How to write query of group by - django

I have model named IssueFlags with columns:
id, created_at, flags_id, issue_id, comments
I want to get data of unique issue_id (latest created) with info about flags_id, created_at and comments
By sql it's working like this:
SELECT created_at, flags_id, issue_id, comments
FROM Issues_issueflags
group by issue_id
How to do the same in Django? I tried to wrote sth in shell, but there is no attribute group by
IssueFlags.objects.order_by('-created_at')
This above return me only the list of ordered data.

Try doing this way:
from django.db.models import Count
IssueFlags.objects.values('created_at', 'flags_id', 'issue_id', 'comments').order_by('-created_at').annotate(total=Count('issue_id'))
I have written annotate(total=Count('issue_id')) assuming that you would have multiple entries of unique issue_id (Note that you can do all possible types of aggregations like Sum, Count, Max, Avg inside . Also, there already exists answers for, doing group by in django. Also have a look at this link or this link. Also, read this django documentation to get a clear idea on when to place values() before annotate() and when to place it after, and then implement the learning as per your requirement.
Would be happy to help if you have any further doubts.

Related

Django 1.11 Annotating a Subquery Aggregate

This is a bleeding-edge feature that I'm currently skewered upon and quickly bleeding out. I want to annotate a subquery-aggregate onto an existing queryset. Doing this before 1.11 either meant custom SQL or hammering the database. Here's the documentation for this, and the example from it:
from django.db.models import OuterRef, Subquery, Sum
comments = Comment.objects.filter(post=OuterRef('pk')).values('post')
total_comments = comments.annotate(total=Sum('length')).values('total')
Post.objects.filter(length__gt=Subquery(total_comments))
They're annotating on the aggregate, which seems weird to me, but whatever.
I'm struggling with this so I'm boiling it right back to the simplest real-world example I have data for. I have Carparks which contain many Spaces. Use Book→Author if that makes you happier but —for now— I just want to annotate on a count of the related model using Subquery*.
spaces = Space.objects.filter(carpark=OuterRef('pk')).values('carpark')
count_spaces = spaces.annotate(c=Count('*')).values('c')
Carpark.objects.annotate(space_count=Subquery(count_spaces))
This gives me a lovely ProgrammingError: more than one row returned by a subquery used as an expression and in my head, this error makes perfect sense. The subquery is returning a list of spaces with the annotated-on total.
The example suggested that some sort of magic would happen and I'd end up with a number I could use. But that's not happening here? How do I annotate on aggregate Subquery data?
Hmm, something's being added to my query's SQL...
I built a new Carpark/Space model and it worked. So the next step is working out what's poisoning my SQL. On Laurent's advice, I took a look at the SQL and tried to make it more like the version they posted in their answer. And this is where I found the real problem:
SELECT "bookings_carpark".*, (SELECT COUNT(U0."id") AS "c"
FROM "bookings_space" U0
WHERE U0."carpark_id" = ("bookings_carpark"."id")
GROUP BY U0."carpark_id", U0."space"
)
AS "space_count" FROM "bookings_carpark";
I've highlighted it but it's that subquery's GROUP BY ... U0."space". It's retuning both for some reason. Investigations continue.
Edit 2: Okay, just looking at the subquery SQL I can see that second group by coming through ☹
In [12]: print(Space.objects_standard.filter().values('carpark').annotate(c=Count('*')).values('c').query)
SELECT COUNT(*) AS "c" FROM "bookings_space" GROUP BY "bookings_space"."carpark_id", "bookings_space"."space" ORDER BY "bookings_space"."carpark_id" ASC, "bookings_space"."space" ASC
Edit 3: Okay! Both these models have sort orders. These are being carried through to the subquery. It's these orders that are bloating out my query and breaking it.
I guess this might be a bug in Django but short of removing the Meta-order_by on both these models, is there any way I can unsort a query at querytime?
*I know I could just annotate a Count for this example. My real purpose for using this is a much more complex filter-count but I can't even get this working.
Shazaam! Per my edits, an additional column was being output from my subquery. This was to facilitate ordering (which just isn't required in a COUNT).
I just needed to remove the prescribed meta-order from the model. You can do this by just adding an empty .order_by() to the subquery. In my code terms that meant:
from django.db.models import Count, OuterRef, Subquery
spaces = Space.objects.filter(carpark=OuterRef('pk')).order_by().values('carpark')
count_spaces = spaces.annotate(c=Count('*')).values('c')
Carpark.objects.annotate(space_count=Subquery(count_spaces))
And that works. Superbly. So annoying.
It's also possible to create a subclass of Subquery, that changes the SQL it outputs. For instance, you can use:
class SQCount(Subquery):
template = "(SELECT count(*) FROM (%(subquery)s) _count)"
output_field = models.IntegerField()
You then use this as you would the original Subquery class:
spaces = Space.objects.filter(carpark=OuterRef('pk')).values('pk')
Carpark.objects.annotate(space_count=SQCount(spaces))
You can use this trick (at least in postgres) with a range of aggregating functions: I often use it to build up an array of values, or sum them.
