import datetime
import pickle
from decimal import Decimal
from operator import attrgetter
from django.conf import settings
from django.core.exceptions import FieldError
from django.db import DEFAULT_DB_ALIAS
from django.db.models import Count, Max, Avg, Sum, StdDev, Variance, F
from django.test import TestCase, Approximate
from models import Author, Book, Publisher, Clues, Entries, HardbackBook
def run_stddev_tests():
"""Check to see if StdDev/Variance tests should be run.
Stddev and Variance are not guaranteed to be available for SQLite, and
are not available for PostgreSQL before 8.2.
"""
if settings.DATABASES[DEFAULT_DB_ALIAS]['ENGINE'] == 'django.db.backends.sqlite3':
return False
class StdDevPop(object):
sql_function = 'STDDEV_POP'
try:
connection.ops.check_aggregate_support(StdDevPop())
except:
return False
return True
class AggregationTests(TestCase):
def assertObjectAttrs(self, obj, **kwargs):
for attr, value in kwargs.iteritems():
self.assertEqual(getattr(obj, attr), value)
def test_aggregates_in_where_clause(self):
"""
Regression test for #12822: DatabaseError: aggregates not allowed in
WHERE clause
Tests that the subselect works and returns results equivalent to a
query with the IDs listed.
Before the corresponding fix for this bug, this test passed in 1.1 and
failed in 1.2-beta (trunk).
"""
qs = Book.objects.values('contact').annotate(Max('id'))
qs = qs.order_by('contact').values_list('id__max', flat=True)
# don't do anything with the queryset (qs) before including it as a
# subquery
books = Book.objects.order_by('id')
qs1 = books.filter(id__in=qs)
qs2 = books.filter(id__in=list(qs))
self.assertEqual(list(qs1), list(qs2))
def test_aggregates_in_where_clause_pre_eval(self):
"""
Regression test for #12822: DatabaseError: aggregates not allowed in
WHERE clause
Same as the above test, but evaluates the queryset for the subquery
before it's used as a subquery.
Before the corresponding fix for this bug, this test failed in both
1.1 and 1.2-beta (trunk).
"""
qs = Book.objects.values('contact').annotate(Max('id'))
qs = qs.order_by('contact').values_list('id__max', flat=True)
# force the queryset (qs) for the subquery to be evaluated in its
# current state
list(qs)
books = Book.objects.order_by('id')
qs1 = books.filter(id__in=qs)
qs2 = books.filter(id__in=list(qs))
self.assertEqual(list(qs1), list(qs2))
if settings.DATABASES[DEFAULT_DB_ALIAS]['ENGINE'] != 'django.db.backends.oracle':
def test_annotate_with_extra(self):
"""
Regression test for #11916: Extra params + aggregation creates
incorrect SQL.
"""
#oracle doesn't support subqueries in group by clause
shortest_book_sql = """
SELECT name
FROM aggregation_regress_book b
WHERE b.publisher_id = aggregation_regress_publisher.id
ORDER BY b.pages
LIMIT 1
"""
# tests that this query does not raise a DatabaseError due to the full
# subselect being (erroneously) added to the GROUP BY parameters
qs = Publisher.objects.extra(select={
'name_of_shortest_book': shortest_book_sql,
}).annotate(total_books=Count('book'))
# force execution of the query
list(qs)
def test_aggregate(self):
# Ordering requests are ignored
self.assertEqual(
Author.objects.order_by("name").aggregate(Avg("age")),
{"age__avg": Approximate(37.444, places=1)}
)
# Implicit ordering is also ignored
self.assertEqual(
Book.objects.aggregate(Sum("pages")),
{"pages__sum": 3703},
)
# Baseline results
self.assertEqual(
Book.objects.aggregate(Sum('pages'), Avg('pages')),
{'pages__sum': 3703, 'pages__avg': Approximate(617.166, places=2)}
)
# Empty values query doesn't affect grouping or results
self.assertEqual(
Book.objects.values().aggregate(Sum('pages'), Avg('pages')),
{'pages__sum': 3703, 'pages__avg': Approximate(617.166, places=2)}
)
# Aggregate overrides extra selected column
self.assertEqual(
