jamsheer / django-qsstats-magic

A django microframework that eases the generation of aggregate data for querysets.

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 > 1.4, < 2.0
• django 1.2+

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()[0]
print '%s new accounts this week.' % qss.this_week()[0]
print '%s new accounts this month.' % qss.this_month()[0]
print '%s new accounts this year.' % qss.this_year()[0]
print '%s new accounts until now.' % qss.until_now()[0]

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')

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.

Multiple aggregates

from my_store_app.models import Purchase
from django.db.models import Sum, Count
import datetime, qsstats

qs = Purchase.objects.all()
qss = qsstats.QuerySetStats(qs, 'date_purchased', aggregates=[Count('id'), Sum('amount')])

print '%s Purchases of value %s today.' % tuple(qss.this_day())
print '%s Purchases of value %s this week.' % tuple(qss.this_week())
print '%s Purchases of value %s this month.' % tuple(qss.this_month())
print '%s Purchases of value %s this year.' % tuple(qss.this_year())
print '%s Purchases of value %s until now.' % tuple(qss.until_now())

This might print something like:

5 Purchases of value 50 today.
11 Purchases of value 110 this week.
27 Purchases of value 270 this month.
377 Purchases of value 3770 year.
409 Purchases of value 4090 until now.

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

aggregates

A list of django aggregation instances. Can be set also set when instantiating or calling one of the methods. You can also pass one aggregation instance.

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 aggregates.

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 aggregates 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 other items are the results of the aggregates operations. 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, aggregates.

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, aggregates.

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, aggregates.

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, aggregates.

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, aggregates.

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 aggregates 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.

New in 0.8.0

• Changed aggregate to aggregates and now the framework returns a list of aggregate information instead of only one.