feat:推荐使用异步API

This commit is contained in:
jxxghp
2025-07-31 09:50:49 +08:00
parent ceda69aedd
commit dee1212a76
5 changed files with 585 additions and 240 deletions

View File

@@ -3,11 +3,11 @@ from typing import Any, List, Optional
from fastapi import APIRouter, Depends
from app import schemas
from app.chain.recommend import RecommendChain
from app.core.event import eventmanager
from app.core.security import verify_token
from app.schemas.types import ChainEventType
from app.chain.recommend import RecommendChain
from app.schemas import RecommendSourceEventData
from app.schemas.types import ChainEventType
router = APIRouter()
@@ -29,163 +29,163 @@ def source(_: schemas.TokenPayload = Depends(verify_token)) -> Any:
@router.get("/bangumi_calendar", summary="Bangumi每日放送", response_model=List[schemas.MediaInfo])
def bangumi_calendar(page: Optional[int] = 1,
count: Optional[int] = 30,
_: schemas.TokenPayload = Depends(verify_token)) -> Any:
async def bangumi_calendar(page: Optional[int] = 1,
count: Optional[int] = 30,
_: schemas.TokenPayload = Depends(verify_token)) -> Any:
"""
浏览Bangumi每日放送
"""
return RecommendChain().bangumi_calendar(page=page, count=count)
return await RecommendChain().async_bangumi_calendar(page=page, count=count)
@router.get("/douban_showing", summary="豆瓣正在热映", response_model=List[schemas.MediaInfo])
def douban_showing(page: Optional[int] = 1,
count: Optional[int] = 30,
_: schemas.TokenPayload = Depends(verify_token)) -> Any:
async def douban_showing(page: Optional[int] = 1,
count: Optional[int] = 30,
_: schemas.TokenPayload = Depends(verify_token)) -> Any:
"""
浏览豆瓣正在热映
"""
return RecommendChain().douban_movie_showing(page=page, count=count)
return await RecommendChain().async_douban_movie_showing(page=page, count=count)
@router.get("/douban_movies", summary="豆瓣电影", response_model=List[schemas.MediaInfo])
def douban_movies(sort: Optional[str] = "R",
tags: Optional[str] = "",
page: Optional[int] = 1,
count: Optional[int] = 30,
_: schemas.TokenPayload = Depends(verify_token)) -> Any:
async def douban_movies(sort: Optional[str] = "R",
tags: Optional[str] = "",
page: Optional[int] = 1,
count: Optional[int] = 30,
_: schemas.TokenPayload = Depends(verify_token)) -> Any:
"""
浏览豆瓣电影信息
"""
return RecommendChain().douban_movies(sort=sort, tags=tags, page=page, count=count)
return await RecommendChain().async_douban_movies(sort=sort, tags=tags, page=page, count=count)
@router.get("/douban_tvs", summary="豆瓣剧集", response_model=List[schemas.MediaInfo])
def douban_tvs(sort: Optional[str] = "R",
tags: Optional[str] = "",
page: Optional[int] = 1,
count: Optional[int] = 30,
_: schemas.TokenPayload = Depends(verify_token)) -> Any:
"""
浏览豆瓣剧集信息
"""
return RecommendChain().douban_tvs(sort=sort, tags=tags, page=page, count=count)
@router.get("/douban_movie_top250", summary="豆瓣电影TOP250", response_model=List[schemas.MediaInfo])
def douban_movie_top250(page: Optional[int] = 1,
count: Optional[int] = 30,
_: schemas.TokenPayload = Depends(verify_token)) -> Any:
"""
浏览豆瓣剧集信息
"""
return RecommendChain().douban_movie_top250(page=page, count=count)
@router.get("/douban_tv_weekly_chinese", summary="豆瓣国产剧集周榜", response_model=List[schemas.MediaInfo])
def douban_tv_weekly_chinese(page: Optional[int] = 1,
count: Optional[int] = 30,
_: schemas.TokenPayload = Depends(verify_token)) -> Any:
"""
中国每周剧集口碑榜
"""
return RecommendChain().douban_tv_weekly_chinese(page=page, count=count)
@router.get("/douban_tv_weekly_global", summary="豆瓣全球剧集周榜", response_model=List[schemas.MediaInfo])
def douban_tv_weekly_global(page: Optional[int] = 1,
count: Optional[int] = 30,
_: schemas.TokenPayload = Depends(verify_token)) -> Any:
"""
全球每周剧集口碑榜
"""
return RecommendChain().douban_tv_weekly_global(page=page, count=count)
@router.get("/douban_tv_animation", summary="豆瓣动画剧集", response_model=List[schemas.MediaInfo])
def douban_tv_animation(page: Optional[int] = 1,
count: Optional[int] = 30,
_: schemas.TokenPayload = Depends(verify_token)) -> Any:
"""
热门动画剧集
"""
return RecommendChain().douban_tv_animation(page=page, count=count)
@router.get("/douban_movie_hot", summary="豆瓣热门电影", response_model=List[schemas.MediaInfo])