I just bumped into a VERY similar case, where I had to get seat reservations for events where the reservation status is not cancelled. After trying to figure the problem out for hours, here's what I've seen as the root cause of the problem:
Preface: this is MariaDB, Django 1.11.
When you annotate a query, it gets a GROUP BY clause with the fields you select (basically what's in your values() query selection). After investigating with the MariaDB command line tool why I'm getting NULLs or Nones on the query results, I've came to the conclusion that the GROUP BY clause will cause the COUNT() to return NULLs.
Then, I started diving into the QuerySet interface to see how can I manually, forcibly remove the GROUP BY from the DB queries, and came up with the following code:
from django.db.models.fields import PositiveIntegerField
reserved_seats_qs = SeatReservation.objects.filter(
performance=OuterRef(name='pk'), status__in=TAKEN_TYPES
).values('id').annotate(
count=Count('id')).values('count')
# Query workaround: remove GROUP BY from subquery. Test this
# vigorously!
reserved_seats_qs.query.group_by = []
performances_qs = Performance.objects.annotate(
reserved_seats=Subquery(
queryset=reserved_seats_qs,
output_field=PositiveIntegerField()))
print(performances_qs[0].reserved_seats)
So basically, you have to manually remove/update the group_by field on the subquery's queryset in order for it to not have a GROUP BY appended on it on execution time. Also, you'll have to specify what output field the subquery will have, as it seems that Django fails to recognize it automatically, and raises exceptions on the first evaluation of the queryset. Interestingly, the second evaluation succeeds without it.
I believe this is a Django bug, or an inefficiency in subqueries. I'll create a bug report about it.
Edit: the bug report is here.
Problem
The problem is that Django adds GROUP BY as soon as it sees using an aggregate function.
Solution
So you can just create your own aggregate function but so that Django thinks it is not aggregate. Just like this:
total_comments = Comment.objects.filter(
post=OuterRef('pk')
).order_by().annotate(
total=Func(F('length'), function='SUM')
).values('total')
Post.objects.filter(length__gt=Subquery(total_comments))
This way you get the SQL query like this:
SELECT "testapp_post"."id", "testapp_post"."length"
FROM "testapp_post"
WHERE "testapp_post"."length" > (SELECT SUM(U0."length") AS "total"
FROM "testapp_comment" U0
WHERE U0."post_id" = "testapp_post"."id")
So you can even use aggregate subqueries in aggregate functions.
Example
You can count the number of workdays between two dates, excluding weekends and holidays, and aggregate and summarize them by employee:
class NonWorkDay(models.Model):
date = DateField()
class WorkPeriod(models.Model):
employee = models.ForeignKey(User, on_delete=models.CASCADE)
start_date = DateField()
end_date = DateField()
number_of_non_work_days = NonWorkDay.objects.filter(
date__gte=OuterRef('start_date'),
date__lte=OuterRef('end_date'),
).annotate(
cnt=Func('id', function='COUNT')
).values('cnt')
WorkPeriod.objects.values('employee').order_by().annotate(
number_of_word_days=Sum(F('end_date__year') - F('start_date__year') - number_of_non_work_days)
)
Hope this will help!
A solution which would work for any general aggregation could be implemented using Window classes from Django 2.0. I have added this to the Django tracker ticket as well.
This allows the aggregation of annotated values by calculating the aggregate over partitions based on the outer query model (in the GROUP BY clause), then annotating that data to every row in the subquery queryset. The subquery can then use the aggregated data from the first row returned and ignore the other rows.
Performance.objects.annotate(
reserved_seats=Subquery(
SeatReservation.objects.filter(
performance=OuterRef(name='pk'),
status__in=TAKEN_TYPES,
).annotate(
reserved_seat_count=Window(
expression=Count('pk'),
partition_by=[F('performance')]
),
).values('reserved_seat_count')[:1],
output_field=FloatField()
)
)
If I understand correctly, you are trying to count Spaces available in a Carpark. Subquery seems overkill for this, the good old annotate alone should do the trick:
Carpark.objects.annotate(Count('spaces'))
This will include a spaces__count value in your results.
OK, I have seen your note...
I was also able to run your same query with other models I had at hand. The results are the same, so the query in your example seems to be OK (tested with Django 1.11b1):
activities = Activity.objects.filter(event=OuterRef('pk')).values('event')
count_activities = activities.annotate(c=Count('*')).values('c')
Event.objects.annotate(spaces__count=Subquery(count_activities))
Maybe your "simplest real-world example" is too simple... can you share the models or other information?
"works for me" doesn't help very much. But.
I tried your example on some models I had handy (the Book -> Author type), it works fine for me in django 1.11b1.
Are you sure you're running this in the right version of Django? Is this the actual code you're running? Are you actually testing this not on carpark but some more complex model?
Maybe try to print(thequery.query) to see what SQL it's trying to run in the database. Below is what I got with my models (edited to fit your question):
SELECT (SELECT COUNT(U0."id") AS "c"
FROM "carparks_spaces" U0
WHERE U0."carpark_id" = ("carparks_carpark"."id")
GROUP BY U0."carpark_id") AS "space_count" FROM "carparks_carpark"
Not really an answer, but hopefully it helps.

