Django ORM Cheatsheet

If you wanted to read a lot of text you'd be reading the Django docs, especially these pages:

But you don't want that, so you're here. I'll get to the point.

Our models

from datetime import date

from django.db import models


class Blog(models.Model):
    name = models.CharField(max_length=100)
    tagline = models.TextField()

    def __str__(self):
        return self.name


class Author(models.Model):
    name = models.CharField(max_length=200)
    email = models.EmailField()

    def __str__(self):
        return self.name


class Entry(models.Model):
    blog = models.ForeignKey(Blog, on_delete=models.CASCADE)
    headline = models.CharField(max_length=255)
    body_text = models.TextField()
    pub_date = models.DateField()
    mod_date = models.DateField(default=date.today)
    authors = models.ManyToManyField(Author)
    number_of_comments = models.IntegerField(default=0)
    number_of_pingbacks = models.IntegerField(default=0)
    rating = models.IntegerField(default=5)

    def __str__(self):
        return self.headline

Starting point

Entry.objects.all()

# SELECT "blog_entry"."id", "blog_entry"."blog_id", ...
# FROM "blog_entry" ...;

# [<Entry: Off foot official kitchen another turn.>,
#  <Entry: Yet year marriage yes her she.>,
#  <Entry: Special mission in who son sort.>,
#  ...
# ]

Make fewer queries

These are the biggest bang for your buck. Use them often.

`select_related()`

*-to-one relationships (one-to-one, many-to-one)

without `select_related()`

entry = Entry.objects.first()
# SELECT ... FROM "blog_entry" ...;

# this attribute access runs a second query
blog = entry.blog
# SELECT ... FROM "blog_blog" WHERE ...;

with `select_related()`

entry = Entry.objects.select_related("blog").first()
# SELECT "blog_entry"."id", ... "blog_blog"."id", ...
# FROM "blog_entry"
# INNER JOIN "blog_blog" ...;

blog = entry.blog
# no query is run because we JOINed with the blog table above

`prefetch_related()`

*-to-many relationships (one-to-many, many-to-many)

without `prefetch_related()`

entry = Entry.objects.first()
# SELECT ... FROM "blog_entry" ...;

# this related query hits the database again
authors = list(entry.authors.all())
# SELECT ...
# FROM "blog_author" INNER JOIN "blog_entry_authors"...
# WHERE "blog_entry_authors"."entry_id" = 4137;

with `prefetch_related()`

entry = Entry.objects.prefetch_related("authors").first()
# SELECT ... FROM "blog_entry" ...;
# SELECT ...
# FROM "blog_author" INNER JOIN "blog_entry_authors" ...
# WHERE "blog_entry_authors"."entry_id" IN (4137);

authors = list(entry.authors.all())
# no query is run because we have an in-memory
# lookup of the relevant authors from above

`update()`

without `update()`

david = (
    Author.objects.filter(name__startswith="David")
    .prefetch_related("entry_set")
    .first()
)
# SELECT ... FROM "blog_author" WHERE "blog_author"."name" LIKE 'David%' ...;
# SELECT ... FROM "blog_entry" INNER JOIN "blog_entry_authors" ...;

# There are many ineffcient ways to update all of David's entries.
# This is one of them.
for entry in david.entry_set.all():
    entry.rating = 5
    entry.save()
# One query for each Entry. Even if we used bulk_update(),
# we're still making more queries than we need.

with `update()`

Entry.objects.filter(authors__name__startswith="David").update(rating=5)
# UPDATE "blog_entry" SET "rating" = 5 WHERE "blog_entry"."id" IN ...;

Query things other than columns, AKA do your work in the DB, not in Python

`annotate()` (first look)

annotate() adds an attribute to each row of the result. Use this with F() to add one field from a related object (this makes more sense when you have objects separated by a long chain of relations).

annotate() is very powerful and makes sense to use in many situations, so just bear with this first unrealistic example.

entries = Entry.objects.annotate(blog_name=F("blog__name"))[:5]
# SELECT "blog_entry"."id", ... "blog_blog"."name" AS "blog_name"
# FROM "blog_entry" INNER JOIN "blog_blog" ...;

# Now we have Entry objects with one extra attribute: blog_name
[entry.blog_name for entry in entries]
# ['Hunter-Rhodes',
#  'Mcneil PLC',
#  'Banks, Hicks and Carpenter',
#  'Anderson PLC',
#  'George-Bray']

`filter()` and `Q()`

Use Q() to do more filtering in the database, and less in your application.

low_engagement_posts = Entry.objects.filter(
    Q(number_of_comments__lt=20) | Q(number_of_pingbacks__lt=20)
)

list(low_engagement_posts)
# SELECT ... FROM "blog_entry"
# WHERE
#   ("blog_entry"."number_of_comments" < 20 OR
#   "blog_entry"."number_of_pingbacks" < 20);

Query Expressions

Many parts of the Django ORM expect a query expression. Query expressions include:

references to fields (possibly on related objects) F()
SQL functions like CASE, NOW, etc.
Subqueries with Subquery()

`F()`

The classic example is an increment, but recall that F() can be used anywhere a query expression is required.

