django-qsstats-magic

==================================================== django-qsstats-magic: QuerySet statistics for Django

The goal of django-qsstats is to be a microframework to make repetitive tasks such as generating aggregate statistics of querysets over time easier. It's probably overkill for the task at hand, but yay microframeworks!

django-qsstats-magic is a refactoring of django-qsstats app with slightly changed API, simplified internals and faster time_series implementation.

Requirements

• python-dateutil <http://labix.org/python-dateutil>_ > 1.4, < 2.0
• django <http://www.djangoproject.com/>_ 1.8+

Database

If timezone support is enabled in Django, the database must have also timezone support installed. For MySQL it might be needed to run:

::

• mysql_tzinfo_to_sql /usr/share/zoneinfo | mysql -u root mysql

License

Liensed under a BSD-style license.

Examples

How many users signed up today? this month? this year?

::

from django.contrib.auth.models import User
import qsstats

qs = User.objects.all()
qss = qsstats.QuerySetStats(qs, 'date_joined')

print '%s new accounts today.' % qss.this_day()
print '%s new accounts this week.' % qss.this_week()
print '%s new accounts this month.' % qss.this_month()
print '%s new accounts this year.' % qss.this_year()
print '%s new accounts until now.' % qss.until_now()

This might print something like::

5 new accounts today.
11 new accounts this week.
27 new accounts this month.
377 new accounts this year.
409 new accounts until now.

Aggregating time-series data suitable for graphing

::

from django.contrib.auth.models import User
import datetime, qsstats

qs = User.objects.all()
qss = qsstats.QuerySetStats(qs, 'date_joined')

today = datetime.date.today()
seven_days_ago = today - datetime.timedelta(days=7)

time_series = qss.time_series(seven_days_ago, today)
print 'New users in the last 7 days: %s' % [t[1] for t in time_series]

This might print something like::

New users in the last 7 days: [3, 10, 7, 4, 12, 9, 11]

Please see qsstats/tests.py for similar usage examples.

API

The QuerySetStats object

In order to provide maximum flexibility, the QuerySetStats object can be instantiated with as little or as much information as you like. All keword arguments are optional but DateFieldMissing and QuerySetMissing will be raised if you try to use QuerySetStats without providing enough information.

qs The queryset to operate on.

Default: ``None``

date_field The date field within the queryset to use.

Default: ``None``

aggregate The django aggregation instance. Can be set also set when instantiating or calling one of the methods.

Default: ``Count('id')``

operator The default operator to use for the pivot function. Can be also set when calling pivot.

Default: ``'lte'``

today The date that will be considered as today date. If today param is None QuerySetStats' today will be datetime.date.today().

Default: ``None``

All of the documented methods take a standard set of keyword arguments that override any information already stored within the QuerySetStats object. These keyword arguments are date_field and aggregate.

Once you have a QuerySetStats object instantiated, you can receive a single aggregate result by using the following methods:

• for_minute

• for_hour

• for_day

• for_week

• for_month

• for_year

  Positional arguments: dt, a datetime.datetime or datetime.date object to filter the queryset to this interval (minute, hour, day, week, month or year).

• this_minute

• this_hour

• this_day

• this_week

• this_month

• this_year

  Wrappers around for_<interval> that uses dateutil.relativedelta to provide aggregate information for this current interval.

QuerySetStats also provides a method for returning aggregated time-series data which may be extremely using in plotting data:

time_series Positional arguments: start and end, each a datetime.date or datetime.datetime object used in marking the start and stop of the time series data.

Keyword arguments: In addition to the standard ``date_field`` and
``aggregate`` keyword argument, ``time_series`` takes an optional
``interval`` keyword argument used to mark which interval to use while
calculating aggregate data between ``start`` and ``end``.  This argument
defaults to ``'days'`` and can accept ``'years'``, ``'months'``,
``'weeks'``, ``'days'``, ``'hours'`` or ``'minutes'``.
It will raise ``InvalidInterval`` otherwise.

This methods returns a list of tuples.  The first item in each
tuple is a ``datetime.datetime`` object for the current inverval.  The
second item is the result of the aggregate operation.  For
example::

    [(datetime.datetime(2010, 3, 28, 0, 0), 12), (datetime.datetime(2010, 3, 29, 0, 0), 0), ...]

Formatting of date information is left as an exercise to the user and may
vary depending on interval used.

until Provide aggregate information until a given date or time, filtering the queryset using lte.

Positional arguments: ``dt`` a ``datetime.date`` or ``datetime.datetime``
object to be used for filtering the queryset since.

Keyword arguments: ``date_field``, ``aggregate``.

until_now Aggregate information until now.

Positional arguments: ``dt`` a ``datetime.date`` or ``datetime.datetime``
object to be used for filtering the queryset since (using ``lte``).

Keyword arguments: ``date_field``, ``aggregate``.

after Aggregate information after a given date or time, filtering the queryset using gte.

Positional arguments: ``dt`` a ``datetime.date`` or ``datetime.datetime``
object to be used for filtering the queryset since.

Keyword arguments: ``date_field``, ``aggregate``.

after_now Aggregate information after now.

Positional arguments: ``dt`` a ``datetime.date`` or ``datetime.datetime``
object to be used for filtering the queryset since (using ``gte``).

Keyword arguments: ``date_field``, ``aggregate``.

pivot Used by since, after, and until_now but potentially useful if you would like to specify your own operator instead of the defaults.

Positional arguments: ``dt`` a ``datetime.date`` or ``datetime.datetime``
object to be used for filtering the queryset since (using ``lte``).

Keyword arguments: ``operator``, ``date_field``, ``aggregate``.

Raises ``InvalidOperator`` if the operator provided is not one of ``'lt'``,
``'lte'``, ``gt`` or ``gte``.

Testing

If you'd like to test django-qsstats-magic against your local configuration, add qsstats to your INSTALLED_APPS and run ./manage.py test qsstats. The test suite assumes that django.contrib.auth is installed.

For testing against different python, DB and django versions install tox (pip install tox) and run 'tox' from the source checkout::

$ tox

Db user 'qsstats_test' with password 'qsstats_test' and a DB 'qsstats_test' should exist.

Difference from django-qsstats

1. Faster time_series method using 1 sql query (currently works for MySQL and PostgreSQL, with a fallback to the old method for other DB backends).
2. Single aggregate parameter instead of aggregate_field and aggregate_class. Default value is always Count('id') and can't be specified in settings.py. QUERYSETSTATS_DEFAULT_OPERATOR option is also unsupported now.
3. Support for minute and hour aggregates.
4. start_date and end_date arguments are renamed to start and end because of 3.
5. Internals are changed.

I don't know if original author (Matt Croydon) would like my changes so I renamed a project for now. If the changes will be merged then django-qsstats-magic will become obsolete.