1.
The effective use of
Django ORM
Yaroslav Muravskyi
@myarik

2.
What we’re going to talk about
- Django ORM Mistakes
- Performance Problems in the Django ORM
- Database concurrency in Django the right way

3.
What is Django ORM?
ORM - Object-relational mapping
Django's ORM is just a pythonical way to create
SQL to query and manipulate your database and get
results in a pythonic fashion.

4.
The first step to fixing a problem
is being able to identify it

5.
Tools

6.
Tools
• django.db.connection (Make sure your Django
DEBUG setting is set to True)

7.
Tools
• django.db.connection (Make sure your Django
DEBUG setting is set to True)
>>> from django.db import connection
>>> Author.objects.all()
<QuerySet [<Author: Michael Armstrong>, ..., <Author: GEORGE PACKER>]>
>>> connection.queries
[{'sql': 'SELECT "books_author"."id", "books_author"."first_name",
"books_author"."last_name", "books_author"."email" FROM "books_author" LIMIT 21',
'time': '0.007'}]

8.
Tools
• django.db.connection (Make sure your Django
DEBUG setting is set to True)
>>> from django.db import connection
>>> Author.objects.all()
<QuerySet [<Author: Michael Armstrong>, ..., <Author: GEORGE PACKER>]>
>>> connection.queries
[{'sql': 'SELECT "books_author"."id", "books_author"."first_name",
"books_author"."last_name", "books_author"."email" FROM "books_author" LIMIT 21',
'time': '0.007'}]
• sql -- The raw SQL statement
• time -- How long the statement took to execute, in seconds.

9.
Tools
• shell_plus command with option --print-sql
from django-extensions project

10.
Tools
• shell_plus command with option --print-sql
from django-extensions project
>>> Author.objects.all()
SELECT "books_author"."id", "books_author"."first_name",
"book_author"."last_name","books_author"."email" FROM "books_author" LIMIT
21
Execution time: 0.001993s [Database: default]

11.
Tools
• Django Debug Toolbar

12.
Django ORM Mistakes

13.
Mistake #1
>>> queryset = Author.objects.all()
>>> [author for author in queryset if author.email.endswith('@gmail.com')]

14.
Mistake #1
Use filter() and exclude() method to do
filtering in the database.
>>> Author.objects.filter(email__icontains='@gmail.com')
>>> queryset = Author.objects.all()
>>> [author for author in queryset if author.email.endswith('@gmail.com')]

15.
Mistake #2
authors = Author.objects.filter(email__icontains='@gmail.com')
if authors:
do_stuff()
if len(authors) > 0:
do_stuff()

16.
Mistake #2
If you want to know only if a record exists,
then use exists() method
Author.objects.filter(email__icontains='@gmail.com').exists()
authors = Author.objects.filter(email__icontains='@gmail.com')
if authors:
do_stuff()
if len(authors) > 0:
do_stuff()

17.
Mistake #3
authors = Author.objects.filter(email__icontains='@gmail.com')
if len(authors) > 5:
do_stuff()

18.
Mistake #3
authors = Author.objects.filter(email__icontains='@gmail.com')
if len(authors) > 5:
do_stuff()
If you need only the size use count()
count = Author.objects.filter(email__icontains='@gmail.com').count()
if count > 5:
do_stuff()

19.
Mistake #4
book = Book.objects.get(id=5)
if book.author:
do_stuff()

20.
Mistake #4
book = Book.objects.get(id=5)
if book.author:
do_stuff()
Use foreign key values directly
# If you don't need the author object
if book.author_id:
do_stuff()
Additional request to the database

21.
Mistake #5
Don’t fetch data you don’t need
# Retrieve values as a dictionary
Book.objects.all().values('name', 'price')
< QuerySet[{'name': 'Rat Of The Stockades', 'price': Decimal('4.28')}, ...] >
# Retrieve values as a tuple
Book.objects.all().values_list('name', 'price')
< QuerySet[('Rat Of The Stockades', Decimal('4.28')), ...] >
# Use QuerySet.defer() and only()
Book.objects.only('name', 'price').all()
Book.objects.defer('price').all()