def douban_movie_hot(page: Optional[int] = 1,
async def douban_tvs(sort: Optional[str] = "R",
tags: Optional[str] = "",
page: Optional[int] = 1,
count: Optional[int] = 30,
_: schemas.TokenPayload = Depends(verify_token)) -> Any:
"""
浏览豆瓣剧集信息
"""
return await RecommendChain().async_douban_tvs(sort=sort, tags=tags, page=page, count=count)
@router.get("/douban_movie_top250", summary="豆瓣电影TOP250", response_model=List[schemas.MediaInfo])
async def douban_movie_top250(page: Optional[int] = 1,
count: Optional[int] = 30,
_: schemas.TokenPayload = Depends(verify_token)) -> Any:
"""
浏览豆瓣剧集信息
"""
return await RecommendChain().async_douban_movie_top250(page=page, count=count)
@router.get("/douban_tv_weekly_chinese", summary="豆瓣国产剧集周榜", response_model=List[schemas.MediaInfo])
async def douban_tv_weekly_chinese(page: Optional[int] = 1,
count: Optional[int] = 30,
_: schemas.TokenPayload = Depends(verify_token)) -> Any:
"""
中国每周剧集口碑榜
"""
return await RecommendChain().async_douban_tv_weekly_chinese(page=page, count=count)
@router.get("/douban_tv_weekly_global", summary="豆瓣全球剧集周榜", response_model=List[schemas.MediaInfo])
async def douban_tv_weekly_global(page: Optional[int] = 1,
count: Optional[int] = 30,
_: schemas.TokenPayload = Depends(verify_token)) -> Any:
"""
全球每周剧集口碑榜
"""
return await RecommendChain().async_douban_tv_weekly_global(page=page, count=count)
@router.get("/douban_tv_animation", summary="豆瓣动画剧集", response_model=List[schemas.MediaInfo])
async def douban_tv_animation(page: Optional[int] = 1,
count: Optional[int] = 30,
_: schemas.TokenPayload = Depends(verify_token)) -> Any:
"""
热门动画剧集
"""
return await RecommendChain().async_douban_tv_animation(page=page, count=count)
@router.get("/douban_movie_hot", summary="豆瓣热门电影", response_model=List[schemas.MediaInfo])
async def douban_movie_hot(page: Optional[int] = 1,
count: Optional[int] = 30,
_: schemas.TokenPayload = Depends(verify_token)) -> Any:
"""
热门电影
"""
return RecommendChain().douban_movie_hot(page=page, count=count)
return await RecommendChain().async_douban_movie_hot(page=page, count=count)
@router.get("/douban_tv_hot", summary="豆瓣热门电视剧", response_model=List[schemas.MediaInfo])
def douban_tv_hot(page: Optional[int] = 1,
count: Optional[int] = 30,
_: schemas.TokenPayload = Depends(verify_token)) -> Any:
async def douban_tv_hot(page: Optional[int] = 1,
count: Optional[int] = 30,
_: schemas.TokenPayload = Depends(verify_token)) -> Any:
"""
热门电视剧
"""
return RecommendChain().douban_tv_hot(page=page, count=count)
return await RecommendChain().async_douban_tv_hot(page=page, count=count)
@router.get("/tmdb_movies", summary="TMDB电影", response_model=List[schemas.MediaInfo])
def tmdb_movies(sort_by: Optional[str] = "popularity.desc",
with_genres: Optional[str] = "",
with_original_language: Optional[str] = "",
with_keywords: Optional[str] = "",
with_watch_providers: Optional[str] = "",
vote_average: Optional[float] = 0.0,
vote_count: Optional[int] = 0,
release_date: Optional[str] = "",
page: Optional[int] = 1,
_: schemas.TokenPayload = Depends(verify_token)) -> Any:
async def tmdb_movies(sort_by: Optional[str] = "popularity.desc",
with_genres: Optional[str] = "",
with_original_language: Optional[str] = "",
with_keywords: Optional[str] = "",
with_watch_providers: Optional[str] = "",
vote_average: Optional[float] = 0.0,
vote_count: Optional[int] = 0,
release_date: Optional[str] = "",
page: Optional[int] = 1,
_: schemas.TokenPayload = Depends(verify_token)) -> Any:
"""
浏览TMDB电影信息
"""
return RecommendChain().tmdb_movies(sort_by=sort_by,
with_genres=with_genres,
with_original_language=with_original_language,
with_keywords=with_keywords,
with_watch_providers=with_watch_providers,
vote_average=vote_average,
vote_count=vote_count,
release_date=release_date,
page=page)
return await RecommendChain().async_tmdb_movies(sort_by=sort_by,
with_genres=with_genres,
with_original_language=with_original_language,
with_keywords=with_keywords,
with_watch_providers=with_watch_providers,
vote_average=vote_average,
vote_count=vote_count,
release_date=release_date,
page=page)
