Skip to main content


Project description

This is a small wrapper around SQS that provides some testing support and and some abstraction over the boto SQS APIs.

There are 2 basic parts, a producer API and a worker API.

Note that these APIs don’t let you pass AWS credentials. This means that you must either pass credentials through ~/.boto configuration, through environment variables, or through temporary credentials provided via EC2 instance roles.

Producing jobs

To send work to workers, instantiate a Queue:

>>> import zc.sqs
>>> queue = zc.sqs.Queue("myqueue")
Connected to region us-east-1.

The SQS queue must already exist. Creating queues is outside the scope of these APIs. Trying to create a Queue instance with a nonexistent queue name will result in an exception being raised.

>>> import mock
>>> with mock.patch("boto.sqs.connect_to_region") as conn:
...     conn().get_queue.return_value = None
...     zc.sqs.Queue("nonexistent") # doctest: +IGNORE_EXCEPTION_DETAIL
Traceback (most recent call last):
NonExistentQueue: nonexistent

To place data in the queue, you call it. You can pass positional, and/or keyword arguments.

>>> queue(1, 2, x=3)
[[1, 2], {'x': 3}]

In this example, we’re running in test mode. In test mode, data are simply echoed back (unless we wire up a worker, as will be discussed below).

Arguments must be json encodable.


Workers are provided as factories that accept configuration data and return callables that are called with queued messages. A worker factory could be implemented with a class that has __init__ and __call__ methods, or with a function that takes configuration data and returns a nested function to handle messages.

Normally, workers don’t return anything. If the input is bad, the worker should raise an exception. The exception will be logged, as will the input data. If the input is good, but the worker can’t perform the request, it should raise zc.sqs.TransientError to indicate that the work should be retried later.


To attach your workers to queues, you use a container, which is just a program that polls an SQS queue and calls your worker. There are currently 2 containers:


The sequential container pulls requests from an SQS queue and hands them to a worker, one at a time.

This is a script entry point and accepts an argument list, containing the path to an ini file. It uses “long polling” to loop efficiently.


The test container is used for writing tests. It supports integration tests of producer and worker code. When running in test mode, it replaces (part of) the sequential container.

The sequential entry point takes the name of an ini file with 2 sections:


The container section configures the container with options:

worker MODULE:expr

The worker constructor


The name of an sqs queue to listen to.


A ZConfig-based logger configuration string.

worker (optional)

Worker options, passed to the worker constructor as a dictionary.

If not provided, an empty dictionary will be passed.

Here’s a simple (pointless) example to illustrate how this is wired up. First, we’ll define a worker factory:

def scaled_addr(config):
    scale = float(config.get('scale', 1))

    def add(a, b, x):
        if x == 'later':
            print ("not now")
            raise zc.sqs.TransientError # Not very imaginative, I know
        print (scale * (a + b + x))

    return add

Now, we’ll define a container configuration:

worker = zc.sqs.tests:scaled_addr
queue = adder
loggers =
     level INFO
       path STDOUT
       format %(levelname)s %(name)s %(message)s
     level INFO
     propagate false
     name zc.sqs.messages
       path messages.log
       format %(message)s

scale = 2

Now, we’ll run the container.

>>> import zc.thread
>>> @zc.thread.Thread
... def thread():
...     zc.sqs.sequential(['ini'])

We ran the container in a thread because it runs forever and wouldn’t return.

Normally, the entry point would run forever, but since we’re running in test mode, the container just wires the worker up to the test environment.

Now, if we create a queue (in test mode):

>>> adder = zc.sqs.Queue("adder")
Connected to region us-east-1.

and send it work:

>>> adder(1, 2, 3)
deleted '[[1, 2, 3], {}]'

We see that the worker ran.

We also see a testing message showing that the test succeeded.

If a worker can’t perform an action immediately, it indicates that the message should be delayed by raising TransientError as shown in the worker example above:

>>> adder(1, 2, 'later')
not now

In this case, since the worker raised TransientError, the message wasn’t deleted from the queue. This means that it’ll be handled later when the job times out.

If the worker rasies an exception, the exception and the message are logged:

>>> adder(1, 2, '') # doctest: +ELLIPSIS
ERROR zc.sqs Handling a message
Traceback (most recent call last):
TypeError: unsupported operand type(s) for +: 'int' and '...'
deleted '[[1, 2, ""], {}]'
>>> with open("messages.log") as f:
...     print(
[[1, 2, ""], {}]

Silencing tests

Sometimes, you don’t want the testing infrastructure to output information when sending messages. There testing setUp method adds an sqs_queues attribute to globals. You can call be_silent to make it stop outputting infomation:

>>> sqs_queues.be_silent()

After calling this, any subsequent queues will be quiet:

>>> queue = zc.sqs.Queue("quiet")
>>> queue(1)

You can get the queued data:

>>> [m.get_body() for m in sqs_queues.get_queue("quiet").get_messages()]
['[[1], {}]']

You can switch back to being noisy:

>>> sqs_queues.be_silent()
>>> queue = zc.sqs.Queue("loud")
>>> queue(1)



  • Python 3 support.

0.3.0 (2014-10-17)

  • Use long polling instead of a configurable polling interval.

0.2.1 (2013-05-15)

  • Better error handling when SQS queues don’t exist.

0.2.0 (2013-05-15)

  • A new silent mode for test queues.

0.1.0 (2013-04-23)

Initial release.

Project details

Download files

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

Source Distribution

zc.sqs-1.0.0.tar.gz (8.1 kB view hashes)

Uploaded Source

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