问题
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?
回答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.
回答2:
Django has added a lot of functionality to the ORM since this question was originally asked. The answer to how to pivot data since Django 1.8 is to use the Case/When conditional expressions. And there is a third party app that will do that for you, PyPI and documentation
来源:https://stackoverflow.com/questions/5958415/pivoting-data-and-complex-annotations-in-django-orm