22.
Mistake #6
for book in Book.objects.all():
do_stuff(book)

23.
Mistake #6
for book in Book.objects.all():
do_stuff(book)
When you have a lot of objects, the caching
behavior of the QuerySet can cause a large
amount of memory to be used.
# One book object in the memory
for book in Book.objects.iterator():
do_stuff(book)

24.
Mistake #7
def create():
with transaction.atomic():
item = Author.objects.create(first_name='Simon', last_name='Anderson',
email='fake@mail.com')
set_email(item.id)
item.books_count= 3
item.save()
def set_email(id):
item = Author.objects.get(id=id)
item.email = 'simon@gmail.com'
item.save()

25.
Mistake #7
def create():
with transaction.atomic():
item = Author.objects.create(first_name='Simon', last_name='Anderson',
email='fake@mail.com')
set_email(item.id)
# The database row has been updated with email='simon@gmail.com', but this
instance still has email='fake@mail.com' as it hasn't been reloaded
item.books_count= 3
item.save()
def set_email(id):
item = Author.objects.get(id=id)
item.email = 'simon@gmail.com'
item.save()

26.
Mistake #7
def create():
with transaction.atomic():
item = Author.objects.create(first_name='Simon', last_name='Anderson',
email='fake@mail.com')
set_email(item)
item.books_count= 3
item.save()
def set_email(item):
item.email = 'simon@gmail.com'
item.save()

27.
Performance Problems in
the Django ORM

28.
Avoid unnecessary queries when
accessing foreign keys
Use the select_related method to load
the foreign key values and cache those results
for each object
# N + 1 query
for book in Book.objects.iterator():
print(book.name, book.author.get_full_name())
# 1 query
for book in Book.objects.select_related('author').iterator():
print(book.name, book.author.get_full_name())

29.
prefetch_related
# Queries 2, Execution time: 0.002458s
def authors():
queryset = Author.objects.prefetch_related('books')
authors = []
for author in queryset:
books = [book.name for book in author.books.all()]
authors.append({
'name': author.get_full_name(),
'books': books
})
return authors
Use the prefetch_related for joining many-to-
many and many-to-one objects

30.
Be careful with prefetch_related
# Queries 18, Execution time: 0.032458s
def top_authors():
queryset = Author.objects.prefetch_related('books')
authors = []
for author in queryset:
books = [book.name for book in author.books.filter(average_rating__gt=3)]
authors.append({
'name': author.get_full_name(),
'books': books
})
return authors

31.
Using Prefetch with to_attr
from django.db.modelsimport Prefetch
# Queries 2, Execution time: 0.008458s
def top_authors():
queryset = Author.objects.prefetch_related(
Prefetch('books',
queryset=Book.objects.filter(average_rating__gt=3),
to_attr='top_books')
)
authors = []
for author in queryset:
books = [book.name for book in author.top_books]
authors.append({'name': author.get_full_name(), 'books': books})
return authors

32.
Subqueries and Annotations
Subqueries and annotations can speed
up to 50 times your application.
Task:
Display the list of authors name and
the count of books for each author.

33.
Subqueries and Annotations
Instead of concatenating name in Python
class Author(models.Model):
...
def get_full_name(self):
return '%s %s' % (self.first_name, self.last_name)
We can concatenate name in a database
from django.db.modelsimport Value
from django.db.models.functionsimport Concat
Author.objects.annotate(
name=Concat('first_name', Value(' '), 'last_name')
).values('name', )

34.
Subqueries and Annotations
from django.db.modelsimport OuterRef, Subquery, Value, IntegerField
from django.db.models.functionsimport Concat
def get_authors():
book_query= Book.objects.filter(
author_id=OuterRef('id')
).values('author_id').order_by().annotate(
books=Count('*')).values('books')
return Author.objects.annotate(
name=Concat('first_name', Value(' '), 'last_name'),
count_books=Subquery(book_query, output_field=IntegerField())
).values('name', 'count_books')

35.
Case
A Case() expression is like the if … elif … else statement in Python
from django.db.modelsimport CharField, Case, Value, When
# Get the discount for each Book based on the rating value
def get_authors():
Book.objects.annotate(
discount=Case(
When(average_rating__gte=4, then=Value('10%')),
When(average_rating__gte=2, then=Value('5%')),
default=Value('0%'),
output_field=CharField(),
)
)

