mirror of https://github.com/django/django.git
246 lines
12 KiB
Python
246 lines
12 KiB
Python
# coding: utf-8
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from django.db import models
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from django.conf import settings
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try:
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sorted
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except NameError:
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from django.utils.itercompat import sorted # For Python 2.3
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class Author(models.Model):
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name = models.CharField(max_length=100)
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age = models.IntegerField()
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friends = models.ManyToManyField('self', blank=True)
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def __unicode__(self):
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return self.name
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class Publisher(models.Model):
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name = models.CharField(max_length=300)
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num_awards = models.IntegerField()
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def __unicode__(self):
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return self.name
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class Book(models.Model):
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isbn = models.CharField(max_length=9)
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name = models.CharField(max_length=300)
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pages = models.IntegerField()
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rating = models.FloatField()
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price = models.DecimalField(decimal_places=2, max_digits=6)
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authors = models.ManyToManyField(Author)
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publisher = models.ForeignKey(Publisher)
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pubdate = models.DateField()
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class Meta:
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ordering = ('name',)
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def __unicode__(self):
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return self.name
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class Store(models.Model):
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name = models.CharField(max_length=300)
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books = models.ManyToManyField(Book)
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original_opening = models.DateTimeField()
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friday_night_closing = models.TimeField()
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def __unicode__(self):
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return self.name
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#Extra does not play well with values. Modify the tests if/when this is fixed.
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__test__ = {'API_TESTS': """
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>>> from django.core import management
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>>> from django.db.models import get_app, F
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# Reset the database representation of this app.
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# This will return the database to a clean initial state.
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>>> management.call_command('flush', verbosity=0, interactive=False)
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>>> from django.db.models import Avg, Sum, Count, Max, Min, StdDev, Variance
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# Ordering requests are ignored
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>>> Author.objects.all().order_by('name').aggregate(Avg('age'))
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{'age__avg': 37.4...}
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# Implicit ordering is also ignored
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>>> Book.objects.all().aggregate(Sum('pages'))
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{'pages__sum': 3703}
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# Baseline results
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>>> Book.objects.all().aggregate(Sum('pages'), Avg('pages'))
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{'pages__sum': 3703, 'pages__avg': 617.1...}
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# Empty values query doesn't affect grouping or results
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>>> Book.objects.all().values().aggregate(Sum('pages'), Avg('pages'))
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{'pages__sum': 3703, 'pages__avg': 617.1...}
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# Aggregate overrides extra selected column
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>>> Book.objects.all().extra(select={'price_per_page' : 'price / pages'}).aggregate(Sum('pages'))
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{'pages__sum': 3703}
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# Annotations get combined with extra select clauses
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>>> sorted(Book.objects.all().annotate(mean_auth_age=Avg('authors__age')).extra(select={'manufacture_cost' : 'price * .5'}).get(pk=2).__dict__.items())
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[('id', 2), ('isbn', u'067232959'), ('manufacture_cost', ...11.545...), ('mean_auth_age', 45.0), ('name', u'Sams Teach Yourself Django in 24 Hours'), ('pages', 528), ('price', Decimal("23.09")), ('pubdate', datetime.date(2008, 3, 3)), ('publisher_id', 2), ('rating', 3.0)]
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# Order of the annotate/extra in the query doesn't matter
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>>> sorted(Book.objects.all().extra(select={'manufacture_cost' : 'price * .5'}).annotate(mean_auth_age=Avg('authors__age')).get(pk=2).__dict__.items())
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[('id', 2), ('isbn', u'067232959'), ('manufacture_cost', ...11.545...), ('mean_auth_age', 45.0), ('name', u'Sams Teach Yourself Django in 24 Hours'), ('pages', 528), ('price', Decimal("23.09")), ('pubdate', datetime.date(2008, 3, 3)), ('publisher_id', 2), ('rating', 3.0)]
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# Values queries can be combined with annotate and extra
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>>> sorted(Book.objects.all().annotate(mean_auth_age=Avg('authors__age')).extra(select={'manufacture_cost' : 'price * .5'}).values().get(pk=2).items())
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[('id', 2), ('isbn', u'067232959'), ('manufacture_cost', ...11.545...), ('mean_auth_age', 45.0), ('name', u'Sams Teach Yourself Django in 24 Hours'), ('pages', 528), ('price', Decimal("23.09")), ('pubdate', datetime.date(2008, 3, 3)), ('publisher_id', 2), ('rating', 3.0)]
