{
    "info": {
        "author": "Matt Croydon, Mikhail Korobov",
        "author_email": "mcroydon@gmail.com, kmike84@gmail.com",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 4 - Beta",
            "Environment :: Web Environment",
            "Framework :: Django",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: MIT License",
            "Programming Language :: Python",
            "Programming Language :: Python :: 2",
            "Programming Language :: Python :: 2.5",
            "Programming Language :: Python :: 2.6",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.4",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
            "Topic :: Software Development :: Libraries :: Python Modules"
        ],
        "description": "====================================================\ndjango-qsstats-magic: QuerySet statistics for Django\n====================================================\n\nThe goal of django-qsstats is to be a microframework to make\nrepetitive tasks such as generating aggregate statistics of querysets\nover time easier.  It's probably overkill for the task at hand, but yay\nmicroframeworks!\n\ndjango-qsstats-magic is a refactoring of django-qsstats app with slightly\nchanged API, simplified internals and faster time_series implementation.\n\n\nRequirements\n============\n\n* `python-dateutil <http://labix.org/python-dateutil>`_ > 1.4, < 2.0\n* `django <http://www.djangoproject.com/>`_ 1.2+\n\nLicense\n=======\n\nLiensed under a BSD-style license.\n\nExamples\n========\n\nHow many users signed up today? this month? this year?\n------------------------------------------------------\n\n::\n\n    from django.contrib.auth.models import User\n    import qsstats\n\n    qs = User.objects.all()\n    qss = qsstats.QuerySetStats(qs, 'date_joined')\n\n    print '%s new accounts today.' % qss.this_day()\n    print '%s new accounts this week.' % qss.this_week()\n    print '%s new accounts this month.' % qss.this_month()\n    print '%s new accounts this year.' % qss.this_year()\n    print '%s new accounts until now.' % qss.until_now()\n\nThis might print something like::\n\n    5 new accounts today.\n    11 new accounts this week.\n    27 new accounts this month.\n    377 new accounts this year.\n    409 new accounts until now.\n\nAggregating time-series data suitable for graphing\n--------------------------------------------------\n\n::\n\n    from django.contrib.auth.models import User\n    import datetime, qsstats\n\n    qs = User.objects.all()\n    qss = qsstats.QuerySetStats(qs, 'date_joined')\n\n    today = datetime.date.today()\n    seven_days_ago = today - datetime.timedelta(days=7)\n\n    time_series = qss.time_series(seven_days_ago, today)\n    print 'New users in the last 7 days: %s' % [t[1] for t in time_series]\n\nThis might print something like::\n\n    New users in the last 7 days: [3, 10, 7, 4, 12, 9, 11]\n\n\nPlease see qsstats/tests.py for similar usage examples.\n\nAPI\n===\n\nThe ``QuerySetStats`` object\n----------------------------\n\nIn order to provide maximum flexibility, the ``QuerySetStats`` object\ncan be instantiated with as little or as much information as you like.\nAll keword arguments are optional but ``DateFieldMissing`` and\n``QuerySetMissing`` will be raised if you try to use ``QuerySetStats``\nwithout providing enough information.\n\n``qs``\n    The queryset to operate on.\n\n    Default: ``None``\n\n``date_field``\n    The date field within the queryset to use.\n\n    Default: ``None``\n\n``aggregate``\n    The django aggregation instance. Can be set also set when\n    instantiating or calling one of the methods.\n\n    Default: ``Count('id')``\n\n``operator``\n    The default operator to use for the ``pivot`` function.  Can be also set\n    when calling ``pivot``.\n\n    Default: ``'lte'``\n\n``today``\n    The date that will be considered as today date. If ``today`` param is None\n    QuerySetStats' today will be datetime.date.today().\n\n    Default: ``None``\n\n\nAll of the documented methods take a standard set of keyword arguments\nthat override any information already stored within the ``QuerySetStats``\nobject.  These keyword arguments are ``date_field`` and ``aggregate``.\n\nOnce you have a ``QuerySetStats`` object instantiated, you can receive a\nsingle aggregate result by using the following methods:\n\n* ``for_minute``\n* ``for_hour``\n* ``for_day``\n* ``for_week``\n* ``for_month``\n* ``for_year``\n\n    Positional arguments: ``dt``, a ``datetime.datetime`` or ``datetime.date``\n    object to filter the queryset to this interval (minute, hour, day, week,\n    month or year).