Files
MoviePilot/app/modules/douban/apiv2.py

539 lines
20 KiB
Python

# -*- coding: utf-8 -*-
import base64
import hashlib
import hmac
from datetime import datetime
from random import choice
from urllib import parse
import requests
from cachetools import TTLCache, cached
from app.core.config import settings
from app.utils.http import RequestUtils
from app.utils.singleton import Singleton
class DoubanApi(metaclass=Singleton):
_urls = {
# 搜索类
# sort=U:近期热门 T:标记最多 S:评分最高 R:最新上映
# q=search_word&start: int = 0&count: int = 20&sort=U
# 聚合搜索
"search": "/search/weixin",
"search_agg": "/search",
"search_subject": "/search/subjects",
"imdbid": "/movie/imdb/%s",
# 电影探索
# sort=U:综合排序 T:近期热度 S:高分优先 R:首播时间
# tags='日本,动画,2022'&start: int = 0&count: int = 20&sort=U
"movie_recommend": "/movie/recommend",
# 电视剧探索
"tv_recommend": "/tv/recommend",
# 搜索
"movie_tag": "/movie/tag",
"tv_tag": "/tv/tag",
# q=search_word&start: int = 0&count: int = 20
"movie_search": "/search/movie",
"tv_search": "/search/movie",
"book_search": "/search/book",
"group_search": "/search/group",
# 各类主题合集
# start: int = 0&count: int = 20
# 正在上映
"movie_showing": "/subject_collection/movie_showing/items",
# 热门电影
"movie_hot_gaia": "/subject_collection/movie_hot_gaia/items",
# 即将上映
"movie_soon": "/subject_collection/movie_soon/items",
# TOP250
"movie_top250": "/subject_collection/movie_top250/items",
# 高分经典科幻片榜
"movie_scifi": "/subject_collection/movie_scifi/items",
# 高分经典喜剧片榜
"movie_comedy": "/subject_collection/movie_comedy/items",
# 高分经典动作片榜
"movie_action": "/subject_collection/movie_action/items",
# 高分经典爱情片榜
"movie_love": "/subject_collection/movie_love/items",
# 热门剧集
"tv_hot": "/subject_collection/tv_hot/items",
# 国产剧
"tv_domestic": "/subject_collection/tv_domestic/items",
# 美剧
"tv_american": "/subject_collection/tv_american/items",
# 本剧
"tv_japanese": "/subject_collection/tv_japanese/items",
# 韩剧
"tv_korean": "/subject_collection/tv_korean/items",
# 动画
"tv_animation": "/subject_collection/tv_animation/items",
# 综艺
"tv_variety_show": "/subject_collection/tv_variety_show/items",
# 华语口碑周榜
"tv_chinese_best_weekly": "/subject_collection/tv_chinese_best_weekly/items",
# 全球口碑周榜
"tv_global_best_weekly": "/subject_collection/tv_global_best_weekly/items",
# 执门综艺
"show_hot": "/subject_collection/show_hot/items",
# 国内综艺
"show_domestic": "/subject_collection/show_domestic/items",
# 国外综艺
"show_foreign": "/subject_collection/show_foreign/items",
"book_bestseller": "/subject_collection/book_bestseller/items",
"book_top250": "/subject_collection/book_top250/items",
# 虚构类热门榜
"book_fiction_hot_weekly": "/subject_collection/book_fiction_hot_weekly/items",
# 非虚构类热门
"book_nonfiction_hot_weekly": "/subject_collection/book_nonfiction_hot_weekly/items",
# 音乐
"music_single": "/subject_collection/music_single/items",
# rank list
"movie_rank_list": "/movie/rank_list",
"movie_year_ranks": "/movie/year_ranks",
"book_rank_list": "/book/rank_list",
"tv_rank_list": "/tv/rank_list",
# movie info
"movie_detail": "/movie/",
"movie_rating": "/movie/%s/rating",
"movie_photos": "/movie/%s/photos",
"movie_trailers": "/movie/%s/trailers",
"movie_interests": "/movie/%s/interests",
"movie_reviews": "/movie/%s/reviews",
"movie_recommendations": "/movie/%s/recommendations",
"movie_celebrities": "/movie/%s/celebrities",
# tv info
"tv_detail": "/tv/",
"tv_rating": "/tv/%s/rating",
"tv_photos": "/tv/%s/photos",
"tv_trailers": "/tv/%s/trailers",
"tv_interests": "/tv/%s/interests",
"tv_reviews": "/tv/%s/reviews",
"tv_recommendations": "/tv/%s/recommendations",
"tv_celebrities": "/tv/%s/celebrities",
# book info
"book_detail": "/book/",
"book_rating": "/book/%s/rating",
"book_interests": "/book/%s/interests",