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# The order of the values, annotate and extra clauses doesn't matter
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>>> sorted(Book.objects.all().values().annotate(mean_auth_age=Avg('authors__age')).extra(select={'manufacture_cost' : 'price * .5'}).get(pk=2).items())
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[('id', 2), ('isbn', u'067232959'), ('manufacture_cost', ...11.545...), ('mean_auth_age', 45.0), ('name', u'Sams Teach Yourself Django in 24 Hours'), ('pages', 528), ('price', Decimal("23.09")), ('pubdate', datetime.date(2008, 3, 3)), ('publisher_id', 2), ('rating', 3.0)]
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# A values query that selects specific columns reduces the output
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>>> sorted(Book.objects.all().annotate(mean_auth_age=Avg('authors__age')).extra(select={'price_per_page' : 'price / pages'}).values('name').get(pk=1).items())
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[('mean_auth_age', 34.5), ('name', u'The Definitive Guide to Django: Web Development Done Right')]
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# The annotations are added to values output if values() precedes annotate()
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>>> sorted(Book.objects.all().values('name').annotate(mean_auth_age=Avg('authors__age')).extra(select={'price_per_page' : 'price / pages'}).get(pk=1).items())
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[('mean_auth_age', 34.5), ('name', u'The Definitive Guide to Django: Web Development Done Right')]
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# Check that all of the objects are getting counted (allow_nulls) and that values respects the amount of objects
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>>> len(Author.objects.all().annotate(Avg('friends__age')).values())
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9
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# Check that consecutive calls to annotate accumulate in the query
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>>> Book.objects.values('price').annotate(oldest=Max('authors__age')).order_by('oldest', 'price').annotate(Max('publisher__num_awards'))
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[{'price': Decimal("30..."), 'oldest': 35, 'publisher__num_awards__max': 3}, {'price': Decimal("29.69"), 'oldest': 37, 'publisher__num_awards__max': 7}, {'price': Decimal("23.09"), 'oldest': 45, 'publisher__num_awards__max': 1}, {'price': Decimal("75..."), 'oldest': 57, 'publisher__num_awards__max': 9}, {'price': Decimal("82.8..."), 'oldest': 57, 'publisher__num_awards__max': 7}]
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# Aggregates can be composed over annotations.
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# The return type is derived from the composed aggregate
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>>> Book.objects.all().annotate(num_authors=Count('authors__id')).aggregate(Max('pages'), Max('price'), Sum('num_authors'), Avg('num_authors'))
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{'num_authors__sum': 10, 'num_authors__avg': 1.66..., 'pages__max': 1132, 'price__max': Decimal("82.80")}
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# Bad field requests in aggregates are caught and reported
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>>> Book.objects.all().aggregate(num_authors=Count('foo'))
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Traceback (most recent call last):
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...
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FieldError: Cannot resolve keyword 'foo' into field. Choices are: authors, id, isbn, name, pages, price, pubdate, publisher, rating, store
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>>> Book.objects.all().annotate(num_authors=Count('foo'))
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Traceback (most recent call last):
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...
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FieldError: Cannot resolve keyword 'foo' into field. Choices are: authors, id, isbn, name, pages, price, pubdate, publisher, rating, store
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>>> Book.objects.all().annotate(num_authors=Count('authors__id')).aggregate(Max('foo'))
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Traceback (most recent call last):
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...
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FieldError: Cannot resolve keyword 'foo' into field. Choices are: authors, id, isbn, name, pages, price, pubdate, publisher, rating, store, num_authors
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# Old-style count aggregations can be mixed with new-style
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>>> Book.objects.annotate(num_authors=Count('authors')).count()
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6
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# Non-ordinal, non-computed Aggregates over annotations correctly inherit
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# the annotation's internal type if the annotation is ordinal or computed
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>>> Book.objects.annotate(num_authors=Count('authors')).aggregate(Max('num_authors'))
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{'num_authors__max': 3}
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>>> Publisher.objects.annotate(avg_price=Avg('book__price')).aggregate(Max('avg_price'))
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{'avg_price__max': 75.0...}
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# Aliases are quoted to protected aliases that might be reserved names
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>>> Book.objects.aggregate(number=Max('pages'), select=Max('pages'))
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{'number': 1132, 'select': 1132}
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# Regression for #10064: select_related() plays nice with aggregates
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>>> Book.objects.select_related('publisher').annotate(num_authors=Count('authors')).values()[0]
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{'rating': 4.0, 'isbn': u'013790395', 'name': u'Artificial Intelligence: A Modern Approach', 'pubdate': datetime.date(1995, 1, 15), 'price': Decimal("82.8..."), 'id': 5, 'num_authors': 2, 'publisher_id': 3, 'pages': 1132}
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# Regression for #10010: exclude on an aggregate field is correctly negated
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>>> len(Book.objects.annotate(num_authors=Count('authors')))
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6
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>>> len(Book.objects.annotate(num_authors=Count('authors')).filter(num_authors__gt=2))
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1
