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diff --git a/tests/modeltests/aggregation/models.py b/tests/modeltests/aggregation/models.py
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+# coding: utf-8
+from django.db import models
+
+try:
+    sorted
+except NameError:
+    from django.utils.itercompat import sorted      # For Python 2.3
+
+class Author(models.Model):
+   name = models.CharField(max_length=100)
+   age = models.IntegerField()
+   friends = models.ManyToManyField('self', blank=True)
+
+   def __unicode__(self):
+      return self.name
+
+class Publisher(models.Model):
+   name = models.CharField(max_length=300)
+   num_awards = models.IntegerField()
+
+   def __unicode__(self):
+      return self.name
+
+class Book(models.Model):
+   isbn = models.CharField(max_length=9)
+   name = models.CharField(max_length=300)
+   pages = models.IntegerField()
+   rating = models.FloatField()
+   price = models.DecimalField(decimal_places=2, max_digits=6)
+   authors = models.ManyToManyField(Author)
+   publisher = models.ForeignKey(Publisher)
+   pubdate = models.DateField()
+
+   def __unicode__(self):
+      return self.name
+
+class Store(models.Model):
+   name = models.CharField(max_length=300)
+   books = models.ManyToManyField(Book)
+   original_opening = models.DateTimeField()
+   friday_night_closing = models.TimeField()
+
+   def __unicode__(self):
+      return self.name
+
+class Entries(models.Model):
+   EntryID = models.AutoField(primary_key=True, db_column='Entry ID')
+   Entry = models.CharField(unique=True, max_length=50)
+   Exclude = models.BooleanField()
+
+class Clues(models.Model):
+   ID = models.AutoField(primary_key=True)
+   EntryID = models.ForeignKey(Entries, verbose_name='Entry', db_column = 'Entry ID')
+   Clue = models.CharField(max_length=150)
+
+# Tests on 'aggergate'
+# Different backends and numbers.
+__test__ = {'API_TESTS': """
+>>> from django.core import management
+>>> try:
+...     from decimal import Decimal
+... except:
+...     from django.utils._decimal import Decimal
+>>> from datetime import date
+
+# Reset the database representation of this app.
+# This will return the database to a clean initial state.
+>>> management.call_command('flush', verbosity=0, interactive=False)
+
+# Empty Call - request nothing, get nothing.
+>>> Author.objects.all().aggregate()
+{}
+
+>>> from django.db.models import Avg, Sum, Count, Max, Min
+
+# Single model aggregation
+#
+
+# Single aggregate
+# Average age of Authors
+>>> Author.objects.all().aggregate(Avg('age'))
+{'age__avg': 37.4...}
+
+# Multiple aggregates
+# Average and Sum of Author ages
+>>> Author.objects.all().aggregate(Sum('age'), Avg('age'))
+{'age__sum': 337, 'age__avg': 37.4...}
+
+# Aggreates interact with filters, and only
+# generate aggregate values for the filtered values
+# Sum of the age of those older than 29 years old
+>>> Author.objects.all().filter(age__gt=29).aggregate(Sum('age'))
+{'age__sum': 254}
+
+# Depth-1 Joins
+#
+
+# On Relationships with self
+# Average age of the friends of each author
+>>> Author.objects.all().aggregate(Avg('friends__age'))
+{'friends__age__avg': 34.07...}
+
+# On ManyToMany Relationships
+#
+
+# Forward
+# Average age of the Authors of Books with a rating of less than 4.5
+>>> Book.objects.all().filter(rating__lt=4.5).aggregate(Avg('authors__age'))
+{'authors__age__avg': 38.2...}
+
+# Backward
+# Average rating of the Books whose Author's name contains the letter 'a'
+>>> Author.objects.all().filter(name__contains='a').aggregate(Avg('book__rating'))
+{'book__rating__avg': 4.0}
+
+# On OneToMany Relationships
+#
+
+# Forward
+# Sum of the number of awards of each Book's Publisher
+>>> Book.objects.all().aggregate(Sum('publisher__num_awards'))
+{'publisher__num_awards__sum': 30}
+
+# Backward
+# Sum of the price of every Book that has a Publisher
+>>> Publisher.objects.all().aggregate(Sum('book__price'))
+{'book__price__sum': Decimal("270.27")}
+
+# Multiple Joins
+#
+
+# Forward
+>>> Store.objects.all().aggregate(Max('books__authors__age'))
+{'books__authors__age__max': 57}
+
+# Backward
+# Note that the very long default alias may be truncated
+>>> Author.objects.all().aggregate(Min('book__publisher__num_awards'))
+{'book__publisher__num_award...': 1}
+
+# Aggregate outputs can also be aliased.