"book_reviews": "/book/%s/reviews",
"book_recommendations": "/book/%s/recommendations",
# music info
"music_detail": "/music/",
"music_rating": "/music/%s/rating",
"music_interests": "/music/%s/interests",
"music_reviews": "/music/%s/reviews",
"music_recommendations": "/music/%s/recommendations",
# doulist
"doulist": "/doulist/",
"doulist_items": "/doulist/%s/items",
# person
"person_detail": "/elessar/subject/",
"person_work": "/elessar/work_collections/%s/works",
}
_user_agents = [
"api-client/1 com.douban.frodo/7.22.0.beta9(231) Android/23 product/Mate 40 vendor/HUAWEI model/Mate 40 brand/HUAWEI rom/android network/wifi platform/AndroidPad"
"api-client/1 com.douban.frodo/7.18.0(230) Android/22 product/MI 9 vendor/Xiaomi model/MI 9 brand/Android rom/miui6 network/wifi platform/mobile nd/1",
"api-client/1 com.douban.frodo/7.1.0(205) Android/29 product/perseus vendor/Xiaomi model/Mi MIX 3 rom/miui6 network/wifi platform/mobile nd/1",
"api-client/1 com.douban.frodo/7.3.0(207) Android/22 product/MI 9 vendor/Xiaomi model/MI 9 brand/Android rom/miui6 network/wifi platform/mobile nd/1"]
_api_secret_key = "bf7dddc7c9cfe6f7"
_api_key = "0dad551ec0f84ed02907ff5c42e8ec70"
_api_key2 = "0ab215a8b1977939201640fa14c66bab"
_base_url = "https://frodo.douban.com/api/v2"
_api_url = "https://api.douban.com/v2"
_session = None
def __init__(self):
self._session = requests.Session()
@classmethod
def __sign(cls, url: str, ts: str, method='GET') -> str:
"""
签名
"""
url_path = parse.urlparse(url).path
raw_sign = '&'.join([method.upper(), parse.quote(url_path, safe=''), ts])
return base64.b64encode(
hmac.new(
cls._api_secret_key.encode(),
raw_sign.encode(),
hashlib.sha1
).digest()
).decode()
@cached(cache=TTLCache(maxsize=settings.CACHE_CONF["douban"], ttl=settings.CACHE_CONF["meta"]))
def __invoke_recommend(self, url: str, **kwargs) -> dict:
"""
推荐/发现类API
"""
return self.__invoke(url, **kwargs)
@cached(cache=TTLCache(maxsize=settings.CACHE_CONF["douban"], ttl=settings.CACHE_CONF["meta"]))
def __invoke_search(self, url: str, **kwargs) -> dict:
"""
搜索类API
"""
return self.__invoke(url, **kwargs)
def __invoke(self, url: str, **kwargs) -> dict:
"""
GET请求
"""
req_url = self._base_url + url
params: dict = {'apiKey': self._api_key}
if kwargs:
params.update(kwargs)
ts = params.pop(
'_ts',
datetime.strftime(datetime.now(), '%Y%m%d')
)
params.update({
'os_rom': 'android',
'apiKey': self._api_key,
'_ts': ts,
'_sig': self.__sign(url=req_url, ts=ts)
})
resp = RequestUtils(
ua=choice(self._user_agents),
session=self._session
).get_res(url=req_url, params=params)
if resp is not None and resp.status_code == 400 and "rate_limit" in resp.text:
return resp.json()
return resp.json() if resp else {}
@cached(cache=TTLCache(maxsize=settings.CACHE_CONF["douban"], ttl=settings.CACHE_CONF["meta"]))
def __post(self, url: str, **kwargs) -> dict:
"""
POST请求
esponse = requests.post(
url="https://api.douban.com/v2/movie/imdb/tt29139455",
headers={
"Content-Type": "application/x-www-form-urlencoded; charset=utf-8",
"Cookie": "bid=J9zb1zA5sJc",
},
data={
"apikey": "0ab215a8b1977939201640fa14c66bab",
}
)
"""
req_url = self._api_url + url
params = {'apikey': self._api_key2}
if kwargs:
params.update(kwargs)
if '_ts' in params:
params.pop('_ts')
resp = RequestUtils(
ua=settings.USER_AGENT,
session=self._session,
).post_res(url=req_url, data=params)
if resp is not None and resp.status_code == 400 and "rate_limit" in resp.text:
return resp.json()
return resp.json() if resp else {}
def imdbid(self, imdbid: str,
ts=datetime.strftime(datetime.now(), '%Y%m%d')):
"""
IMDBID搜索
"""
return self.__post(self._urls["imdbid"] % imdbid, _ts=ts)
def search(self, keyword: str, start: int = 0, count: int = 20,