Book.objects.extra(select={'price_per_page' : 'price / pages'}).aggregate(Sum('pages')),
{'pages__sum': 3703}
)
def test_annotation(self):
# Annotations get combined with extra select clauses
obj = Book.objects.annotate(mean_auth_age=Avg("authors__age")).extra(select={"manufacture_cost": "price * .5"}).get(pk=2)
self.assertObjectAttrs(obj,
contact_id=3,
id=2,
isbn=u'067232959',
mean_auth_age=45.0,
name='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
)
# Different DB backends return different types for the extra select computation
self.assertTrue(obj.manufacture_cost == 11.545 or obj.manufacture_cost == Decimal('11.545'))
# Order of the annotate/extra in the query doesn't matter
obj = Book.objects.extra(select={'manufacture_cost' : 'price * .5'}).annotate(mean_auth_age=Avg('authors__age')).get(pk=2)
self.assertObjectAttrs(obj,
contact_id=3,
id=2,
isbn=u'067232959',
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
)
# Different DB backends return different types for the extra select computation
self.assertTrue(obj.manufacture_cost == 11.545 or obj.manufacture_cost == Decimal('11.545'))
# Values queries can be combined with annotate and extra
obj = Book.objects.annotate(mean_auth_age=Avg('authors__age')).extra(select={'manufacture_cost' : 'price * .5'}).values().get(pk=2)
manufacture_cost = obj['manufacture_cost']
self.assertTrue(manufacture_cost == 11.545 or manufacture_cost == Decimal('11.545'))
del obj['manufacture_cost']
self.assertEqual(obj, {
"contact_id": 3,
"id": 2,
"isbn": u"067232959",
"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,
})
# The order of the (empty) values, annotate and extra clauses doesn't
# matter
obj = Book.objects.values().annotate(mean_auth_age=Avg('authors__age')).extra(select={'manufacture_cost' : 'price * .5'}).get(pk=2)
manufacture_cost = obj['manufacture_cost']
self.assertTrue(manufacture_cost == 11.545 or manufacture_cost == Decimal('11.545'))
del obj['manufacture_cost']
self.assertEqual(obj, {
'contact_id': 3,
'id': 2,
'isbn': u'067232959',
'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
})
# If the annotation precedes the values clause, it won't be included
# unless it is explicitly named
obj = Book.objects.annotate(mean_auth_age=Avg('authors__age')).extra(select={'price_per_page' : 'price / pages'}).values('name').get(pk=1)
self.assertEqual(obj, {
"name": u'The Definitive Guide to Django: Web Development Done Right',
})
obj = Book.objects.annotate(mean_auth_age=Avg('authors__age')).extra(select={'price_per_page' : 'price / pages'}).values('name','mean_auth_age').get(pk=1)
self.assertEqual(obj, {
'mean_auth_age': 34.5,
'name': u'The Definitive Guide to Django: Web Development Done Right',
})
# If an annotation isn't included in the values, it can still be used
# in a filter
qs = Book.objects.annotate(n_authors=Count('authors')).values('name').filter(n_authors__gt=2)
self.assertQuerysetEqual(
qs, [
{"name": u'Python Web Development with Django'}
],
lambda b: b,
)
# The annotations are added to values output if values() precedes
# annotate()
obj = Book.objects.values('name').annotate(mean_auth_age=Avg('authors__age')).extra(select={'price_per_page' : 'price / pages'}).get(pk=1)
self.assertEqual(obj, {
'mean_auth_age': 34.5,
'name': u'The Definitive Guide to Django: Web Development Done Right',
})
# Check that all of the objects are getting counted (allow_nulls) and
# that values respects the amount of objects
self.assertEqual(
len(Author.objects.annotate(Avg('friends__age')).values()),
9
)
# Check that consecutive calls to annotate accumulate in the query
qs = Book.objects.values('price').annotate(oldest=Max('authors__age')).order_by('oldest', 'price').annotate(Max('publisher__num_awards'))
self.assertQuerysetEqual(
qs, [
{'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}
],
lambda b: b,
)
def test_aggrate_annotation(self):