@router.get("/tmdb_tvs", summary="TMDB剧集", response_model=List[schemas.MediaInfo])
def tmdb_tvs(sort_by: Optional[str] = "popularity.desc",
with_genres: Optional[str] = "",
with_original_language: Optional[str] = "",
with_keywords: Optional[str] = "",
with_watch_providers: Optional[str] = "",
vote_average: Optional[float] = 0.0,
vote_count: Optional[int] = 0,
release_date: Optional[str] = "",
page: Optional[int] = 1,
_: schemas.TokenPayload = Depends(verify_token)) -> Any:
async def tmdb_tvs(sort_by: Optional[str] = "popularity.desc",
with_genres: Optional[str] = "",
with_original_language: Optional[str] = "",
with_keywords: Optional[str] = "",
with_watch_providers: Optional[str] = "",
vote_average: Optional[float] = 0.0,
vote_count: Optional[int] = 0,
release_date: Optional[str] = "",
page: Optional[int] = 1,
_: schemas.TokenPayload = Depends(verify_token)) -> Any:
"""
浏览TMDB剧集信息
"""
return RecommendChain().tmdb_tvs(sort_by=sort_by,
with_genres=with_genres,
with_original_language=with_original_language,
with_keywords=with_keywords,
with_watch_providers=with_watch_providers,
vote_average=vote_average,
vote_count=vote_count,
release_date=release_date,
page=page)
return await RecommendChain().async_tmdb_tvs(sort_by=sort_by,
with_genres=with_genres,
with_original_language=with_original_language,
with_keywords=with_keywords,
with_watch_providers=with_watch_providers,
vote_average=vote_average,
vote_count=vote_count,
release_date=release_date,
page=page)
@router.get("/tmdb_trending", summary="TMDB流行趋势", response_model=List[schemas.MediaInfo])
def tmdb_trending(page: Optional[int] = 1,
_: schemas.TokenPayload = Depends(verify_token)) -> Any:
async def tmdb_trending(page: Optional[int] = 1,
_: schemas.TokenPayload = Depends(verify_token)) -> Any:
"""
TMDB流行趋势
"""
return RecommendChain().tmdb_trending(page=page)
return await RecommendChain().async_tmdb_trending(page=page)

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@@ -2,15 +2,14 @@ import asyncio
import io
import json
import re
import tempfile
from collections import deque
from datetime import datetime
from typing import Optional, Union, Annotated
import aiofiles
import pillow_avif # noqa 用于自动注册AVIF支持
from PIL import Image
from aiopath import AsyncPath
from app.helper.sites import SitesHelper # noqa # noqa
from fastapi import APIRouter, Body, Depends, HTTPException, Header, Request, Response
from fastapi.responses import StreamingResponse
@@ -29,6 +28,7 @@ from app.helper.mediaserver import MediaServerHelper
from app.helper.message import MessageHelper
from app.helper.progress import ProgressHelper
from app.helper.rule import RuleHelper
from app.helper.sites import SitesHelper # noqa # noqa
from app.helper.subscribe import SubscribeHelper
from app.helper.system import SystemHelper
from app.log import logger
@@ -121,8 +121,8 @@ async def fetch_image(
try:
if not await cache_path.parent.exists():
await cache_path.parent.mkdir(parents=True, exist_ok=True)
with tempfile.NamedTemporaryFile(dir=cache_path.parent, delete=False) as tmp_file:
tmp_file.write(content)
async with aiofiles.tempfile.NamedTemporaryFile(dir=cache_path.parent, delete=False) as tmp_file:
await tmp_file.write(content)
temp_path = AsyncPath(tmp_file.name)
await temp_path.replace(cache_path)
except Exception as e:

View File

@@ -1,10 +1,11 @@
import asyncio
import io
import tempfile
from pathlib import Path
from typing import List, Optional
import aiofiles
import pillow_avif # noqa 用于自动注册AVIF支持
from PIL import Image
from aiopath import AsyncPath
from app.chain import ChainBase
from app.chain.bangumi import BangumiChain
@@ -15,7 +16,7 @@ from app.core.config import settings, global_vars
from app.log import logger
from app.schemas import MediaType
from app.utils.common import log_execution_time
from app.utils.http import RequestUtils
from app.utils.http import AsyncRequestUtils
from app.utils.security import SecurityUtils
from app.utils.singleton import Singleton
@@ -34,127 +35,13 @@ class RecommendChain(ChainBase, metaclass=Singleton):
def refresh_recommend(self):
"""
刷新推荐
刷新推荐数据 - 同步包装器
"""
logger.debug("Starting to refresh Recommend data.")