\n\n* ``this_minute``\n* ``this_hour``\n* ``this_day``\n* ``this_week``\n* ``this_month``\n* ``this_year``\n\n    Wrappers around ``for_<interval>`` that uses ``dateutil.relativedelta`` to\n    provide aggregate information for this current interval.\n\n``QuerySetStats`` also provides a method for returning aggregated\ntime-series data which may be extremely using in plotting data:\n\n``time_series``\n    Positional arguments: ``start`` and ``end``, each a\n    ``datetime.date`` or ``datetime.datetime`` object used in marking\n    the start and stop of the time series data.\n\n    Keyword arguments: In addition to the standard ``date_field`` and\n    ``aggregate`` keyword argument, ``time_series`` takes an optional\n    ``interval`` keyword argument used to mark which interval to use while\n    calculating aggregate data between ``start`` and ``end``.  This argument\n    defaults to ``'days'`` and can accept ``'years'``, ``'months'``,\n    ``'weeks'``, ``'days'``, ``'hours'`` or ``'minutes'``.\n    It will raise ``InvalidInterval`` otherwise.\n\n    This methods returns a list of tuples.  The first item in each\n    tuple is a ``datetime.datetime`` object for the current inverval.  The\n    second item is the result of the aggregate operation.  For\n    example::\n\n        [(datetime.datetime(2010, 3, 28, 0, 0), 12), (datetime.datetime(2010, 3, 29, 0, 0), 0), ...]\n\n    Formatting of date information is left as an exercise to the user and may\n    vary depending on interval used.\n\n``until``\n    Provide aggregate information until a given date or time, filtering the\n    queryset using ``lte``.\n\n    Positional arguments: ``dt`` a ``datetime.date`` or ``datetime.datetime``\n    object to be used for filtering the queryset since.\n\n    Keyword arguments: ``date_field``, ``aggregate``.\n\n``until_now``\n    Aggregate information until now.\n\n    Positional arguments: ``dt`` a ``datetime.date`` or ``datetime.datetime``\n    object to be used for filtering the queryset since (using ``lte``).\n\n    Keyword arguments: ``date_field``, ``aggregate``.\n\n``after``\n    Aggregate information after a given date or time, filtering the queryset\n    using ``gte``.\n\n    Positional arguments: ``dt`` a ``datetime.date`` or ``datetime.datetime``\n    object to be used for filtering the queryset since.\n\n    Keyword arguments: ``date_field``, ``aggregate``.\n\n``after_now``\n    Aggregate information after now.\n\n    Positional arguments: ``dt`` a ``datetime.date`` or ``datetime.datetime``\n    object to be used for filtering the queryset since (using ``gte``).\n\n    Keyword arguments: ``date_field``, ``aggregate``.\n\n``pivot``\n    Used by ``since``, ``after``, and ``until_now`` but potentially useful if\n    you would like to specify your own operator instead of the defaults.\n\n    Positional arguments: ``dt`` a ``datetime.date`` or ``datetime.datetime``\n    object to be used for filtering the queryset since (using ``lte``).\n\n    Keyword arguments: ``operator``, ``date_field``, ``aggregate``.\n\n    Raises ``InvalidOperator`` if the operator provided is not one of ``'lt'``,\n    ``'lte'``, ``gt`` or ``gte``.\n\nTesting\n=======\n\nIf you'd like to test ``django-qsstats-magic`` against your local configuration, add\n``qsstats`` to your ``INSTALLED_APPS`` and run ``./manage.py test qsstats``.\nThe test suite assumes that ``django.contrib.auth`` is installed.\n\nFor testing against different python, DB and django versions install tox\n(pip install tox) and run 'tox' from the source checkout::\n\n    $ tox\n\nDb user 'qsstats_test' with password 'qsstats_test' and a DB 'qsstats_test'\nshould exist.\n\nDifference from django-qsstats\n==============================\n\n1. Faster time_series method using 1 sql query (currently works for MySQL and\n   PostgreSQL, with a fallback to the old method for other DB backends).\n2. Single ``aggregate`` parameter instead of ``aggregate_field`` and\n   ``aggregate_class``. Default value is always ``Count('id')`` and can't be\n   specified in settings.py. ``QUERYSETSTATS_DEFAULT_OPERATOR`` option is also\n   unsupported now.\n3. Support for minute and hour aggregates.\n4. ``start_date`` and ``end_date`` arguments are renamed to ``start`` and\n   ``end`` because of 3.\n5. Internals are changed.\n\nI don't know if original author (Matt Croydon) would like my changes so\nI renamed a project for now. If the changes will be merged then\ndjango-qsstats-magic will become obsolete.",
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        "summary": "A django microframework that eases the generation of aggregate data for querysets.",
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