For those watching trunk, revision 9742 added aggregate support to
Django. (Yay!)
The short version is that Querysets now have two additional operations
- annotate() and aggregate(). For details on how to use these new
operations, see the documentation:
http://docs.djangoproject.com/en/dev/topics/db/aggregation/
As prior warning - there is one known problem which we are still
tracking down. On Windows, using SQLite and Python 2.5, date and
decimal values can get corrupted. This doesn't affect other versions
of Python (2.4 or 2.6) on Windows, or Python 2.5 on Linux/Mac. I hope
to get these problems cleared up very soon. If you are affected,
either don't update your SVN checkout, or use a different version of
Python (multiple Python versions co-exist fairly easily under
Windows).
I've opened ticket #10031 to track this known problem. If you find any
other issues with aggregates, please open a ticket (or ask on the
mailing list/IRC if you're unsure if the problem is usage or bug).
Lastly - some thank-yous. This commit wouldn't have been possible
without the assistance of many other people.
Nicolas Lara did some excellent work turning a specification into a
working implementation as part of the 2008 Google Summer of Code.
Nicolas - take a bow - you did some excellent work here.
Alex Gaynor provided some excellent assistance debugging and fixing a
number of problems as we neared completion of the project. Thanks
Alex.
Justin Bronn used his GIS-fu to get aggregates working with
contrib.gis. Thanks Justin.
Karen Tracey used her massive personal server farm to provide
cross-platform testing. Thanks Karen.
Ian Kelly helped out testing and fixing aggregates on Oracle. Thanks Ian.
Malcolm Tredinnick did his usual stunning job at reviewing code and
picking holes in designs. Thanks Malcolm.
Thanks also to the many people that contributed ideas during the
design phase, and to those who tested the code as it was developing.
Your efforts may not have ended up in the final design or turned into
a bug report, but thanks for taking the time to look at an
experimental feature.
Yours,
Russ Magee %-)
Thank you all very much! This is big.