# Aggregates can be composed over annotations.
# The return type is derived from the composed aggregate
vals = Book.objects.all().annotate(num_authors=Count('authors__id')).aggregate(Max('pages'), Max('price'), Sum('num_authors'), Avg('num_authors'))
self.assertEqual(vals, {
'num_authors__sum': 10,
'num_authors__avg': Approximate(1.666, places=2),
'pages__max': 1132,
'price__max': Decimal("82.80")
})
def test_field_error(self):
# Bad field requests in aggregates are caught and reported
self.assertRaises(
FieldError,
lambda: Book.objects.all().aggregate(num_authors=Count('foo'))
)
self.assertRaises(
FieldError,
lambda: Book.objects.all().annotate(num_authors=Count('foo'))
)
self.assertRaises(
FieldError,
lambda: Book.objects.all().annotate(num_authors=Count('authors__id')).aggregate(Max('foo'))
)
def test_more(self):
# Old-style count aggregations can be mixed with new-style
self.assertEqual(
Book.objects.annotate(num_authors=Count('authors')).count(),
6
)
# Non-ordinal, non-computed Aggregates over annotations correctly
# inherit the annotation's internal type if the annotation is ordinal
# or computed
vals = Book.objects.annotate(num_authors=Count('authors')).aggregate(Max('num_authors'))
self.assertEqual(
vals,
{'num_authors__max': 3}
)
vals = Publisher.objects.annotate(avg_price=Avg('book__price')).aggregate(Max('avg_price'))
self.assertEqual(
vals,
{'avg_price__max': 75.0}
)
# Aliases are quoted to protected aliases that might be reserved names
vals = Book.objects.aggregate(number=Max('pages'), select=Max('pages'))
self.assertEqual(
vals,
{'number': 1132, 'select': 1132}
)
# Regression for #10064: select_related() plays nice with aggregates
obj = Book.objects.select_related('publisher').annotate(num_authors=Count('authors')).values()[0]
self.assertEqual(obj, {
'contact_id': 8,
'id': 5,
'isbn': u'013790395',
'name': u'Artificial Intelligence: A Modern Approach',
'num_authors': 2,
'pages': 1132,
'price': Decimal("82.8"),
'pubdate': datetime.date(1995, 1, 15),
'publisher_id': 3,
'rating': 4.0,
})
# Regression for #10010: exclude on an aggregate field is correctly
# negated
self.assertEqual(
len(Book.objects.annotate(num_authors=Count('authors'))),
6
)
self.assertEqual(
len(Book.objects.annotate(num_authors=Count('authors')).filter(num_authors__gt=2)),
1
)
self.assertEqual(
len(Book.objects.annotate(num_authors=Count('authors')).exclude(num_authors__gt=2)),
5
)
self.assertEqual(
len(Book.objects.annotate(num_authors=Count('authors')).filter(num_authors__lt=3).exclude(num_authors__lt=2)),
2
)
self.assertEqual(
len(Book.objects.annotate(num_authors=Count('authors')).exclude(num_authors__lt=2).filter(num_authors__lt=3)),
2
)
def test_aggregate_fexpr(self):
# Aggregates can be used with F() expressions
# ... where the F() is pushed into the HAVING clause
qs = Publisher.objects.annotate(num_books=Count('book')).filter(num_books__lt=F('num_awards')/2).order_by('name').values('name','num_books','num_awards')
self.assertQuerysetEqual(
qs, [
{'num_books': 1, 'name': u'Morgan Kaufmann', 'num_awards': 9},
{'num_books': 2, 'name': u'Prentice Hall', 'num_awards': 7}
],
lambda p: p,
)
qs = Publisher.objects.annotate(num_books=Count('book')).exclude(num_books__lt=F('num_awards')/2).order_by('name').values('name','num_books','num_awards')
self.assertQuerysetEqual(
qs, [
{'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}
],
lambda p: p,
)
# ... and where the F() references an aggregate
qs = Publisher.objects.annotate(num_books=Count('book')).filter(num_awards__gt=2*F('num_books')).order_by('name').values('name','num_books','num_awards')
self.assertQuerysetEqual(
qs, [
{'num_books': 1, 'name': u'Morgan Kaufmann', 'num_awards': 9},
{'num_books': 2, 'name': u'Prentice Hall', 'num_awards': 7}
],
lambda p: p,
)
qs = Publisher.objects.annotate(num_books=Count('book')).exclude(num_books__lt=F('num_awards')/2).order_by('name').values('name','num_books','num_awards')
self.assertQuerysetEqual(
qs, [
{'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}
],
lambda p: p,
)
def test_db_col_table(self):
