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    "info": {
        "author": "Andr\u00e9s Bucchi",
        "author_email": "afbucchi@gmail.com",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 2 - Pre-Alpha",
            "Framework :: Django",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: BSD License",
            "Natural Language :: English",
            "Programming Language :: Python :: 2",
            "Programming Language :: Python :: 2.6",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.3"
        ],
        "description": "=============================\ndjango-cacheq\n=============================\n\nBackground tasks using django's cache framework.\n\n\nQuickstart\n----------\n\nInstall django-cacheq::\n\n    pip install django-cacheq\n\nRequirements\n\n- django>=1.5.1\n- jsonfield>=1.0.3\n- lockfile>=0.10.2\n\nAdd it to your installed apps::\n\n    INSTALLED_APPS = (\n        ...\n        'cacheq',\n    )\n\nAnd that's it with setup. You can add some basic settings too, but they are not really required.::\n    \n    CACHES = {\n        'default: ...,\n        'cacheq': ...,\n        'other': ...\n    }\n    \n    CACHEQ = {\n        'CACHE': 'cacheq',                      # which cache to use, defaults to 'default'\n                                                # note that dummybackend is *not* supported\n        'LOCKFILE': '/var/tmp/mycacheq.lock',   # lock file to use if cache is filebased, \n                                                # defaults to '/var/tmp/cacheq.lock'\n        # these settings are only for testing\n        'MEMCACHED_TESTS_USING': 'memcached',   # which cache to use for running memcached \n                                                # backend tests, only for development\n        'REDIS_TESTS_USING': 'redis',           # which cache to use for running redis \n                                                # backend tests, only for development\n    }\n\nThen use it in your project::\n\n    import operator\n    from cacheq import CacheQ\n    \n    cq = CacheQ(name='myqueue', using='cacheq') # as in get_cache('cacheq')\n    \n    # either enqueue one job\n    job = cq.enqueue(operator.add, 1, 2)\n    \n    # or several at a time. note that both the args=[...] and kwargs={...}\n    # arguments are required in this case, even if empty\n    tasks = [(operator.add, [1,2], {}), (operator.div, [], {'a': 2, 'b': 2})]\n    job = cq.enqueue_many(tasks) # job with many tasks\n    \n    # or you can use the @cq.job decorator\n    @cq.job\n    def myfunc(a,b):\n        return a+b\n    \n    job = myfunc.delay(1,b=2)\n    \n    # then wait for results\n    job.ready() # False\n    job.ready() # True\n    job.result # 3\n    \n    # calling job.ready() or job.result will not hit the database\n    # it will look for result and status in cache. once it's ready \n    # it will update job in database.\n\nRunning the worker::\n\n    python manage.py cqworker --using=cacheq --queue=myqueue --name=worker123 --pulse=0.1\n\nThis will run a cqworker with name \"worker123\" in foreground listening to queue \"myqueue\" using the cache backend under get_cache('cacheq'). The 'pulse' option is not really necessary, but it will accept any value between 0.0 and 1.0, which will be the time that the worker will wait to look for a new job again. I don't know if this is really helpful, as it would still be only one connection to memcached / redis, and time.sleep is blocking.\n\nThese are the default values\n\n- using: 'default'\n- queue: 'default'\n- name: 'worker'\n- pulse: 1.0\n\nWhen running tests it's helpful to run the worker and exit when jobs are done. You can do this by either calling the cqworker command with the --burst option or by using the worker.run method.::\n\n    python manage.py cqworker --using=cacheq --queue=myqueue --burst\n    \n    # or programatically\n    from cacheq import get_worker\n    \n    worker = get_worker(queue_name='myqueue', using='cacheq')\n    worker.run(burst=True)\n\n\ndjango-cacheq uses django ORM as a backend for job results. This is only something that fitted specific needs I had at the time I wrote this package, but I guess it would be wise to remove it at some point and replace it by a cache backend too, or maybe adding a setting that allows other database to be used specifically as a results backend.\n\nAnyways, for now you can clear jobs by using the cqclear command::\n\n    python manage.py cqclear <done failed pending all> [--no-input]\n    \nIn the case you want to delete pending jobs, you will have to confirm the action if you do not provide the --no-input option. So have this in mind if you wish to use a cronjob to clear jobs periodically.\n\n\n\n\n\nHistory\n-------\n\n0.1.0 (2015-07-25)\n++++++++++++++++++\n\n* First release on PyPI.",
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        "summary": "Background tasks using django's cache framework.",
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