Django: Filtering out duplicate query results

I have a model:
class Item(models.Model):
date = models.DateField()
I would like to select one of these objects for each date, with no duplicates.
So if there were 100 items in the database, which had dates of either 1/1/12 or 1/2/12, I would want to return a list of two objects (one for 1/1/12 and one for 1/2/12).
I'm not sure of the terminology for this kind of query, so am having trouble searching for an answer.
I'm currently using this query:
item_list = Item.objects.distinct('date')
But it is not working as I expected.
Any help appriciated.
Thanks for reading.
Are you using Postgress SQL? Django documentation says distinct on fields works only with that DB. Also you have to use order_by before using distinct().
Check documentation : django distinct

Grouping Django model entries by day using its datetime field

I'm working with an Article like model that has a DateTimeField(auto_now_add=True) to capture the publication date (pub_date). This looks something like the following:
class Article(models.Model):
text = models.TextField()
pub_date = models.DateTimeField(auto_now_add=True)
I want to do a query that counts how many article posts or entries have been added per day. In other words, I want to query the entries and group them by day (and eventually month, hour, second, etc.). This would look something like the following in the SQLite shell:
select pub_date, count(id) from "myapp_article"
where id = 1
group by strftime("%d", pub_date)
;
Which returns something like:
2012-03-07 18:08:57.456761|5
2012-03-08 18:08:57.456761|9
2012-03-09 18:08:57.456761|1
I can't seem to figure out how to get that result from a Django QuerySet. I am aware of how to get a similar result using itertools.groupby, but that isn't possible in this situation (explanation to follow).
The end result of this query will be used in a graph showing the number of posts per day. I'm attempting to use the Django Chartit package to achieve this goal. Chartit puts a constraint on the data source (DataPool). The source must be a Model, Manager, or QuerySet, so using itertools.groupby is not an option as far as I can tell.
So the question is... How do I group or aggregate the entries by day and end up with a QuerySet object?
Create an extra field that only store date data(not time) and annotate with Count:
Article.objects.extra({'published':"date(pub_date)"}).values('published').annotate(count=Count('id'))
Result will be:
published,count
2012-03-07,5
2012-03-08,9
2012-03-09,1