# Tests on fields with non-default table and column names.
qs = Clues.objects.values('EntryID__Entry').annotate(Appearances=Count('EntryID'), Distinct_Clues=Count('Clue', distinct=True))
self.assertQuerysetEqual(qs, [])
qs = Entries.objects.annotate(clue_count=Count('clues__ID'))
self.assertQuerysetEqual(qs, [])
def test_empty(self):
# Regression for #10089: Check handling of empty result sets with
# aggregates
self.assertEqual(
Book.objects.filter(id__in=[]).count(),
0
)
vals = 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'))
self.assertEqual(
vals,
{'max_authors': None, 'max_rating': None, 'num_authors': 0, 'avg_authors': None, 'max_price': None}
)
qs = 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()
self.assertQuerysetEqual(
qs, [
{'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}
],
lambda p: p
)
def test_more_more(self):
# Regression for #10113 - Fields mentioned in order_by() must be
# included in the GROUP BY. This only becomes a problem when the
# order_by introduces a new join.
self.assertQuerysetEqual(
Book.objects.annotate(num_authors=Count('authors')).order_by('publisher__name', 'name'), [
"Practical Django Projects",
"The Definitive Guide to Django: Web Development Done Right",
"Paradigms of Artificial Intelligence Programming: Case Studies in Common Lisp",
"Artificial Intelligence: A Modern Approach",
"Python Web Development with Django",
"Sams Teach Yourself Django in 24 Hours",
],
lambda b: b.name
)
# Regression for #10127 - Empty select_related() works with annotate
qs = Book.objects.filter(rating__lt=4.5).select_related().annotate(Avg('authors__age'))
self.assertQuerysetEqual(
qs, [
(u'Artificial Intelligence: A Modern Approach', 51.5, u'Prentice Hall', u'Peter Norvig'),
(u'Practical Django Projects', 29.0, u'Apress', u'James Bennett'),
(u'Python Web Development with Django', Approximate(30.333, places=2), u'Prentice Hall', u'Jeffrey Forcier'),
(u'Sams Teach Yourself Django in 24 Hours', 45.0, u'Sams', u'Brad Dayley')
],
lambda b: (b.name, b.authors__age__avg, b.publisher.name, b.contact.name)
)
# Regression for #10132 - If the values() clause only mentioned extra
# (select=) columns, those columns are used for grouping
qs = Book.objects.extra(select={'pub':'publisher_id'}).values('pub').annotate(Count('id')).order_by('pub')
self.assertQuerysetEqual(
qs, [
{'pub': 1, 'id__count': 2},
{'pub': 2, 'id__count': 1},
{'pub': 3, 'id__count': 2},
{'pub': 4, 'id__count': 1}
],
lambda b: b
)
qs = Book.objects.extra(select={'pub':'publisher_id', 'foo':'pages'}).values('pub').annotate(Count('id')).order_by('pub')
self.assertQuerysetEqual(
qs, [
{'pub': 1, 'id__count': 2},
{'pub': 2, 'id__count': 1},
{'pub': 3, 'id__count': 2},
{'pub': 4, 'id__count': 1}
],
lambda b: b
)
# Regression for #10182 - Queries with aggregate calls are correctly
# realiased when used in a subquery
ids = Book.objects.filter(pages__gt=100).annotate(n_authors=Count('authors')).filter(n_authors__gt=2).order_by('n_authors')
self.assertQuerysetEqual(
Book.objects.filter(id__in=ids), [
"Python Web Development with Django",
],
lambda b: b.name
)
def test_duplicate_alias(self):
