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Project description
aiorezka
Installation
Without cache
pip install aiorezka
With cache
It's recommended to use cache, because it will reduce load on Rezka API.
pip install aiorezka[request_cache]
Usage
from aiorezka.api import RezkaAPI
import asyncio
async def main():
async with RezkaAPI() as api:
details = await api.movie_detail.get(
'https://rezka.ag/cartoons/comedy/2136-rik-i-morti-2013.html'
)
print(details)
asyncio.run(main())
You can find more examples in examples directory.
Download TV series
pip install yt-dlp
- Install downloader extras for
aiorezka:
pip install aiorezka[downloader]
- Run download process:
python -m aiorezka -u https://rezka.ag/cartoons/comedy/2136-rik-i-morti-2013-latest.html -a Сыендук -s 1
Aiorezka CLI
options:
-h, --help show this help message and exit
-v, --version show program's version number and exit
-u URL, --url URL URL of the movie or TV series to download. Can be full
URL or just urn (e.g. /films/series/12345.html)
-p PATH, --path PATH Path to save downloaded files (default: current
directory)
-s SEASON, --season SEASON
Season number for TV series (default: 1)
-a AUDIO_TRACK, --audio-track AUDIO_TRACK
Preferred audio track for TV series
Configuration
Hostname configuration
You can configure hostname for requests. By default it will use rezka.ag hostname.
To change it, you can pass environment variable REZKA_HOSTNAME or change it in code:
import aiorezka
aiorezka.host = 'rezka.co'
Concurrency configuration
You can configure concurrency for API client, basically it will limit number of concurrent requests via asyncio.Semaphore.
By default it will use 60 concurrent requests.
To change it, you can pass environment variable REZKA_CONCURRENCY_LIMIT or change it in code:
import aiorezka
aiorezka.concurrency_limit = 100
Retry configuration
You can configure retry policy for requests. By default it will retry 3 times with 1 * (backoff ** retry_no) second delay.
To change it, you can pass environment variables, such as REZKA_MAX_RETRY and REZKA_RETRY_DELAY or change it in code:
import aiorezka
aiorezka.max_retry = 5
aiorezka.retry_delay = 2
Cache configuration
You can configure cache for requests. By default, it will use aiorezka.cache.QueryCache + aiorezka.cache.DiskCacheThreadProvider with 1 day TTL.
Cache will periodically save to disk, so you can use it between restarts.
use_cache
Enable or disable cache. By default, it's disabled.
import aiorezka
aiorezka.use_cache = False # disable cache
or use environment variable REZKA_USE_CACHE
cache_directory
Directory where cache will be stored. By default, it's /tmp/aiorezka_cache.
import aiorezka
aiorezka.cache_directory = '/tmp/aiorezka_cache'
or use environment variable REZKA_CACHE_DIRECTORY
memcache_max_len
Max number of items in memory cache. When it's reached, it will be saved to disk.
By default, it's 1000.
import aiorezka
aiorezka.memcache_max_len = 1000
or use environment variable REZKA_MEMCACHE_MAX_LEN
cache_ttl
TTL for cache objects.
By default, it's 1 day.
import aiorezka
aiorezka.cache_ttl = 60 * 60 * 24 # 1 day
or use environment variable REZKA_CACHE_TTL
max_open_files
Max number of open files for cache. It's used for aiorezka.cache.DiskCacheThreadProvider. When app starts cache will be rebuilt on disk, so it will open a lot of files to check if they are expired.
By default, it's 5000.
import aiorezka
aiorezka.max_open_files = 5000
or use environment variable REZKA_MAX_OPEN_FILES
You can disable cache rebuild on start, then TTL will be ignored.
from aiorezka.api import RezkaAPI
async def main():
async with RezkaAPI(cache_rebuild_on_start=False) as api:
pass
Logging configuration
You can configure logging for aiorezka. By default, it will use logging.INFO level.
import aiorezka
aiorezka.log_level = "DEBUG"
or use environment variable REZKA_LOG_LEVEL
Debugging
Measure RPS
Measure requests per second, use it only for debug purposes.
import asyncio
from aiorezka.api import RezkaAPI
from aiorezka.cli import measure_rps
@measure_rps
async def main():
async with RezkaAPI() as api:
movies = await api.movie.iter_pages(range(1, 10), chain=True)
detailed_movies = await api.movie_detail.many(movies)
for movie in detailed_movies:
attributes = '\n'.join([f'{attr["key"]}: {attr["value"]}' for attr in movie.attributes])
print(f'{movie.title}\n{attributes}\n')
if __name__ == '__main__':
asyncio.run(main())
Output will look like:
[main][333 requests in 37.82s] 8.81 rps
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