Django annotation with nested filter

Is it possible to filter within an annotation?
In my mind something like this (which doesn't actually work)
Student.objects.all().annotate(Count('attendance').filter(type="Excused"))
The resultant table would have every student with the number of excused absences. Looking through documentation filters can only be before or after the annotation which would not yield the desired results.
A workaround is this
for student in Student.objects.all():
student.num_excused_absence = Attendance.objects.filter(student=student, type="Excused").count()
This works but does many queries, in a real application this can get impractically long. I think this type of statement is possible in SQL but would prefer to stay with ORM if possible. I even tried making two separate queries (one for all students, another to get the total) and combined them with |. The combination changed the total :(
Some thoughts after reading answers and comments
I solved the attendance problem using extra sql here.
Timmy's blog post was useful. My answer is based off of it.
hash1baby's answer works but seems equally complex as sql. It also requires executing sql then adding the result in a for loop. This is bad for me because I'm stacking lots of these filtering queries together. My solution builds up a big queryset with lots of filters and extra and executes it all at once.
If performance is no issue - I suggest the for loop work around. It's by far the easiest to understand.
As of Django 1.8 you can do this directly in the ORM:
students = Student.objects.all().annotate(num_excused_absences=models.Sum(
models.Case(
models.When(absence__type='Excused', then=1),
default=0,
output_field=models.IntegerField()
)))
Answer adapted from another SO question on the same topic
I haven't tested the sample above but did accomplish something similar in my own app.
You are correct - django does not allow you to filter the related objects being counted, without also applying the filter to the primary objects, and therefore excluding those primary objects with a no related objects after filtering.
But, in a bit of abstraction leakage, you can count groups by using a values query.
So, I collect the absences in a dictionary, and use that in a loop. Something like this:
# a query for students
students = Students.objects.all()
# a query to count the student attendances, grouped by type.
attendance_counts = Attendence(student__in=students).values('student', 'type').annotate(abs=Count('pk'))
# regroup that into a dictionary {student -> { type -> count }}
from itertools import groupby
attendance_s_t = dict((s, (dict(t, c) for (s, t, c) in g)) for s, g in groupby(attendance_counts, lambda (s, t, c): s))
# then use them efficiently:
for student in students:
student.absences = attendance_s_t.get(student.pk, {}).get('Excused', 0)
Maybe this will work for you:
excused = Student.objects.filter(attendance__type='Excused').annotate(abs=Count('attendance'))
You need to filter the Students you're looking for first to just those with excused absences and then annotate the count of them.
Here's a link to the Django Aggregation Docs where it discusses filtering order.

Django DB, finding Categories whose Items are all in a subset

I have a two models:
class Category(models.Model):
pass
class Item(models.Model):
cat = models.ForeignKey(Category)
I am trying to return all Categories for which all of that category's items belong to a given subset of item ids (fixed thanks). For example, all categories for which all of the items associated with that category have ids in the set [1,3,5].
How could this be done using Django's query syntax (as of 1.1 beta)? Ideally, all the work should be done in the database.
Category.objects.filter(item__id__in=[1, 3, 5])
Django creates the reverse relation ship on the model without the foreign key. You can filter on it by using its related name (usually just the model name lowercase but it can be manually overwritten), two underscores, and the field name you want to query on.
lets say you require all items to be in the following set:
allowable_items = set([1,3,4])
one bruteforce solution would be to check the item_set for every category as so:
categories_with_allowable_items = [
category for category in
Category.objects.all() if
set([item.id for item in category.item_set.all()]) <= allowable_items
]
but we don't really have to check all categories, as categories_with_allowable_items is always going to be a subset of the categories related to all items with ids in allowable_items... so that's all we have to check (and this should be faster):
categories_with_allowable_items = set([
item.category for item in
Item.objects.select_related('category').filter(pk__in=allowable_items) if
set([siblingitem.id for siblingitem in item.category.item_set.all()]) <= allowable_items
])
if performance isn't really an issue, then the latter of these two (if not the former) should be fine. if these are very large tables, you might have to come up with a more sophisticated solution. also if you're using a particularly old version of python remember that you'll have to import the sets module
I've played around with this a bit. If QuerySet.extra() accepted a "having" parameter I think it would be possible to do it in the ORM with a bit of raw SQL in the HAVING clause. But it doesn't, so I think you'd have to write the whole query in raw SQL if you want the database doing the work.
EDIT:
This is the query that gets you part way there:
from django.db.models import Count
Category.objects.annotate(num_items=Count('item')).filter(num_items=...)
The problem is that for the query to work, "..." needs to be a correlated subquery that looks up, for each category, the number of its items in allowed_items. If .extra had a "having" argument, you'd do it like this:
Category.objects.annotate(num_items=Count('item')).extra(having="num_items=(SELECT COUNT(*) FROM app_item WHERE app_item.id in % AND app_item.cat_id = app_category.id)", having_params=[allowed_item_ids])