36.
Aggregation with Filter
from django.db.modelsimport Count, Case, Value, When, Sum, IntegerField
Book.objects.aggregate(
total_books=Count('id'),
total_platinum_discount=Sum(Case(
When(average_rating__gte=4, then=Value(1)),
default=Value(0),
output_field=IntegerField(),
))
)
Conditional expressions

37.
Aggregation with Filter
from django.db.modelsimport Count, Q
Book.objects.aggregate(
total_books=Count('id'),
total_platinum_discount=Count('id', filter=Q(average_rating__gte=4))
)
In Django 2.0 a filter argument to aggregate
functions was added to make this a lot easier

38.
Database concurrency in
Django the right way

39.
Specifying which fields to save
def set_name(id, value):
instance = Book.objects.get(id=id)
instance.name = value
instance.save()
def set_rating(id, value):
instance = Book.objects.get(id=id)
instance.average_rating = value
instance.save()
What happens if the set_name and set_rating
will run simultaneously?

40.
Specifying which fields to save

41.
Specifying which fields to save
def set_name(id, value):
instance = Book.objects.get(id=id)
instance.name = value
instance.save(update_fields=['name'])
def set_rating(id, value):
instance = Book.objects.get(id=id)
instance.average_rating = value
instance.save(update_fields=['average_rating'])
One possible solution is to identify the
updated fields

42.
Use an F() expression to simple
arithmetic tasks
book = Book.objects.get(pk=804)
book.count+= 1
book.save()

43.
Use an F() expression to simple
arithmetic tasks
book = Book.objects.get(pk=804)
book.count= F('count') + 1
book.save()

44.
Use an F() expression to simple
arithmetic tasks
book = Book.objects.get(pk=804)
book.count= F('count') + 1
book.save()
But take care with this kind of assignment.
Avoiding race conditions using F()
book = Book.objects.get(pk=804) # count = 10
book.count= F('count') + 1
book.save() # count = 11
book.name = 'Avoiding race conditions'
book.save() # count = 12

45.
The code
def create_payment(collection_id):
with transaction.atomic():
book_collection = BookCollection.objects.select_releted('user').get(id=collection_id)
amount = book_collection.book_set.all().aggregate(total=Sum('price'))['total']
if book_collection.user.balance>= amount:
user.reduce_balance(amount)
Payment.objects.create(amount=amount, book_collection=book_collection)
else:
raise Exception('Insufficient funds')

46.
What happens if there are two
simultaneous requests?

47.
Select for update
SELECT FOR UPDATE returns a queryset that
will lock rows until the end of the
transaction

48.
Select for update

49.
def create_payment(collection_id):
# Wrap in a database transaction
with transaction.atomic():
book_collection = BookCollection.objects.get(id=collection_id)
amount = book_collection.book_set.all().aggregate(total=Sum('price'))['total']
# Wait for a lock
user = User.objects.select_for_update().get(id=book_collection.user_id)
if user.balance >= amount:
user.reduce_balance(amount)
Payment.objects.create(amount=amount, book_collection=book_collection)
else:
raise Exception('Insufficient funds')
Select for update

50.
with transaction.atomic():
User.objects.select_for_update().filter(id__in=[804, 806])
...
Select for update – Querysets are
lazy!
In this case, the select_for_update will never
be run. Wrap the select_for_update in a bool if
you don't evaluate them straight away.
bool(User.objects.select_for_update().filter(id__in=[804, 806]))

51.
Select for update – Preventing
deadlocks
# Worker 1
with transaction.atomic():
ids = [804, 805]
bool(User.objects.select_for_update().filter(id__in=ids))
...
# Worker 2
with transaction.atomic():
ids = [805, 804]
bool(User.objects.select_for_update().filter(id__in=ids))
...
Waiting for each other

52.
Select for update – Preventing
deadlocks
When using select_for_updates on multiple
records, make sure you acquire the locks in a
consistent order.
# Worker 1
with transaction.atomic():
ids = [804, 805]
bool(User.objects.select_for_update().filter(id__in=ids).order_by('id'))
...

53.
- Make your code clear and then work on optimizing
it
- Learn how to use the Django ORM properly to get
the most out of it
- Database concurrency is something you need to
think about
- ORMs can obscure bugs. Look at the SQL
Summary

54.
Thanks!
@myarik
y@myarik.com