You're right about that. You can aggregate over custom expressions. For
aggregating over enums you should be able to use case expressions
On Wed, 5 Aug 2015 at 05:05 Anssi Kääriäinen <akaar...@gmail.com> wrote:
> On Tuesday, August 4, 2015, Shai Berger <s...@platonix.com> wrote:
>>
>> The classic database aggregation examples involve aggregation over time:
>> Sum
>> of sales per quarter (which is, itself, a function over date); average
>> temparature per month; etc. All these require group-by clauses which name
>> (expressions over) columns which are not FKs.
>>
>>
> The following should work:
>
>
>
> qs.annotate(quarter=Quarter('sold_date')).values('quarter').annotate(sum=Sum('amount'))
>
> I recall some changes to how the group by expression is generated for
> expressions. If I recall correctly the group by should have the expression
> itself now, not the base columns of the expression.
>
> There are many similar examples involving "enum columns" -- columns with a
>> limited set of choices, where the choices are not instances of another
>> model.
>
>
> I'm not sure of this one.
>
> - Anssi
>
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