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A queue using mongo as backend storage.

Project description


  • Isolation

    Do not let different consumers process the same message.

  • Reliablity

    Do not let a failed consumer disappear an item.

  • Atomic

    Operations on the queue are atomic.


A queue can be instantiated with a mongo collection and a consumer identifier. The consumer identifier helps distinguish multiple queue consumers that are taking jobs from the queue:

>> from pymongo import Connection
>> from mongoqueue import MongoQueue
>> queue = MongoQueue(
...   Connection(TEST_DB).doctest_queue,
...   consumer_id="consumer-1",
...   timeout=300,
...   max_attempts=3)

The MongoQueue class timeout parameters specifies how long in a seconds a how long a job may be held by a consumer before its considered failed.

A job which timeouts or errors more than the max_attempts parameter is considered permanently failed, and will no longer be processed.

New jobs/items can be placed in the queue by passing a dictionary:

>> queue.put({"foobar": 1})

A job priority key and integer value can be specified in the dictionary which will cause the job to be processed before lower priority items:

>> queue.put({"foobar": 0}, priority=1})

An item can be fetched out by calling the next method on a queue. This returns a Job object:

>> job =
>> job.payload
{"foobar": 1}

The job class exposes some control methods on the job, for marking progress, completion, errors, or releasing the job back into the queue.

  • complete Marks a job as complete and removes it from the queue.

  • error Optionally specified with a message, releases the job back to the

    queue, and increments its attempts, and stores the error message on the job.

  • progress Optionally takes a progress count integer, notes progress on the job

    and resets the lock timeout.

  • release Release a job back to the pool. The attempts counter is not modified.

As a convience the job supports the context manager protocol:

>> with job as data:
...   print data['payload']

{"foobar: 0}

If the context closure is exited without the job is marked complete, if there’s an exception the error is stored on the job.

Inspired By

Running Tests

Unit tests can be run with

$ python nosetests


0.6.0 - Feb 4th, 2013 - Isolate passed in data from metadata in Job. 0.5.2 - Dec 9th, 2012 - Fix for regression in sort parameters from pymongo 2.4 0.5.1 - Dec 2nd, 2012 - Packaging fix for readme data file.


Kapil Thangavelu, author & maintainer Dustin Laurence, sort fix for pymongo 2.4 Jonathan Sackett, Job data isolation.

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