+
+# Average amazon.com Book rating
+>>> Store.objects.filter(name='Amazon.com').aggregate(amazon_mean=Avg('books__rating'))
+{'amazon_mean': 4.08...}
+
+# Tests on annotate()
+
+# An empty annotate call does nothing but return the same QuerySet
+>>> Book.objects.all().annotate().order_by('pk')
+[<Book: The Definitive Guide to Django: Web Development Done Right>, <Book: Sams Teach Yourself Django in 24 Hours>, <Book: Practical Django Projects>, <Book: Python Web Development with Django>, <Book: Artificial Intelligence: A Modern Approach>, <Book: Paradigms of Artificial Intelligence Programming: Case Studies in Common Lisp>]
+
+# Annotate inserts the alias into the model object with the aggregated result
+>>> books = Book.objects.all().annotate(mean_age=Avg('authors__age'))
+>>> books.get(pk=1).name
+u'The Definitive Guide to Django: Web Development Done Right'
+
+>>> books.get(pk=1).mean_age
+34.5
+
+# On ManyToMany Relationships
+
+# Forward
+# Average age of the Authors of each book with a rating less than 4.5
+>>> books = Book.objects.all().filter(rating__lt=4.5).annotate(Avg('authors__age'))
+>>> sorted([(b.name, b.authors__age__avg) for b in books])
+[(u'Artificial Intelligence: A Modern Approach', 51.5), (u'Practical Django Projects', 29.0), (u'Python Web Development with Django', 30.3...), (u'Sams Teach Yourself Django in 24 Hours', 45.0)]
+
+# Count the number of authors of each book
+>>> books = Book.objects.annotate(num_authors=Count('authors'))
+>>> sorted([(b.name, b.num_authors) for b in books])
+[(u'Artificial Intelligence: A Modern Approach', 2), (u'Paradigms of Artificial Intelligence Programming: Case Studies in Common Lisp', 1), (u'Practical Django Projects', 1), (u'Python Web Development with Django', 3), (u'Sams Teach Yourself Django in 24 Hours', 1), (u'The Definitive Guide to Django: Web Development Done Right', 2)]
+
+# Backward
+# Average rating of the Books whose Author's names contains the letter 'a'
+>>> authors = Author.objects.all().filter(name__contains='a').annotate(Avg('book__rating'))
+>>> sorted([(a.name, a.book__rating__avg) for a in authors])
+[(u'Adrian Holovaty', 4.5), (u'Brad Dayley', 3.0), (u'Jacob Kaplan-Moss', 4.5), (u'James Bennett', 4.0), (u'Paul Bissex', 4.0), (u'Stuart Russell', 4.0)]
+
+# Count the number of books written by each author
+>>> authors = Author.objects.annotate(num_books=Count('book'))
+>>> sorted([(a.name, a.num_books) for a in authors])
+[(u'Adrian Holovaty', 1), (u'Brad Dayley', 1), (u'Jacob Kaplan-Moss', 1), (u'James Bennett', 1), (u'Jeffrey Forcier ', 1), (u'Paul Bissex', 1), (u'Peter Norvig', 2), (u'Stuart Russell', 1), (u'Wesley J. Chun', 1)]
+
+# On OneToMany Relationships
+
+# Forward
+# Annotate each book with the number of awards of each Book's Publisher
+>>> books = Book.objects.all().annotate(Sum('publisher__num_awards'))
+>>> sorted([(b.name, b.publisher__num_awards__sum) for b in books])
+[(u'Artificial Intelligence: A Modern Approach', 7), (u'Paradigms of Artificial Intelligence Programming: Case Studies in Common Lisp', 9), (u'Practical Django Projects', 3), (u'Python Web Development with Django', 7), (u'Sams Teach Yourself Django in 24 Hours', 1), (u'The Definitive Guide to Django: Web Development Done Right', 3)]
+
+# Backward
+# Annotate each publisher with the sum of the price of all books sold
+>>> publishers = Publisher.objects.all().annotate(Sum('book__price'))
+>>> sorted([(p.name, p.book__price__sum) for p in publishers])
+[(u'Apress', Decimal("59.69")), (u'Morgan Kaufmann', Decimal("75.00")), (u'Prentice Hall', Decimal("112.49")), (u'Sams', Decimal("23.09"))]
+
+# Calls to values() are not commutative over annotate().