# Regression for #11256 - duplicating a default alias raises ValueError.
self.assertRaises(ValueError, Book.objects.all().annotate, Avg('authors__age'), authors__age__avg=Avg('authors__age'))
def test_field_name_conflict(self):
# Regression for #11256 - providing an aggregate name that conflicts with a field name on the model raises ValueError
self.assertRaises(ValueError, Author.objects.annotate, age=Avg('friends__age'))
def test_m2m_name_conflict(self):
# Regression for #11256 - providing an aggregate name that conflicts with an m2m name on the model raises ValueError
self.assertRaises(ValueError, Author.objects.annotate, friends=Count('friends'))
def test_reverse_relation_name_conflict(self):
# Regression for #11256 - providing an aggregate name that conflicts with a reverse-related name on the model raises ValueError
self.assertRaises(ValueError, Author.objects.annotate, book_contact_set=Avg('friends__age'))
def test_pickle(self):
# Regression for #10197 -- Queries with aggregates can be pickled.
# First check that pickling is possible at all. No crash = success
qs = Book.objects.annotate(num_authors=Count('authors'))
pickle.dumps(qs)
# Then check that the round trip works.
query = qs.query.get_compiler(qs.db).as_sql()[0]
qs2 = pickle.loads(pickle.dumps(qs))
self.assertEqual(
qs2.query.get_compiler(qs2.db).as_sql()[0],
query,
)
def test_more_more_more(self):
# Regression for #10199 - Aggregate calls clone the original query so
# the original query can still be used
books = Book.objects.all()
books.aggregate(Avg("authors__age"))
self.assertQuerysetEqual(
books.all(), [
u'Artificial Intelligence: A Modern Approach',
u'Paradigms of Artificial Intelligence Programming: Case Studies in Common Lisp',
u'Practical Django Projects',
u'Python Web Development with Django',
u'Sams Teach Yourself Django in 24 Hours',
u'The Definitive Guide to Django: Web Development Done Right'
],
lambda b: b.name
)
# Regression for #10248 - Annotations work with DateQuerySets
qs = Book.objects.annotate(num_authors=Count('authors')).filter(num_authors=2).dates('pubdate', 'day')
self.assertQuerysetEqual(
qs, [
datetime.datetime(1995, 1, 15, 0, 0),
datetime.datetime(2007, 12, 6, 0, 0)
],
lambda b: b
)
# Regression for #10290 - extra selects with parameters can be used for
# grouping.
qs = Book.objects.annotate(mean_auth_age=Avg('authors__age')).extra(select={'sheets' : '(pages + %s) / %s'}, select_params=[1, 2]).order_by('sheets').values('sheets')
self.assertQuerysetEqual(
qs, [
150,
175,
224,
264,
473,
566
],
lambda b: int(b["sheets"])
)
# Regression for 10425 - annotations don't get in the way of a count()
# clause
self.assertEqual(
Book.objects.values('publisher').annotate(Count('publisher')).count(),
4
)
self.assertEqual(
Book.objects.annotate(Count('publisher')).values('publisher').count(),
6
)
publishers = Publisher.objects.filter(id__in=[1, 2])
self.assertQuerysetEqual(
publishers, [
"Apress",
"Sams"
],
lambda p: p.name
)
publishers = publishers.annotate(n_books=Count("book"))
self.assertEqual(
publishers[0].n_books,
2
)
self.assertQuerysetEqual(
publishers, [
"Apress",
"Sams",
],
lambda p: p.name
)
books = Book.objects.filter(publisher__in=publishers)
self.assertQuerysetEqual(
books, [
"Practical Django Projects",
"Sams Teach Yourself Django in 24 Hours",
"The Definitive Guide to Django: Web Development Done Right",
],
lambda b: b.name
)
self.assertQuerysetEqual(
publishers, [
"Apress",
"Sams",
],
lambda p: p.name
)
# Regression for 10666 - inherited fields work with annotations and
# aggregations
self.assertEqual(
HardbackBook.objects.aggregate(n_pages=Sum('book_ptr__pages')),
{'n_pages': 2078}
)
self.assertEqual(
HardbackBook.objects.aggregate(n_pages=Sum('pages')),
{'n_pages': 2078},
)
qs = HardbackBook.objects.annotate(n_authors=Count('book_ptr__authors')).values('name', 'n_authors')
self.assertQuerysetEqual(
qs, [
{'n_authors': 2, 'name': u'Artificial Intelligence: A Modern Approach'},
{'n_authors': 1, 'name': u'Paradigms of Artificial Intelligence Programming: Case Studies in Common Lisp'}
],
lambda h: h
)
qs = HardbackBook.objects.annotate(n_authors=Count('authors')).values('name', 'n_authors')
self.assertQuerysetEqual(
qs, [
{'n_authors': 2, 'name': u'Artificial Intelligence: A Modern Approach'},
{'n_authors': 1, 'name': u'Paradigms of Artificial Intelligence Programming: Case Studies in Common Lisp'}
],
lambda h: h,
)
