduplicate_mode() -> DeduplicateMode:
        return DeduplicateMode.BY_ALL_COLUMNS

    def scrape(self) -> Iterator[dict]:
        token = wanikani_api_key()
        headers = {
            'Authorization': f'Bearer {token}',
            'Wanikani-Revision': '20170710',
        }
        url = 'https://api.wanikani.com/v2/summary'
        response = requests.get(url, headers=headers)
        response.raise_for_status()
        data = response.json()

        lessons = data.get('data', {}).get('lessons', [])
        total_lessons = sum(len(lesson.get('subject_ids', [])) for lesson in lessons)

        reviews = data.get('data', {}).get('reviews', [])
        now = datetime.now(timezone.utc)
        total_reviews = 0
        for review in reviews:
            available_at_str = review.get('available_at')
            if available_at_str:
                available_at = datetime.fromisoformat(
                    available_at_str.replace('Z', '+00:00'),
                )
                if available_at <= now:
                    total_reviews += len(review.get('subject_ids', []))

        yield {
            'lessons_available': total_lessons,
            'reviews_available': total_reviews,
        }