cache_backend.clear(region=recommend_cache_region)
logger.debug("Recommend Cache has been cleared.")
# 推荐来源方法
recommend_methods = [
self.tmdb_movies,
self.tmdb_tvs,
self.tmdb_trending,
self.bangumi_calendar,
self.douban_movie_showing,
self.douban_movies,
self.douban_tvs,
self.douban_movie_top250,
self.douban_tv_weekly_chinese,
self.douban_tv_weekly_global,
self.douban_tv_animation,
self.douban_movie_hot,
self.douban_tv_hot,
]
# 缓存并刷新所有推荐数据
recommends = []
# 记录哪些方法已完成
methods_finished = set()
# 这里避免区间内连续调用相同来源,因此遍历方案为每页遍历所有推荐来源,再进行页数遍历
for page in range(1, self.cache_max_pages + 1):
for method in recommend_methods:
if global_vars.is_system_stopped:
return
if method in methods_finished:
continue
logger.debug(f"Fetch {method.__name__} data for page {page}.")
data = method(page=page)
if not data:
logger.debug("All recommendation methods have finished fetching data. Ending pagination early.")
methods_finished.add(method)
continue
recommends.extend(data)
# 如果所有方法都已经完成,提前结束循环
if len(methods_finished) == len(recommend_methods):
break
# 缓存收集到的海报
self.__cache_posters(recommends)
logger.debug("Recommend data refresh completed.")
def __cache_posters(self, datas: List[dict]):
"""
提取 poster_path 并缓存图片
:param datas: 数据列表
"""
if not settings.GLOBAL_IMAGE_CACHE:
return
for data in datas:
if global_vars.is_system_stopped:
return
poster_path = data.get("poster_path")
if poster_path:
poster_url = poster_path.replace("original", "w500")
logger.debug(f"Caching poster image: {poster_url}")
self.__fetch_and_save_image(poster_url)
@staticmethod
def __fetch_and_save_image(url: str):
"""
请求并保存图片
:param url: 图片路径
"""
if not settings.GLOBAL_IMAGE_CACHE or not url:
return
# 生成缓存路径
sanitized_path = SecurityUtils.sanitize_url_path(url)
cache_path = settings.CACHE_PATH / "images" / sanitized_path
# 没有文件类型,则添加后缀,在恶意文件类型和实际需求下的折衷选择
if not cache_path.suffix:
cache_path = cache_path.with_suffix(".jpg")
# 确保缓存路径和文件类型合法
if not SecurityUtils.is_safe_path(settings.CACHE_PATH, cache_path, settings.SECURITY_IMAGE_SUFFIXES):
logger.debug(f"Invalid cache path or file type for URL: {url}, sanitized path: {sanitized_path}")
return
# 本地存在缓存图片,则直接跳过
if cache_path.exists():
logger.debug(f"Cache hit: Image already exists at {cache_path}")
return
# 请求远程图片
referer = "https://movie.douban.com/" if "doubanio.com" in url else None
proxies = settings.PROXY if not referer else None
response = RequestUtils(ua=settings.NORMAL_USER_AGENT, proxies=proxies, referer=referer).get_res(url=url)
if not response:
logger.debug(f"Empty response for URL: {url}")
return
# 验证下载的内容是否为有效图片
try:
Image.open(io.BytesIO(response.content)).verify()
asyncio.run(self.async_refresh_recommend())
except Exception as e:
logger.debug(f"Invalid image format for URL {url}: {e}")
return
if not cache_path:
return
try:
if not cache_path.parent.exists():
cache_path.parent.mkdir(parents=True, exist_ok=True)
with tempfile.NamedTemporaryFile(dir=cache_path.parent, delete=False) as tmp_file:
tmp_file.write(response.content)
temp_path = Path(tmp_file.name)
temp_path.replace(cache_path)
logger.debug(f"Successfully cached image at {cache_path} for URL: {url}")
except Exception as e:
logger.debug(f"Failed to write cache file {cache_path} for URL {url}: {e}")
logger.error(f"刷新推荐数据失败:{str(e)}")
raise
@log_execution_time(logger=logger)
@cached(ttl=recommend_ttl, region=recommend_cache_region)
@@ -310,3 +197,314 @@ class RecommendChain(ChainBase, metaclass=Singleton):
"""
tvs = DoubanChain().tv_hot(page=page, count=count)
return [media.to_dict() for media in tvs] if tvs else []
# 异步版本的方法
async def async_refresh_recommend(self):
"""
异步刷新推荐
"""
logger.debug("Starting to async refresh Recommend data.")
cache_backend.clear(region=recommend_cache_region)
logger.debug("Recommend Cache has been cleared.")