+
+# Calling values on a queryset that has annotations returns the output
+# as a dictionary
+>>> Book.objects.filter(pk=1).annotate(mean_age=Avg('authors__age')).values()
+[{'rating': 4.5, 'isbn': u'159059725', 'name': u'The Definitive Guide to Django: Web Development Done Right', 'pubdate': datetime.date(2007, 12, 6), 'price': Decimal("30..."), 'id': 1, 'publisher_id': 1, 'pages': 447, 'mean_age': 34.5}]
+
+>>> Book.objects.filter(pk=1).annotate(mean_age=Avg('authors__age')).values('pk', 'isbn', 'mean_age')
+[{'pk': 1, 'isbn': u'159059725', 'mean_age': 34.5}]
+
+# Calling it with paramters reduces the output but does not remove the
+# annotation.
+>>> Book.objects.filter(pk=1).annotate(mean_age=Avg('authors__age')).values('name')
+[{'name': u'The Definitive Guide to Django: Web Development Done Right', 'mean_age': 34.5}]
+
+# An empty values() call before annotating has the same effect as an
+# empty values() call after annotating
+>>> Book.objects.filter(pk=1).values().annotate(mean_age=Avg('authors__age'))
+[{'rating': 4.5, 'isbn': u'159059725', 'name': u'The Definitive Guide to Django: Web Development Done Right', 'pubdate': datetime.date(2007, 12, 6), 'price': Decimal("30..."), 'id': 1, 'publisher_id': 1, 'pages': 447, 'mean_age': 34.5}]
+
+# Calling annotate() on a ValuesQuerySet annotates over the groups of
+# fields to be selected by the ValuesQuerySet.
+
+# Note that an extra parameter is added to each dictionary. This
+# parameter is a queryset representing the objects that have been
+# grouped to generate the annotation
+
+>>> Book.objects.all().values('rating').annotate(n_authors=Count('authors__id'), mean_age=Avg('authors__age')).order_by('rating')
+[{'rating': 3.0, 'n_authors': 1, 'mean_age': 45.0}, {'rating': 4.0, 'n_authors': 6, 'mean_age': 37.1...}, {'rating': 4.5, 'n_authors': 2, 'mean_age': 34.5}, {'rating': 5.0, 'n_authors': 1, 'mean_age': 57.0}]
+
+# If a join doesn't match any objects, an aggregate returns None
+>>> authors = Author.objects.all().annotate(Avg('friends__age')).order_by('id')
+>>> len(authors)
+9
+>>> sorted([(a.name, a.friends__age__avg) for a in authors])
+[(u'Adrian Holovaty', 32.0), (u'Brad Dayley', None), (u'Jacob Kaplan-Moss', 29.5), (u'James Bennett', 34.0), (u'Jeffrey Forcier ', 27.0), (u'Paul Bissex', 31.0), (u'Peter Norvig', 46.0), (u'Stuart Russell', 57.0), (u'Wesley J. Chun', 33.6...)]
+
+
+# The Count aggregation function allows an extra parameter: distinct.