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>>> len(Book.objects.annotate(num_authors=Count('authors')).exclude(num_authors__gt=2))
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5
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>>> len(Book.objects.annotate(num_authors=Count('authors')).filter(num_authors__lt=3).exclude(num_authors__lt=2))
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2
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>>> len(Book.objects.annotate(num_authors=Count('authors')).exclude(num_authors__lt=2).filter(num_authors__lt=3))
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2
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# Aggregates can be used with F() expressions
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# ... where the F() is pushed into the HAVING clause
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>>> Publisher.objects.annotate(num_books=Count('book')).filter(num_books__lt=F('num_awards')/2).order_by('name').values('name','num_books','num_awards')
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[{'num_books': 1, 'name': u'Morgan Kaufmann', 'num_awards': 9}, {'num_books': 2, 'name': u'Prentice Hall', 'num_awards': 7}]
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>>> Publisher.objects.annotate(num_books=Count('book')).exclude(num_books__lt=F('num_awards')/2).order_by('name').values('name','num_books','num_awards')
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[{'num_books': 2, 'name': u'Apress', 'num_awards': 3}, {'num_books': 0, 'name': u"Jonno's House of Books", 'num_awards': 0}, {'num_books': 1, 'name': u'Sams', 'num_awards': 1}]
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# ... and where the F() references an aggregate
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>>> Publisher.objects.annotate(num_books=Count('book')).filter(num_awards__gt=2*F('num_books')).order_by('name').values('name','num_books','num_awards')
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[{'num_books': 1, 'name': u'Morgan Kaufmann', 'num_awards': 9}, {'num_books': 2, 'name': u'Prentice Hall', 'num_awards': 7}]
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>>> Publisher.objects.annotate(num_books=Count('book')).exclude(num_books__lt=F('num_awards')/2).order_by('name').values('name','num_books','num_awards')
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[{'num_books': 2, 'name': u'Apress', 'num_awards': 3}, {'num_books': 0, 'name': u"Jonno's House of Books", 'num_awards': 0}, {'num_books': 1, 'name': u'Sams', 'num_awards': 1}]
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# Regression for #10089: Check handling of empty result sets with aggregates
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>>> Book.objects.filter(id__in=[]).count()
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0
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>>> Book.objects.filter(id__in=[]).aggregate(num_authors=Count('authors'), avg_authors=Avg('authors'), max_authors=Max('authors'), max_price=Max('price'), max_rating=Max('rating'))
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{'max_authors': None, 'max_rating': None, 'num_authors': 0, 'avg_authors': None, 'max_price': None}
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>>> Publisher.objects.filter(pk=5).annotate(num_authors=Count('book__authors'), avg_authors=Avg('book__authors'), max_authors=Max('book__authors'), max_price=Max('book__price'), max_rating=Max('book__rating')).values()
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[{'max_authors': None, 'name': u"Jonno's House of Books", 'num_awards': 0, 'max_price': None, 'num_authors': 0, 'max_rating': None, 'id': 5, 'avg_authors': None}]
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# Regression for #10113 - Fields mentioned in order_by() must be included in the GROUP BY.
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# This only becomes a problem when the order_by introduces a new join.
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>>> Book.objects.annotate(num_authors=Count('authors')).order_by('publisher__name', 'name')
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[<Book: Practical Django Projects>, <Book: The Definitive Guide to Django: Web Development Done Right>, <Book: Paradigms of Artificial Intelligence Programming: Case Studies in Common Lisp>, <Book: Artificial Intelligence: A Modern Approach>, <Book: Python Web Development with Django>, <Book: Sams Teach Yourself Django in 24 Hours>]
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"""
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}
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if settings.DATABASE_ENGINE != 'sqlite3':
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__test__['API_TESTS'] += """
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# Stddev and Variance are not guaranteed to be available for SQLite.
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>>> Book.objects.aggregate(StdDev('pages'))
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{'pages__stddev': 311.46...}
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>>> Book.objects.aggregate(StdDev('rating'))
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{'rating__stddev': 0.60...}
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>>> Book.objects.aggregate(StdDev('price'))
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{'price__stddev': 24.16...}
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>>> Book.objects.aggregate(StdDev('pages', sample=True))
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{'pages__stddev': 341.19...}
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>>> Book.objects.aggregate(StdDev('rating', sample=True))
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{'rating__stddev': 0.66...}
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>>> Book.objects.aggregate(StdDev('price', sample=True))
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{'price__stddev': 26.46...}
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>>> Book.objects.aggregate(Variance('pages'))
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{'pages__variance': 97010.80...}
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>>> Book.objects.aggregate(Variance('rating'))
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{'rating__variance': 0.36...}
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>>> Book.objects.aggregate(Variance('price'))
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{'price__variance': 583.77...}
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>>> Book.objects.aggregate(Variance('pages', sample=True))
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{'pages__variance': 116412.96...}
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>>> Book.objects.aggregate(Variance('rating', sample=True))
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{'rating__variance': 0.44...}
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>>> Book.objects.aggregate(Variance('price', sample=True))
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{'price__variance': 700.53...}
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"""
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