A reliable distributed scheduler with pluggable storage backends for Async Python.
Minimal installation (just SQLite persistence):
::
pip install pyncette
Full installation (all the backends and Prometheus metrics exporter):
::
pip install pyncette[all]
You can also install the in-development version with::
pip install https://github.com/tibordp/pyncette/archive/master.zip
https://pyncette.readthedocs.io
Simple in-memory scheduler (does not persist state)
.. code:: python
from pyncette import Pyncette, Context
app = Pyncette()
@app.task(schedule='* * * * *')
async def foo(context: Context):
print('This will run every minute')
if __name__ == '__main__':
app.main()
Persistent distributed cron using Redis (coordinates execution with parallel instances and survives restarts)
.. code:: python
from pyncette import Pyncette, Context
from pyncette.redis import redis_repository
app = Pyncette(repository_factory=redis_repository, redis_url='redis://localhost')
@app.task(schedule='* * * * * */10')
async def foo(context: Context):
print('This will run every 10 seconds')
if __name__ == '__main__':
app.main()
See the examples directory for more examples of usage.
Pyncette is designed for reliable (at-least-once or at-most-once) execution of recurring tasks (think cronjobs) whose lifecycles are managed dynamically, but can work effectively for non-reccuring tasks too.
Example use cases:
Pyncette might not be a good fit if:
Pyncette comes with an implementation for the following backends (used for persistence and coordination) out-of-the-box:
pip install pyncette[redis])pip install pyncette[postgres])pip install pyncette[mysql])pip install pyncette[dynamodb])Pyncette imposes few requirements on the underlying datastores, so it can be extended to support other databases or custom storage formats / integrations with existing systems. For best results, the backend needs to provide:
To run integration tests you will need Redis, PostgreSQL, MySQL and Localstack (for DynamoDB) running locally.
To run the all tests run::
tox
Alternatively, there is a Docker Compose environment that will set up all the backends so that integration tests can run seamlessly::
docker-compose up -d
docker-compose run --rm shell
tox
To run just the unit tests (excluding integration tests)::
tox -e py310 # or your Python version of choice
Note, to combine the coverage data from all the tox environments run:
.. list-table:: :widths: 10 90 :stub-columns: 1
- - Windows
- ::
set PYTEST_ADDOPTS=--cov-append
tox
- - Other
- ::
PYTEST_ADDOPTS=--cov-append tox
add_to_context() to inject static data to contextInMemoryRepository)poll_interval before next tick instead of the full amountcontext.args['name'] instead of context.nameFAQs
A reliable distributed scheduler with pluggable storage backends
We found that pyncette demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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