+# This restricts the count results to unique items
+>>> Book.objects.all().aggregate(Count('rating'))
+{'rating__count': 6}
+
+>>> Book.objects.all().aggregate(Count('rating', distinct=True))
+{'rating__count': 4}
+
+# Retreiving the grouped objects
+
+# When using Count you can also omit the primary key and refer only to
+# the related field name if you want to count all the related objects
+# and not a specific column
+>>> explicit = list(Author.objects.annotate(Count('book__id')))
+>>> implicit = list(Author.objects.annotate(Count('book')))
+>>> explicit == implicit
+True
+
+# Ordering is allowed on aggregates
+>>> Book.objects.values('rating').annotate(oldest=Max('authors__age')).order_by('oldest', 'rating')
+[{'rating': 4.5, 'oldest': 35}, {'rating': 3.0, 'oldest': 45}, {'rating': 4.0, 'oldest': 57}, {'rating': 5.0, 'oldest': 57}]
+
+>>> Book.objects.values('rating').annotate(oldest=Max('authors__age')).order_by('-oldest', '-rating')
+[{'rating': 5.0, 'oldest': 57}, {'rating': 4.0, 'oldest': 57}, {'rating': 3.0, 'oldest': 45}, {'rating': 4.5, 'oldest': 35}]
+
+# It is possible to aggregate over anotated values
+>>> Book.objects.all().annotate(num_authors=Count('authors__id')).aggregate(Avg('num_authors'))
+{'num_authors__avg': 1.66...}
+
+# You can filter the results based on the aggregation alias.
+
+# Lets add a publisher to test the different possibilities for filtering
+>>> p = Publisher(name='Expensive Publisher', num_awards=0)
+>>> p.save()
+>>> Book(name='ExpensiveBook1', pages=1, isbn='111', rating=3.5, price=Decimal("1000"), publisher=p, pubdate=date(2008,12,1)).save()
+>>> Book(name='ExpensiveBook2', pages=1, isbn='222', rating=4.0, price=Decimal("1000"), publisher=p, pubdate=date(2008,12,2)).save()
+>>> Book(name='ExpensiveBook3', pages=1, isbn='333', rating=4.5, price=Decimal("35"), publisher=p, pubdate=date(2008,12,3)).save()
+
+# Publishers that have:
+
+# (i) more than one book
+>>> Publisher.objects.annotate(num_books=Count('book__id')).filter(num_books__gt=1).order_by('pk')
+[<Publisher: Apress>, <Publisher: Prentice Hall>, <Publisher: Expensive Publisher>]
+
+# (ii) a book that cost less than 40
+>>> Publisher.objects.filter(book__price__lt=Decimal("40.0")).order_by('pk')
+[<Publisher: Apress>, <Publisher: Apress>, <Publisher: Sams>, <Publisher: Prentice Hall>, <Publisher: Expensive Publisher>]
+
+# (iii) more than one book and (at least) a book that cost less than 40
+>>> Publisher.objects.annotate(num_books=Count('book__id')).filter(num_books__gt=1, book__price__lt=Decimal("40.0")).order_by('pk')
+[<Publisher: Apress>, <Publisher: Prentice Hall>, <Publisher: Expensive Publisher>]
+
+# (iv) more than one book that costs less than $40
+>>> Publisher.objects.filter(book__price__lt=Decimal("40.0")).annotate(num_books=Count('book__id')).filter(num_books__gt=1).order_by('pk')
+[<Publisher: Apress>]
+
+# Now a bit of testing on the different lookup types
+#
+
+>>> Publisher.objects.annotate(num_books=Count('book')).filter(num_books__range=[1, 3]).order_by('pk')
+[<Publisher: Apress>, <Publisher: Sams>, <Publisher: Prentice Hall>, <Publisher: Morgan Kaufmann>, <Publisher: Expensive Publisher>]
+
+>>> Publisher.objects.annotate(num_books=Count('book')).filter(num_books__range=[1, 2]).order_by('pk')
+[<Publisher: Apress>, <Publisher: Sams>, <Publisher: Prentice Hall>, <Publisher: Morgan Kaufmann>]
+
+>>> Publisher.objects.annotate(num_books=Count('book')).filter(num_books__in=[1, 3]).order_by('pk')
+[<Publisher: Sams>, <Publisher: Morgan Kaufmann>, <Publisher: Expensive Publisher>]
+
+>>> Publisher.objects.annotate(num_books=Count('book')).filter(num_books__isnull=True)
+[]
+
+>>> p.delete()
+
+# Does Author X have any friends? (or better, how many friends does author X have)
+>> Author.objects.filter(pk=1).aggregate(Count('friends__id'))
+{'friends__id__count': 2.0}
+
+# Give me a list of all Books with more than 1 authors
+>>> Book.objects.all().annotate(num_authors=Count('authors__name')).filter(num_authors__ge=2).order_by('pk')
+[<Book: The Definitive Guide to Django: Web Development Done Right>, <Book: Artificial Intelligence: A Modern Approach>]
+
+# Give me a list of all Authors that have no friends
+>>> Author.objects.all().annotate(num_friends=Count('friends__id', distinct=True)).filter(num_friends=0).order_by('pk')
+[<Author: Brad Dayley>]
+
+# Give me a list of all publishers that have published more than 1 books
+>>> Publisher.objects.all().annotate(num_books=Count('book__id')).filter(num_books__gt=1).order_by('pk')
+[<Publisher: Apress>, <Publisher: Prentice Hall>]
+
+# Give me a list of all publishers that have published more than 1 books that cost less than 40
+>>> Publisher.objects.all().filter(book__price__lt=Decimal("40.0")).annotate(num_books=Count('book__id')).filter(num_books__gt=1)
+[<Publisher: Apress>]
+
+# Give me a list of all Books that were written by X and one other author.
