108 lines
3.7 KiB
Python
108 lines
3.7 KiB
Python
import dataclasses
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import datetime
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import logging
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from collections.abc import Iterator, Mapping
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import requests_util
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from personal_data.data import DeduplicateMode, Scraper
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from .. import secrets
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logger = logging.getLogger(__name__)
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URL_API_ROOT = 'https://api.wanikani.com/v2'
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URL_ASSIGNMENTS = URL_API_ROOT + '/assignments'
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URL_SUMMARY = URL_API_ROOT + '/summary'
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URL_SUBJECTS = URL_API_ROOT + '/subjects/{subject_id}'
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def _setup_cache(session):
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requests_util.setup_limiter(
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session,
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URL_API_ROOT,
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expire_after=datetime.timedelta(days=90),
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per_minute=30,
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)
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requests_util.setup_limiter(
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session,
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URL_ASSIGNMENTS,
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expire_after=datetime.timedelta(days=3),
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per_minute=30,
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)
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@dataclasses.dataclass(frozen=True)
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class WaniKaniLessonsFetcher(Scraper):
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dataset_name = 'wanikani_lessons'
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deduplicate_mode = DeduplicateMode.BY_ALL_COLUMNS
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def scrape(self) -> Iterator[Mapping[str, object]]:
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"""Fetch assignments from the WaniKani API and yield a dict for each assignment with a non-null unlocked_at timestamp."""
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_setup_cache(self.session)
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headers = {
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'Authorization': f'Bearer {secrets.wanikani_api_key()}',
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'Wanikani-Revision': '20170710',
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}
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url = URL_ASSIGNMENTS
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while url:
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logger.warning('Getting: %s', url)
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response = self.session.get(url, headers=headers)
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response.raise_for_status()
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json_resp = response.json()
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for assignment in json_resp.get('data', []):
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data_item = assignment['data']
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subject_id = data_item.get('subject_id')
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if subject_id:
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subj_url = URL_SUBJECTS.format(subject_id=subject_id)
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logger.warning('Getting: %s', subj_url)
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subj_response = self.session.get(subj_url, headers=headers)
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subj_response.raise_for_status()
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subj_json = subj_response.json()
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subject_characters = subj_json.get('data', {}).get('characters')
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data_item['subject_characters'] = subject_characters
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yield data_item
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url = json_resp.get('pages', {}).get('next_url')
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@dataclasses.dataclass(frozen=True)
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class WaniKaniSummaryFetcher(Scraper):
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dataset_name: str = 'wanikani_summary'
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deduplicate_mode = DeduplicateMode.BY_ALL_COLUMNS
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@staticmethod
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def deduplicate_mode() -> DeduplicateMode:
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return DeduplicateMode.BY_ALL_COLUMNS
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def scrape(self) -> Iterator[dict]:
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_setup_cache(self.session)
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headers = {
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'Authorization': f'Bearer {secrets.wanikani_api_key()}',
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'Wanikani-Revision': '20170710',
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}
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response = self.session.get(URL_SUMMARY, headers=headers)
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response.raise_for_status()
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data = response.json()
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lessons = data.get('data', {}).get('lessons', [])
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total_lessons = sum(len(lesson.get('subject_ids', [])) for lesson in lessons)
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reviews = data.get('data', {}).get('reviews', [])
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now = datetime.datetime.now(datetime.timezone.utc)
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total_reviews = 0
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for review in reviews:
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available_at_str = review.get('available_at')
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if available_at_str:
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available_at = datetime.datetime.fromisoformat(
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available_at_str.replace('Z', '+00:00'),
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)
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if available_at <= now:
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total_reviews += len(review.get('subject_ids', []))
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del review
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yield {
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'time': now,
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'lessons_available': total_lessons,
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'reviews_available': total_reviews,
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}
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