# 推荐来源方法
recommend_methods = [
self.async_tmdb_movies,
self.async_tmdb_tvs,
self.async_tmdb_trending,
self.async_bangumi_calendar,
self.async_douban_movie_showing,
self.async_douban_movies,
self.async_douban_tvs,
self.async_douban_movie_top250,
self.async_douban_tv_weekly_chinese,
self.async_douban_tv_weekly_global,
self.async_douban_tv_animation,
self.async_douban_movie_hot,
self.async_douban_tv_hot,
]
# 缓存并刷新所有推荐数据
recommends = []
# 记录哪些方法已完成
methods_finished = set()
# 这里避免区间内连续调用相同来源,因此遍历方案为每页遍历所有推荐来源,再进行页数遍历
for page in range(1, self.cache_max_pages + 1):
# 为每个页面并发执行所有方法
tasks = []
for method in recommend_methods:
if global_vars.is_system_stopped:
return
if method in methods_finished:
continue
tasks.append(self._async_fetch_method_data(method, page, methods_finished))
# 并发执行所有任务
if tasks:
results = await asyncio.gather(*tasks, return_exceptions=True)
for result in results:
if isinstance(result, list) and result:
recommends.extend(result)
# 如果所有方法都已经完成,提前结束循环
if len(methods_finished) == len(recommend_methods):
break
# 缓存收集到的海报
await self.__async_cache_posters(recommends)
logger.debug("Async recommend data refresh completed.")
@staticmethod
async def _async_fetch_method_data(method, page: int, methods_finished: set):
"""
异步获取方法数据的辅助函数
"""
try:
logger.debug(f"Async fetch {method.__name__} data for page {page}.")
data = await method(page=page)
if not data:
logger.debug(f"Method {method.__name__} finished fetching data. Ending pagination early.")
methods_finished.add(method)
return []
return data
except Exception as e:
logger.error(f"Error fetching data from {method.__name__}: {e}")
methods_finished.add(method)
return []
async def __async_cache_posters(self, datas: List[dict]):
"""
异步提取 poster_path 并缓存图片
:param datas: 数据列表
"""
if not settings.GLOBAL_IMAGE_CACHE:
return
tasks = []
for data in datas:
if global_vars.is_system_stopped:
return
poster_path = data.get("poster_path")
if poster_path:
poster_url = poster_path.replace("original", "w500")
logger.debug(f"Async caching poster image: {poster_url}")
tasks.append(self.__async_fetch_and_save_image(poster_url))
# 并发缓存图片
if tasks:
await asyncio.gather(*tasks, return_exceptions=True)
@staticmethod
async def __async_fetch_and_save_image(url: str):
"""
异步请求并保存图片
:param url: 图片路径
"""
if not settings.GLOBAL_IMAGE_CACHE or not url:
return
# 生成缓存路径
base_path = AsyncPath(settings.CACHE_PATH)
sanitized_path = SecurityUtils.sanitize_url_path(url)
cache_path = base_path / "images" / sanitized_path
# 没有文件类型,则添加后缀,在恶意文件类型和实际需求下的折衷选择
if not cache_path.suffix:
cache_path = cache_path.with_suffix(".jpg")
# 确保缓存路径和文件类型合法
if not await SecurityUtils.async_is_safe_path(base_path=base_path,
user_path=cache_path,
allowed_suffixes=settings.SECURITY_IMAGE_SUFFIXES):
logger.debug(f"Invalid cache path or file type for URL: {url}, sanitized path: {sanitized_path}")
return
# 本地存在缓存图片,则直接跳过
if await cache_path.exists():
logger.debug(f"Cache hit: Image already exists at {cache_path}")
return
# 请求远程图片
referer = "https://movie.douban.com/" if "doubanio.com" in url else None
proxies = settings.PROXY if not referer else None
response = await AsyncRequestUtils(ua=settings.NORMAL_USER_AGENT,
proxies=proxies, referer=referer).get_res(url=url)
if not response:
logger.debug(f"Empty response for URL: {url}")
return
# 验证下载的内容是否为有效图片
try:
Image.open(io.BytesIO(response.content)).verify()
except Exception as e:
logger.debug(f"Invalid image format for URL {url}: {e}")
return
if not cache_path:
return
try:
if not await cache_path.parent.exists():
await cache_path.parent.mkdir(parents=True, exist_ok=True)
async with aiofiles.tempfile.NamedTemporaryFile(dir=cache_path.parent, delete=False) as tmp_file:
await tmp_file.write(response.content)
temp_path = AsyncPath(tmp_file.name)
await temp_path.replace(cache_path)
logger.debug(f"Successfully cached image at {cache_path} for URL: {url}")
except Exception as e:
logger.debug(f"Failed to write cache file {cache_path} for URL {url}: {e}")
@log_execution_time(logger=logger)
@cached(ttl=recommend_ttl, region=recommend_cache_region)
async def async_tmdb_movies(self, sort_by: Optional[str] = "popularity.desc",
with_genres: Optional[str] = "",
with_original_language: Optional[str] = "",
with_keywords: Optional[str] = "",
with_watch_providers: Optional[str] = "",
vote_average: Optional[float] = 0.0,
vote_count: Optional[int] = 0,
release_date: Optional[str] = "",
page: Optional[int] = 1) -> List[dict]:
"""
异步TMDB热门电影
"""
movies = await TmdbChain().async_run_module("async_tmdb_discover", mtype=MediaType.MOVIE,
sort_by=sort_by,
with_genres=with_genres,
with_original_language=with_original_language,
with_keywords=with_keywords,
with_watch_providers=with_watch_providers,
vote_average=vote_average,
vote_count=vote_count,
release_date=release_date,
page=page)
return [movie.to_dict() for movie in movies] if movies else []
@log_execution_time(logger=logger)
@cached(ttl=recommend_ttl, region=recommend_cache_region)
async def async_tmdb_tvs(self, sort_by: Optional[str] = "popularity.desc",
with_genres: Optional[str] = "",
with_original_language: Optional[str] = "zh|en|ja|ko",
with_keywords: Optional[str] = "",
with_watch_providers: Optional[str] = "",
vote_average: Optional[float] = 0.0,
vote_count: Optional[int] = 0,
release_date: Optional[str] = "",
page: Optional[int] = 1) -> List[dict]:
"""
异步TMDB热门电视剧
"""
tvs = await TmdbChain().async_run_module("async_tmdb_discover", mtype=MediaType.TV,
sort_by=sort_by,
with_genres=with_genres,
with_original_language=with_original_language,
with_keywords=with_keywords,
with_watch_providers=with_watch_providers,
vote_average=vote_average,
vote_count=vote_count,
release_date=release_date,
page=page)
return [tv.to_dict() for tv in tvs] if tvs else []
@log_execution_time(logger=logger)
@cached(ttl=recommend_ttl, region=recommend_cache_region)
async def async_tmdb_trending(self, page: Optional[int] = 1) -> List[dict]:
"""
异步TMDB流行趋势
"""
infos = await TmdbChain().async_run_module("async_tmdb_trending", page=page)
return [info.to_dict() for info in infos] if infos else []
@log_execution_time(logger=logger)
@cached(ttl=recommend_ttl, region=recommend_cache_region)
async def async_bangumi_calendar(self, page: Optional[int] = 1, count: Optional[int] = 30) -> List[dict]:
"""
异步Bangumi每日放送
"""
medias = await BangumiChain().async_run_module("async_bangumi_calendar")
return [media.to_dict() for media in medias[(page - 1) * count: page * count]] if medias else []
@log_execution_time(logger=logger)
@cached(ttl=recommend_ttl, region=recommend_cache_region)
async def async_douban_movie_showing(self, page: Optional[int] = 1, count: Optional[int] = 30) -> List[dict]:
"""
异步豆瓣正在热映
"""
movies = await DoubanChain().async_run_module("async_movie_showing", page=page, count=count)
return [media.to_dict() for media in movies] if movies else []
@log_execution_time(logger=logger)
@cached(ttl=recommend_ttl, region=recommend_cache_region)
async def async_douban_movies(self, sort: Optional[str] = "R", tags: Optional[str] = "",
page: Optional[int] = 1, count: Optional[int] = 30) -> List[dict]:
"""
异步豆瓣最新电影
"""
movies = await DoubanChain().async_run_module("async_douban_discover", mtype=MediaType.MOVIE,
sort=sort, tags=tags, page=page, count=count)
return [media.to_dict() for media in movies] if movies else []
@log_execution_time(logger=logger)