ts=datetime.strftime(datetime.now(), '%Y%m%d')) -> dict:
"""
关键字搜索
"""
return self.__invoke_search(self._urls["search"], q=keyword,
start=start, count=count, _ts=ts)
def movie_search(self, keyword: str, start: int = 0, count: int = 20,
ts=datetime.strftime(datetime.now(), '%Y%m%d')):
"""
电影搜索
"""
return self.__invoke_search(self._urls["movie_search"], q=keyword,
start=start, count=count, _ts=ts)
def tv_search(self, keyword: str, start: int = 0, count: int = 20,
ts=datetime.strftime(datetime.now(), '%Y%m%d')):
"""
电视搜索
"""
return self.__invoke_search(self._urls["tv_search"], q=keyword,
start=start, count=count, _ts=ts)
def book_search(self, keyword: str, start: int = 0, count: int = 20,
ts=datetime.strftime(datetime.now(), '%Y%m%d')):
"""
书籍搜索
"""
return self.__invoke_search(self._urls["book_search"], q=keyword,
start=start, count=count, _ts=ts)
def group_search(self, keyword: str, start: int = 0, count: int = 20,
ts=datetime.strftime(datetime.now(), '%Y%m%d')):
"""
小组搜索
"""
return self.__invoke_search(self._urls["group_search"], q=keyword,
start=start, count=count, _ts=ts)
def person_search(self, keyword: str, start: int = 0, count: int = 20,
ts=datetime.strftime(datetime.now(), '%Y%m%d')):
"""
人物搜索
"""
return self.__invoke_search(self._urls["search_subject"], type="person", q=keyword,
start=start, count=count, _ts=ts)
def movie_showing(self, start: int = 0, count: int = 20,
ts=datetime.strftime(datetime.now(), '%Y%m%d')):
"""
正在热映
"""
return self.__invoke_recommend(self._urls["movie_showing"],
start=start, count=count, _ts=ts)
def movie_soon(self, start: int = 0, count: int = 20,
ts=datetime.strftime(datetime.now(), '%Y%m%d')):
"""
即将上映
"""
return self.__invoke_recommend(self._urls["movie_soon"],
start=start, count=count, _ts=ts)
def movie_hot_gaia(self, start: int = 0, count: int = 20,
ts=datetime.strftime(datetime.now(), '%Y%m%d')):
"""
热门电影
"""
return self.__invoke_recommend(self._urls["movie_hot_gaia"],
start=start, count=count, _ts=ts)
def tv_hot(self, start: int = 0, count: int = 20,
ts=datetime.strftime(datetime.now(), '%Y%m%d')):
"""
热门剧集
"""
return self.__invoke_recommend(self._urls["tv_hot"],
start=start, count=count, _ts=ts)
def tv_animation(self, start: int = 0, count: int = 20,
ts=datetime.strftime(datetime.now(), '%Y%m%d')):
"""
动画
"""
return self.__invoke_recommend(self._urls["tv_animation"],
start=start, count=count, _ts=ts)
def tv_variety_show(self, start: int = 0, count: int = 20,
ts=datetime.strftime(datetime.now(), '%Y%m%d')):
"""
综艺
"""
return self.__invoke_recommend(self._urls["tv_variety_show"],
start=start, count=count, _ts=ts)
def tv_rank_list(self, start: int = 0, count: int = 20,
ts=datetime.strftime(datetime.now(), '%Y%m%d')):
"""
电视剧排行榜
"""
return self.__invoke_recommend(self._urls["tv_rank_list"],
start=start, count=count, _ts=ts)
def show_hot(self, start: int = 0, count: int = 20,
ts=datetime.strftime(datetime.now(), '%Y%m%d')):
"""
综艺热门
"""
return self.__invoke_recommend(self._urls["show_hot"],
start=start, count=count, _ts=ts)
def movie_detail(self, subject_id: str):
"""
电影详情
"""
return self.__invoke_search(self._urls["movie_detail"] + subject_id)
def movie_celebrities(self, subject_id: str):
"""
电影演职员
"""
return self.__invoke_search(self._urls["movie_celebrities"] % subject_id)
def tv_detail(self, subject_id: str):
"""
电视剧详情
"""
return self.__invoke_search(self._urls["tv_detail"] + subject_id)
def tv_celebrities(self, subject_id: str):
"""
电视剧演职员
"""
return self.__invoke_search(self._urls["tv_celebrities"] % subject_id)
def book_detail(self, subject_id: str):
"""
书籍详情
"""
return self.__invoke_search(self._urls["book_detail"] + subject_id)
def movie_top250(self, start: int = 0, count: int = 20,
