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Torrelque

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    Torrelque

Asynchronous Redis-backed reliable queue package


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Torrelque


Torrelque is a Python package that provides minimal asynchronous reliable distributed Redis-backed (or a protocol-compatible alternative) work queues. It is built:

  1. Lock-free. It relies on Redis transactions and its single-threaded execution model.
  2. Poll-free. Waiting subset of the Python API relies either on blocking Redis commands or notifications.
  3. Bulk-friendly. Tasks can be produced and consumed in bulk.
  4. Introspectable. Task stats, task status transition watching API, and the data model comprehensible directly in Redis.

Supported Redis server implementations: Redis, KeyDB.

Install

::

pip install Torrelque

Quickstart

Producer:

.. sourcecode:: python

import redis.asyncio import torrelque

client = redis.asyncio.Redis() queue = torrelque.Torrelque(client, queue='email') queue.schedule_sweep() # to make due requeued tasks available again

task_data = {'addr': 'joe@doe.com', 'subj': 'hello', 'body': '...'} task_id = await queue.enqueue(task_data) print('Email task enqueued', task_id)

Consumer:

.. sourcecode:: python

import redis.asyncio import torrelque

client = redis.asyncio.Redis() queue = torrelque.Torrelque(client, queue='email')

while True: task_id, task_data = await queue.dequeue() try: await some_email_client.send(**task_data) except Exception: print('Email sending error, retrying in 30s', task_id) await queue.requeue(task_id, delay=30) else: print('Email sent', task_id) await queue.release(task_id)

Example list

  • Producer-consumer <e1_>_. Infinite producing and consuming loops.
  • Batch processing <e2_>_. Finite number of tasks, consumers stop with a poison pill, bulk enqueue. This example can be used as a synthetic benchmark. Because there's no IO-bound workload, it'll be CPU-bound which isn't normal mode of operation for an asynchronous application. But it can be used to compare between CPython, PyPy and concurrency parameters.
  • Web application background task <e3_>_. This tornado application allows to start a task and push server-sent events (SSE) to UI about its status. UI starts a task and waits for it to complete. When a task fails it's re-queued with exponential back-off.

.. _e1: https://heptapod.host/saajns/torrelque/blob/branch/default/example/producer_consumer.py .. _e2: https://heptapod.host/saajns/torrelque/blob/branch/default/example/batch_processing.py .. _e3: https://heptapod.host/saajns/torrelque/blob/branch/default/example/wait_until_complete.py

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