@cached(ttl=recommend_ttl, region=recommend_cache_region)
async def async_douban_tvs(self, sort: Optional[str] = "R", tags: Optional[str] = "",
page: Optional[int] = 1, count: Optional[int] = 30) -> List[dict]:
"""
异步豆瓣最新电视剧
"""
tvs = await DoubanChain().async_run_module("async_douban_discover", mtype=MediaType.TV,
sort=sort, tags=tags, page=page, count=count)
return [media.to_dict() for media in tvs] if tvs else []
@log_execution_time(logger=logger)
@cached(ttl=recommend_ttl, region=recommend_cache_region)
async def async_douban_movie_top250(self, page: Optional[int] = 1, count: Optional[int] = 30) -> List[dict]:
"""
异步豆瓣电影TOP250
"""
movies = await DoubanChain().async_run_module("async_movie_top250", page=page, count=count)
return [media.to_dict() for media in movies] if movies else []
@log_execution_time(logger=logger)
@cached(ttl=recommend_ttl, region=recommend_cache_region)
async def async_douban_tv_weekly_chinese(self, page: Optional[int] = 1, count: Optional[int] = 30) -> List[dict]:
"""
异步豆瓣国产剧集榜
"""
tvs = await DoubanChain().async_run_module("async_tv_weekly_chinese", page=page, count=count)
return [media.to_dict() for media in tvs] if tvs else []
@log_execution_time(logger=logger)
@cached(ttl=recommend_ttl, region=recommend_cache_region)
async def async_douban_tv_weekly_global(self, page: Optional[int] = 1, count: Optional[int] = 30) -> List[dict]:
"""
异步豆瓣全球剧集榜
"""
tvs = await DoubanChain().async_run_module("async_tv_weekly_global", page=page, count=count)
return [media.to_dict() for media in tvs] if tvs else []
@log_execution_time(logger=logger)
@cached(ttl=recommend_ttl, region=recommend_cache_region)
async def async_douban_tv_animation(self, page: Optional[int] = 1, count: Optional[int] = 30) -> List[dict]:
"""
异步豆瓣热门动漫
"""
tvs = await DoubanChain().async_run_module("async_tv_animation", page=page, count=count)
return [media.to_dict() for media in tvs] if tvs else []
@log_execution_time(logger=logger)
@cached(ttl=recommend_ttl, region=recommend_cache_region)
async def async_douban_movie_hot(self, page: Optional[int] = 1, count: Optional[int] = 30) -> List[dict]:
"""
异步豆瓣热门电影
"""
movies = await DoubanChain().async_run_module("async_movie_hot", page=page, count=count)
return [media.to_dict() for media in movies] if movies else []
@log_execution_time(logger=logger)
@cached(ttl=recommend_ttl, region=recommend_cache_region)
async def async_douban_tv_hot(self, page: Optional[int] = 1, count: Optional[int] = 30) -> List[dict]:
"""
异步豆瓣热门电视剧
"""
tvs = await DoubanChain().async_run_module("async_tv_hot", page=page, count=count)
return [media.to_dict() for media in tvs] if tvs else []

View File

@@ -782,6 +782,152 @@ class TheMovieDbModule(_ModuleBase):
return [MediaInfo(tmdb_info=info) for info in infos]
return []
async def async_tmdb_trending(self, page: Optional[int] = 1) -> List[MediaInfo]:
"""
TMDB流行趋势异步版本
:param page: 第几页
:return: TMDB信息列表
"""
trending = await self.tmdb.async_discover_trending(page=page)
if trending:
return [MediaInfo(tmdb_info=info) for info in trending]
return []
async def async_tmdb_collection(self, collection_id: int) -> Optional[List[MediaInfo]]:
"""
根据合集ID查询集合异步版本
:param collection_id: 合集ID
"""
results = await self.tmdb.async_get_collection(collection_id)
if results:
return [MediaInfo(tmdb_info=info) for info in results]
return []
async def async_tmdb_seasons(self, tmdbid: int) -> List[schemas.TmdbSeason]:
"""
根据TMDBID查询themoviedb所有季信息异步版本
:param tmdbid: TMDBID
"""
tmdb_info = await self.tmdb.async_get_info(tmdbid=tmdbid, mtype=MediaType.TV)
if not tmdb_info:
return []
return [schemas.TmdbSeason(**sea)
for sea in tmdb_info.get("seasons", []) if sea.get("season_number")]