ts=datetime.strftime(datetime.now(), '%Y%m%d')):
"""
电影TOP250
"""
return self.__invoke_recommend(self._urls["movie_top250"],
start=start, count=count, _ts=ts)
def movie_recommend(self, tags='', sort='R', start: int = 0, count: int = 20,
ts=datetime.strftime(datetime.now(), '%Y%m%d')):
"""
电影探索
"""
return self.__invoke_recommend(self._urls["movie_recommend"], tags=tags, sort=sort,
start=start, count=count, _ts=ts)
def tv_recommend(self, tags='', sort='R', start: int = 0, count: int = 20,
ts=datetime.strftime(datetime.now(), '%Y%m%d')):
"""
电视剧探索
"""
return self.__invoke_recommend(self._urls["tv_recommend"], tags=tags, sort=sort,
start=start, count=count, _ts=ts)
def tv_chinese_best_weekly(self, start: int = 0, count: int = 20,
ts=datetime.strftime(datetime.now(), '%Y%m%d')):
"""
华语口碑周榜
"""
return self.__invoke_recommend(self._urls["tv_chinese_best_weekly"],
start=start, count=count, _ts=ts)
def tv_global_best_weekly(self, start: int = 0, count: int = 20,
ts=datetime.strftime(datetime.now(), '%Y%m%d')):
"""
全球口碑周榜
"""
return self.__invoke_recommend(self._urls["tv_global_best_weekly"],
start=start, count=count, _ts=ts)
def doulist_detail(self, subject_id: str):
"""
豆列详情
:param subject_id: 豆列id
"""
return self.__invoke_search(self._urls["doulist"] + subject_id)
def doulist_items(self, subject_id: str, start: int = 0, count: int = 20,
ts=datetime.strftime(datetime.now(), '%Y%m%d')):
"""
豆列列表
:param subject_id: 豆列id
:param start: 开始
:param count: 数量
:param ts: 时间戳
"""
return self.__invoke_search(self._urls["doulist_items"] % subject_id,
start=start, count=count, _ts=ts)
def movie_recommendations(self, subject_id: str, start: int = 0, count: int = 20,
ts=datetime.strftime(datetime.now(), '%Y%m%d')):
"""
电影推荐
:param subject_id: 电影id
:param start: 开始
:param count: 数量
:param ts: 时间戳
"""
return self.__invoke_recommend(self._urls["movie_recommendations"] % subject_id,
start=start, count=count, _ts=ts)
def tv_recommendations(self, subject_id: str, start: int = 0, count: int = 20,
ts=datetime.strftime(datetime.now(), '%Y%m%d')):
"""
电视剧推荐
:param subject_id: 电视剧id
:param start: 开始
:param count: 数量
:param ts: 时间戳
"""
return self.__invoke_recommend(self._urls["tv_recommendations"] % subject_id,
start=start, count=count, _ts=ts)
def movie_photos(self, subject_id: str, start: int = 0, count: int = 20,
ts=datetime.strftime(datetime.now(), '%Y%m%d')):
"""
电影剧照
:param subject_id: 电影id
:param start: 开始
:param count: 数量
:param ts: 时间戳
"""
return self.__invoke_search(self._urls["movie_photos"] % subject_id,
start=start, count=count, _ts=ts)
def tv_photos(self, subject_id: str, start: int = 0, count: int = 20,
ts=datetime.strftime(datetime.now(), '%Y%m%d')):
"""
电视剧剧照
:param subject_id: 电视剧id
:param start: 开始
:param count: 数量
:param ts: 时间戳
"""
return self.__invoke_search(self._urls["tv_photos"] % subject_id,
start=start, count=count, _ts=ts)
def person_detail(self, subject_id: int):
"""
用户详情
:param subject_id: 人物 id
:return:
"""
return self.__invoke_search(self._urls["person_detail"] + str(subject_id))
def person_work(self, subject_id: int, start: int = 0, count: int = 20, sort_by: str = "time",
collection_title: str = "影视",
ts=datetime.strftime(datetime.now(), '%Y%m%d')):
"""
用户作品集
:param subject_id: work_collection id
:param start: 开始页
:param count: 数量
:param sort_by: collection or time or vote
:param collection_title: 影视 or 图书 or 音乐
:param ts: 时间戳
:return:
"""
return self.__invoke_search(self._urls["person_work"] % subject_id, sortby=sort_by,
collection_title=collection_title,
start=start, count=count, _ts=ts)
def clear_cache(self):
"""
清空LRU缓存
"""
# 尚未支持缓存清理
pass
def close(self):
if self._session:
self._session.close()