Pivoting data and complex annotations in Django ORM

Question

The ORM in Django lets us easily annotate (add fields to) querysets based on related data, hwoever I can't find a way to get multiple annotations for different filtered subsets of related data.

This is being asked in relation to django-helpdesk, an open-source Django-powered trouble-ticket tracker. I need to have data pivoted like this for charting and reporting purposes

Consider these models:

CHOICE_LIST = (
    ('open', 'Open'),
    ('closed', 'Closed'),
)

class Queue(models.model):
    name = models.CharField(max_length=40)

class Issue(models.Model):
    subject = models.CharField(max_length=40)
    queue = models.ForeignKey(Queue)
    status = models.CharField(max_length=10, choices=CHOICE_LIST)

And this dataset:

Queues:

ID | Name
---+------------------------------
1  | Product Information Requests
2  | Service Requests

Issues:

ID | Queue | Status
---+-------+---------
1  | 1     | open
2  | 1     | open
3  | 1     | closed
4  | 2     | open
5  | 2     | closed
6  | 2     | closed
7  | 2     | closed

I would like to see an annotation/aggregate look something like this:

Queue ID | Name                          | open | closed
---------+-------------------------------+------+--------
1        | Product Information Requests  | 2    | 1
2        | Service Requests              | 1    | 3

This is basically a crosstab or pivot table, in Excel parlance. I am currently building this output using some custom SQL queries, however if I can move to using the Django ORM I can more easily filter the data dynamically without doing dodgy insertion of WHERE clauses in my SQL.

For "bonus points": How would one do this where the pivot field (status in the example above) was a date, and we wanted the columns to be months / weeks / quarters / days?

Answer 1

You have Python, use it.

from collections import defaultdict
summary = defaultdict( int )
for issue in Issues.objects.all():
    summary[issue.queue, issue.status] += 1

Now your summary object has queue, status as a two-tuple key. You can display it directly, using various template techniques.

Or, you can regroup it into a table-like structure, if that's simpler.

table = []
queues = list( q for q,_ in summary.keys() )
for q in sorted( queues ):
    table.append( q.id, q.name, summary.count(q,'open'), summary.count(q.'closed') )

You have lots and lots of Python techniques for doing pivot tables.

If you measure, you may find that a mostly-Python solution like this is actually faster than a pure SQL solution. Why? Mappings can be faster than SQL algorithms which require a sort as part of a GROUP-BY.