+>>> Book.objects.all().annotate(num_authors=Count('authors__id')).filter(authors__name__contains='Norvig', num_authors__gt=1)
+[<Book: Artificial Intelligence: A Modern Approach>]
+
+# Give me the average rating of all Books that were written by X and one other author.
+#(Aggregate over objects discovered using membership of the m2m set)
+
+# Adding an existing author to another book to test it the right way
+>>> a = Author.objects.get(name__contains='Norvig')
+>>> b = Book.objects.get(name__contains='Done Right')
+>>> b.authors.add(a)
+>>> b.save()
+
+# This should do it
+>>> Book.objects.all().annotate(num_authors=Count('authors__id')).filter(authors__name__contains='Norvig', num_authors__gt=1).aggregate(Avg('rating'))
+{'rating__avg': 4.25}
+>>> b.authors.remove(a)
+
+# Give me a list of all Authors that have published a book with at least one other person
+# (Filters over a count generated on a related object)
+#
+# Cheating: [a for a in Author.objects.all().annotate(num_coleagues=Count('book__authors__id'), num_books=Count('book__id', distinct=True)) if a.num_coleagues - a.num_books > 0]
+# F-Syntax is required. Will be fixed after F objects are available
+
+# Tests on fields with non-default table and column names.
+>>> Clues.objects.values('EntryID__Entry').annotate(Appearances=Count('EntryID'), Distinct_Clues=Count('Clue', distinct=True))
+[]
+
+# Aggregates also work on dates, times and datetimes
+>>> Publisher.objects.annotate(earliest_book=Min('book__pubdate')).order_by('earliest_book').values()
+[{'earliest_book': datetime.date(1991, 10, 15), 'num_awards': 9, 'id': 4, 'name': u'Morgan Kaufmann'}, {'earliest_book': datetime.date(1995, 1, 15), 'num_awards': 7, 'id': 3, 'name': u'Prentice Hall'}, {'earliest_book': datetime.date(2007, 12, 6), 'num_awards': 3, 'id': 1, 'name': u'Apress'}, {'earliest_book': datetime.date(2008, 3, 3), 'num_awards': 1, 'id': 2, 'name': u'Sams'}]
+
+>>> Store.objects.aggregate(Max('friday_night_closing'), Min("original_opening"))
+{'friday_night_closing__max': datetime.time(23, 59, 59), 'original_opening__min': datetime.datetime(1945, 4, 25, 16, 24, 14)}
+
+# values_list() can also be used
+
+>>> Book.objects.filter(pk=1).annotate(mean_age=Avg('authors__age')).values_list('pk', 'isbn', 'mean_age')
+[(1, u'159059725', 34.5)]
+
+>>> Book.objects.filter(pk=1).annotate(mean_age=Avg('authors__age')).values_list('isbn')
+[(u'159059725',)]
+
+>>> Book.objects.filter(pk=1).annotate(mean_age=Avg('authors__age')).values_list('mean_age')
+[(34.5,)]
+
+>>> Book.objects.filter(pk=1).annotate(mean_age=Avg('authors__age')).values_list('mean_age', flat=True)
+[34.5]
+
+"""}