{
    "info": {
        "author": "Bruno Reni\u00e9",
        "author_email": "bruno@renie.fr",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 4 - Beta",
            "Environment :: Web Environment",
            "Intended Audience :: Developers",
            "Natural Language :: English",
            "Programming Language :: Python",
            "Programming Language :: Python :: 2",
            "Programming Language :: Python :: 2.6",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.2",
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        "description": "RACHE\n=====\n\n.. image:: https://travis-ci.org/brutasse/rache.png?branch=master\n   :alt: Build Status\n   :target: https://travis-ci.org/brutasse/rache\n\nA scheduler backed by `Redis`_ with a very simple interface.\n\n.. _Redis: http://redis.io/\n\nRACHE doesn't handle job execution. It only maintains a list of jobs and their\ntheoretical execution time. It's up to you to monitor pending jobs and send\nthem to an actual task queue.\n\nInstallation\n------------\n\nRACHE works with any Python version from 2.6 to 3.3. You only need a working\nRedis server.\n\n::\n\n    pip install rache\n\nConfiguration\n-------------\n\nBy default RACHE connects to Redis on localhost, port 6379, database 0. To\noverride this, set a ``REDIS_URL`` environment variable::\n\n    REDIS_URL=redis://redis.example.com:6379/2\n\nRACHE prefixes all its Redis keys with ``rache:``. You can override this by\nsetting the ``RACHE_REDIS_PREFIX`` environment variable.\n\nUsage\n-----\n\n::\n\n    import rq\n\n    from rache import schedule_job, pending_jobs\n\n    # Schedule a job now\n    schedule_job('http://github.com/brutasse/rache', schedule_in=0, timeout=10)\n\n    # Get pending jobs\n    jobs = pending_jobs()\n\n    # Send them to the task queue for immediate execution\n    for job in jobs:\n        rq.enqueue_job(...)\n\n``schedule_job``\n````````````````\n\n::\n\n    schedule_job('job id', schedule_in=<seconds>, connection=None, **kwargs)\n\nA given job ID is unique from the scheduler perspective. Scheduling it twice\nresults in it being scheduled at the time decided in the last call.\n\n``**kwargs`` can be used to attach data to your jobs. For instance, if you\nhave jobs to fetch URLs and want to attach a timeout to these jobs::\n\n    schedule_job('http://example.com/test', schedule_in=3600, timeout=10)\n\nThe job data is persistent. To remove a key from the data, call\n``schedule_job()`` with that key set to None::\n\n    schedule_job('http://example.com/test', schedule_in=3600, timeout=None)\n\n``schedule_in`` is mandatory. This means you can't update an existing job\nwithout rescheduling it.\n\n``connection`` allows you to pass a custom Redis connection object. This is\nuseful if you have your own connection pooling and want to manage connections\nyourself.\n\n``pending_jobs``\n````````````````\n\n::\n\n    jobs = pending_jobs(reschedule_in=None, limit=None, connection=None)\n\n(the returned value is a generator)\n\nFetches the pending jobs and returns a list of jobs. Each job is a dictionnary\nwith an ``id`` key and its additional data.\n\n``reschedule_in`` controls whether to auto-reschedule jobs in a given time.\nThis is useful if you have periodic jobs but also want to special-case some\njobs according to their results (``enqueue`` is `rq`_-style syntax)::\n\n    jobs = pending_jobs(reschedule_in=3600)\n\n    for job in jobs:\n        enqueue(do_something, kwargs=job)\n\n    def do_something(**kwargs):\n        # \u2026 do some work\n\n        if some_condition:\n            # re-schedule in 30 days\n            schedule_job(kwargs['id'], schedule_in=3600 * 24 * 30)\n\n.. _rq: http://python-rq.org/\n\n``limit`` allows you to limit the number of jobs returned. Remaining jobs are\nleft on schedule, even if they should have been scheduled right now.\n\n``connection`` allows you to pass a custom Redis connection object.\n\n``delete_job``\n``````````````\n\n::\n\n    delete_job('<job id>', connection=None)\n\nRemoves a job completely from the scheduler.\n\n``connection`` allows you to pass a custom Redis connection object.\n\n``job_details``\n```````````````\n\n::\n\n    job_details('<job id>', connection=None)\n\nReturns a dictionnary with the job data. The job ID and scheduled time are\nset in the ``id`` and ``schedule_at`` keys of the returned value.\n\n``connection`` allows you to pass a custom Redis connection object.\n\n``scheduled_jobs``\n``````````````````\n\n::\n\n    scheduled_jobs(with_times=False, connection=None)\n\n(the returned value is a generator)\n\nFetches all the job IDs stored in the scheduler. This returns a list of IDs or\na list of ``(job_id, timestamp)`` tuples if ``with_times`` is set to ``True``.\n\nThis is useful for syncing jobs between the scheduler and a database, for\ninstance.\n\n``connection`` allows you to pass a custom Redis connection object.\n\nContributing\n------------\n\nCreate a local environment::\n\n    virtualen env\n    source env/bin/activate\n    pip install -e .\n\nRun the tests::\n\n    python setup.py test\n\nOr for all supported python versions::\n\n    tox\n\nHack, fix bugs and submit pull requests!\n\nChangelog\n---------\n\n* **0.3.1** (2013-08-31):\n\n  * Made ``pending_jobs`` work correctly with both ``Redis`` and\n    ``StrictRedis`` clients.\n\n* **0.3** (2013-08-31):\n\n  * Allow passing custom Redis connection objects for fine control on open\n    connections.\n\n* **0.2.2** (2013-07-10):\n\n  * Fixed a typo that lead to ``AttributeError`` when retrieving some jobs.\n\n* **0.2.1** (2013-07-03):\n\n  * Allowed ``pending_jobs()`` to return non-unicode data if undecodable bytes\n    are passed to ``schedule_job()``.\n\n* **0.2** (2013-06-02):\n\n  * Added ``limit`` kwarg to ``pending_jobs()``.\n  * Allowed ``schedule_in`` to be a timedelta alternatively to a number of\n    seconds.\n  * Added ``job_details()``.\n  * Numerical data attached to jobs is cast to ``int()`` when returned.\n\n* **0.1** (2013-06-01):\n\n  * Initial release",
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