Skip to main content

Postgres-based distributed task processing library

Project description

Procrastinate: PostgreSQL-based Task Queue for Python

Deployed to PyPI Deployed to PyPI GitHub Repository Continuous Integration Documentation Documentation Coverage badge MIT License Contributor Covenant Discord

Procrastinate is looking for additional maintainers!

Procrastinate is an open-source Python 3.8+ distributed task processing library, leveraging PostgreSQL to store task definitions, manage locks and dispatch tasks. It can be used within both sync and async code, has Django integration, and is easy to use with ASGI frameworks. It supports periodic tasks, retries, arbitrary task locks etc.

In other words, from your main code, you call specific functions (tasks) in a special way and instead of being run on the spot, they're scheduled to be run elsewhere, now or in the future.

Here's an example (if you want to run the code yourself, head to Quickstart):

# mycode.py
import procrastinate

# Make an app in your code
app = procrastinate.App(connector=procrastinate.SyncPsycopgConnector())

# Then define tasks
@app.task(queue="sums")
def sum(a, b):
    with open("myfile", "w") as f:
        f.write(str(a + b))

with app.open():
    # Launch a job
    sum.defer(a=3, b=5)

# Somewhere in your program, run a worker (actually, it's usually a
# different program than the one deferring jobs for execution)
app.run_worker(queues=["sums"])

The worker will run the job, which will create a text file named myfile with the result of the sum 3 + 5 (that's 8).

Similarly, from the command line:

export PROCRASTINATE_APP="mycode.app"

# Launch a job
procrastinate defer mycode.sum '{"a": 3, "b": 5}'

# Run a worker
procrastinate worker -q sums

Lastly, you can use Procrastinate asynchronously too (actually, it's the recommended way to use it):

import asyncio

import procrastinate

# Make an app in your code
app = procrastinate.App(connector=procrastinate.PsycopgConnector())

# Define tasks using coroutine functions
@app.task(queue="sums")
async def sum(a, b):
    await asyncio.sleep(a + b)

async with app.open_async():
    # Launch a job
    await sum.defer_async(a=3, b=5)

    # Somewhere in your program, run a worker (actually, it's often a
    # different program than the one deferring jobs for execution)
    await app.run_worker_async(queues=["sums"])

There are quite a few interesting features that Procrastinate adds to the mix. You can head to the Quickstart section for a general tour or to the How-To sections for specific features. The Discussion section should hopefully answer your questions. Otherwise, feel free to open an issue.

Note to my future self: add a quick note here on why this project is named "Procrastinate" ;) .

Where to go from here

The complete docs is probably the best place to learn about the project.

If you encounter a bug, or want to get in touch, you're always welcome to open a ticket.

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

procrastinate-2.0.0b3.tar.gz (69.5 kB view details)

Uploaded Source

Built Distribution

procrastinate-2.0.0b3-py3-none-any.whl (99.8 kB view details)

Uploaded Python 3

File details

Details for the file procrastinate-2.0.0b3.tar.gz.

File metadata

  • Download URL: procrastinate-2.0.0b3.tar.gz
  • Upload date:
  • Size: 69.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/4.0.2 CPython/3.11.8

File hashes

Hashes for procrastinate-2.0.0b3.tar.gz
Algorithm Hash digest
SHA256 95751d212f5b89522b4d1b72c9ac16b08272bd303834a12417941b08ca2fa110
MD5 c229a9497417c9f701a57a23c28fc0ca
BLAKE2b-256 1c53353af5efb5e1a7366a6d245aba995d1cbaec2cf327754de3a7ce814d5689

See more details on using hashes here.

File details

Details for the file procrastinate-2.0.0b3-py3-none-any.whl.

File metadata

File hashes

Hashes for procrastinate-2.0.0b3-py3-none-any.whl
Algorithm Hash digest
SHA256 2fd212861e43509a2843fb7ef50e2dd04ccf2b5e7d7913f93cf72aa23452594f
MD5 16432cbf86e581047e204aaa38fc2913
BLAKE2b-256 9592046aed6ea27f3d093c7276fbcaad966fe87cf82839fdf21b3b2c75405ead

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page