Distributed async locks in Python, similar to https://github.com/vaidik/sherlock
Project description
Distributed async locks on Python
What is this?
Locks are required when you have a distributed system (like any API) and you want to ensure consistency for your data and prevent race conditions. There are a lot of ways to implement them, and this library aims to provide easy access to some of the better ways.
The library is written purely for use with asyncio code for now.
Supports MongoDB (using unique indexes + ttl indexes for consistency and safety) for now, can be extended for other storage systems pretty easily.
License
Licensing is important. This project itself uses BSD 3-clause license, but e.g. Mongodb Motor library and other such libraries used by it may have their own licenses.
For more information check the LICENSE -file.
Getting started
Add shylock to your project via pip / pipenv / poetry
pip install shylock[motor]
For most easy usage, you should in your application startup logic configure the default backend for Shylock to use, and then use the Lock class to handle your locking needs.
from motor.motor_asyncio import AsyncIOMotorClient
from shylock import configure, Lock, ShylockMotorAsyncIOBackend
CONNECTION_STRING = "mongodb://your-connection-string"
client = AsyncIOMotorClient(CONNECTION_STRING)
configure(ShylockMotorAsyncIOBackend(client, "projectdb"))
async def use_lock():
with Lock("my-lock"):
# The lock is now acquired, and will be automatically released
do_something()
async def another_lock_use():
lock = Lock("my-lock")
try:
lock.acquire()
do_something()
finally:
lock.release()
async def time_sensitive_code():
lock = Lock("my-lock")
try:
locked = lock.acquire(block=False)
if locked:
do_something()
finally:
if locked:
lock.release()
You can also check out the example.
Contributing
This project is run on GitHub using the issue tracking and pull requests here. If you want to contribute, feel free to submit issues (incl. feature requests) or PRs here.
To test changes locally python setup.py develop is a good way to run this, and you can python setup.py develop --uninstall afterwards (you might want to also use the --user flag).
Project details
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