# Regression for #10766 - Shouldn't be able to reference an aggregate
# fields in an an aggregate() call.
self.assertRaises(
FieldError,
lambda: Book.objects.annotate(mean_age=Avg('authors__age')).annotate(Avg('mean_age'))
)
def test_empty_filter_count(self):
self.assertEqual(
Author.objects.filter(id__in=[]).annotate(Count("friends")).count(),
0
)
def test_empty_filter_aggregate(self):
self.assertEqual(
Author.objects.filter(id__in=[]).annotate(Count("friends")).aggregate(Count("pk")),
{"pk__count": None}
)
def test_annotate_and_join(self):
self.assertEqual(
Author.objects.annotate(c=Count("friends__name")).exclude(friends__name="Joe").count(),
Author.objects.count()
)
def test_f_expression_annotation(self):
# Books with less than 200 pages per author.
qs = Book.objects.values("name").annotate(
n_authors=Count("authors")
).filter(
pages__lt=F("n_authors") * 200
).values_list("pk")
self.assertQuerysetEqual(
Book.objects.filter(pk__in=qs), [
"Python Web Development with Django"
],
attrgetter("name")
)
def test_values_annotate_values(self):
qs = Book.objects.values("name").annotate(
n_authors=Count("authors")
).values_list("pk", flat=True)
self.assertEqual(list(qs), list(Book.objects.values_list("pk", flat=True)))
def test_having_group_by(self):
# Test that when a field occurs on the LHS of a HAVING clause that it
# appears correctly in the GROUP BY clause
qs = Book.objects.values_list("name").annotate(
n_authors=Count("authors")
).filter(
pages__gt=F("n_authors")
).values_list("name", flat=True)
# Results should be the same, all Books have more pages than authors
self.assertEqual(
list(qs), list(Book.objects.values_list("name", flat=True))
)
if run_stddev_tests():
def test_stddev(self):
self.assertEqual(
Book.objects.aggregate(StdDev('pages')),
{'pages__stddev': Approximate(311.46, 1)}
)
self.assertEqual(
Book.objects.aggregate(StdDev('rating')),
{'rating__stddev': Approximate(0.60, 1)}
)
self.assertEqual(
Book.objects.aggregate(StdDev('price')),
{'price__stddev': Approximate(24.16, 2)}
)
self.assertEqual(
Book.objects.aggregate(StdDev('pages', sample=True)),
{'pages__stddev': Approximate(341.19, 2)}
)
self.assertEqual(
Book.objects.aggregate(StdDev('rating', sample=True)),
{'rating__stddev': Approximate(0.66, 2)}
)
self.assertEqual(
Book.objects.aggregate(StdDev('price', sample=True)),
{'price__stddev': Approximate(26.46, 1)}
)
self.assertEqual(
Book.objects.aggregate(Variance('pages')),
{'pages__variance': Approximate(97010.80, 1)}
)
self.assertEqual(
Book.objects.aggregate(Variance('rating')),
{'rating__variance': Approximate(0.36, 1)}
)
self.assertEqual(
Book.objects.aggregate(Variance('price')),
{'price__variance': Approximate(583.77, 1)}
)
self.assertEqual(
Book.objects.aggregate(Variance('pages', sample=True)),
{'pages__variance': Approximate(116412.96, 1)}
)
self.assertEqual(
Book.objects.aggregate(Variance('rating', sample=True)),
{'rating__variance': Approximate(0.44, 2)}
)
self.assertEqual(
Book.objects.aggregate(Variance('price', sample=True)),
{'price__variance': Approximate(700.53, 2)}
)