from __future__ import annotations
from dataclasses import dataclass
from datetime import datetime, timezone
from typing import Iterator
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,
        }