async def async_tmdb_group_seasons(self, group_id: str) -> List[schemas.TmdbSeason]:
"""
根据剧集组ID查询themoviedb所有季集信息异步版本
:param group_id: 剧集组ID
"""
group_seasons = await self.tmdb.async_get_tv_group_seasons(group_id)
if not group_seasons:
return []
return [schemas.TmdbSeason(
season_number=sea.get("order"),
name=sea.get("name"),
episode_count=len(sea.get("episodes") or []),
air_date=sea.get("episodes")[0].get("air_date") if sea.get("episodes") else None,
) for sea in group_seasons]
async def async_tmdb_episodes(self, tmdbid: int, season: int,
episode_group: Optional[str] = None) -> List[schemas.TmdbEpisode]:
"""
根据TMDBID查询某季的所有集信息异步版本
:param tmdbid: TMDBID
:param season: 季
:param episode_group: 剧集组
"""
if episode_group:
season_info = await self.tmdb.async_get_tv_group_detail(episode_group, season=season)
else:
season_info = await self.tmdb.async_get_tv_season_detail(tmdbid=tmdbid, season=season)
if not season_info or not season_info.get("episodes"):
return []
return [schemas.TmdbEpisode(**episode) for episode in season_info.get("episodes")]
async def async_tmdb_movie_similar(self, tmdbid: int) -> List[MediaInfo]:
"""
根据TMDBID查询类似电影异步版本
:param tmdbid: TMDBID
"""
similar = await self.tmdb.async_get_movie_similar(tmdbid=tmdbid)
if similar:
return [MediaInfo(tmdb_info=info) for info in similar]
return []
async def async_tmdb_tv_similar(self, tmdbid: int) -> List[MediaInfo]:
"""
根据TMDBID查询类似电视剧异步版本
:param tmdbid: TMDBID
"""
similar = await self.tmdb.async_get_tv_similar(tmdbid=tmdbid)
if similar:
return [MediaInfo(tmdb_info=info) for info in similar]
return []
async def async_tmdb_movie_recommend(self, tmdbid: int) -> List[MediaInfo]:
"""
根据TMDBID查询推荐电影异步版本
:param tmdbid: TMDBID
"""
recommend = await self.tmdb.async_get_movie_recommend(tmdbid=tmdbid)
if recommend:
return [MediaInfo(tmdb_info=info) for info in recommend]
return []
async def async_tmdb_tv_recommend(self, tmdbid: int) -> List[MediaInfo]:
"""
根据TMDBID查询推荐电视剧异步版本
:param tmdbid: TMDBID
"""
recommend = await self.tmdb.async_get_tv_recommend(tmdbid=tmdbid)
if recommend:
return [MediaInfo(tmdb_info=info) for info in recommend]
return []
async def async_tmdb_movie_credits(self, tmdbid: int, page: Optional[int] = 1) -> List[schemas.MediaPerson]:
"""
根据TMDBID查询电影演职员表异步版本
:param tmdbid: TMDBID
:param page: 页码
"""
credit_infos = await self.tmdb.async_get_movie_credits(tmdbid=tmdbid, page=page)
if credit_infos:
return [schemas.MediaPerson(source="themoviedb", **info) for info in credit_infos]
return []
async def async_tmdb_tv_credits(self, tmdbid: int, page: Optional[int] = 1) -> List[schemas.MediaPerson]:
"""
根据TMDBID查询电视剧演职员表异步版本
:param tmdbid: TMDBID
:param page: 页码
"""
credit_infos = await self.tmdb.async_get_tv_credits(tmdbid=tmdbid, page=page)
if credit_infos:
return [schemas.MediaPerson(source="themoviedb", **info) for info in credit_infos]
return []
async def async_tmdb_person_detail(self, person_id: int) -> schemas.MediaPerson:
"""
根据TMDBID查询人物详情异步版本
:param person_id: 人物ID
"""
detail = await self.tmdb.async_get_person_detail(person_id=person_id)
if detail:
return schemas.MediaPerson(source="themoviedb", **detail)
return schemas.MediaPerson()
async def async_tmdb_person_credits(self, person_id: int, page: Optional[int] = 1) -> List[MediaInfo]:
"""
根据TMDBID查询人物参演作品异步版本
:param person_id: 人物ID
:param page: 页码
"""
infos = await self.tmdb.async_get_person_credits(person_id=person_id, page=page)
if infos:
return [MediaInfo(tmdb_info=tmdbinfo) for tmdbinfo in infos]
return []
def clear_cache(self):
"""
清除缓存

View File

@@ -6,6 +6,7 @@ fastapi~=0.115.14
passlib~=1.7.4
PyJWT~=2.10.1
python-multipart~=0.0.9
aiofiles~=24.1.0
alembic~=1.16.2
bcrypt~=4.0.1
regex~=2024.11.6