Entry.objects.filter(authors__name__startswith="David").first().rating
# 5

Entry.objects.filter(authors__name__startswith="David").update(
    rating=F("rating") - 1
)
# UPDATE "blog_entry"
#   SET "rating" = ("blog_entry"."rating" - 1) WHERE ...;

Entry.objects.filter(authors__name__startswith="David").first().rating
# 4

`CASE` and conditional logic

Django docs page

Value() below is a query expression for a string, integer, bool, etc. literal value. You could use F() or another expression as the then value or even in place of the rating= condition.

entries = Entry.objects.annotate(
    coolness=Case(
        When(rating=5, then=Value("super cool")),
        When(rating=4, then=Value("pretty cool")),
        default=Value("not cool"),
    )
)
# SELECT ...
# CASE
#   WHEN "blog_entry"."rating" = 5 THEN 'super cool'
#   WHEN "blog_entry"."rating" = 4 THEN 'pretty cool'
#   ELSE 'not cool'
# END AS "coolness"
# FROM "blog_entry" LIMIT 5;

[f"Entry {e.pk} is {e.coolness}" for e in entries[:5]]
# ['Entry 4137 is super cool',
#  'Entry 4138 is not cool',
#  'Entry 4139 is not cool',
#  'Entry 4140 is pretty cool',
#  'Entry 4141 is not cool']

`Subquery()` and `OuterRef()`

Annotate each blog with the headline of the most recent entry.

This pattern is the only use for Subquery() I have ever found: query a *-to-many relation, OuterRef("pk") to "join" the rows, use values() to return one column and [:1] to return one row from the subquery. This is basically a copy of the example in the Django docs.

blogs = Blog.objects.annotate(
    most_recent_headline=Subquery(
        Entry.objects.filter(blog=OuterRef("pk"))
        .order_by("-pub_date")
        .values("headline")[:1]
    )
)
[(blog, str(blog.most_recent_headline)) for blog in blogs[:5]]
# SELECT
#   "blog_blog"."id",
#   "blog_blog"."name",
#   "blog_blog"."tagline",
#   (
#     SELECT
#       U0."headline"
#     FROM
#       "blog_entry" U0
#     WHERE
#       U0."blog_id" = ("blog_blog"."id")
#     ORDER BY
#       U0."pub_date" DESC
#     LIMIT
#       1
#   ) AS "most_recent_headline"
# FROM
#   "blog_blog"
# LIMIT
#   5;


# [(<Blog: Robinson-Wilson>, 'Three space maintain subject much.'),
#  (<Blog: Anderson PLC>, 'Rock authority enjoy hundred reduce behavior.'),
#  (<Blog: Mcneil PLC>, 'Visit beyond base.'),
#  (<Blog: Smith, Baker and Rodriguez>, 'Tree look culture minute affect.'),
#  (<Blog: George-Bray>, 'Then produce tree quality top similar.')]

Select less data

`values()` (part 1)

Select the specified fields only, as dictionaries. You can also select annotations, like this:

Entry.objects.annotate(num_authors=Count("authors")).values(
    "rating", "num_authors"
)[:5]
# SELECT
#   "blog_entry"."rating",
#   COUNT("blog_entry_authors"."author_id") AS "num_authors"
# FROM "blog_entry" LEFT OUTER JOIN "blog_entry_authors" ...;

# [{'num_authors': 3, 'rating': 1},
#  {'num_authors': 4, 'rating': 4},
#  {'num_authors': 4, 'rating': 2},
#  {'num_authors': 3, 'rating': 2},
#  {'num_authors': 3, 'rating': 5}]

`exists()`

If you need a yes/no answer that something exists, this is faster than fetching the whole row.

unrealistic_data_exists = Entry.objects.filter(
    mod_date__lt=F("pub_date")
).exists()
# SELECT
#  (1) AS "a"
#   FROM "blog_entry"
#   WHERE "blog_entry"."mod_date" < ("blog_entry"."pub_date")
#   LIMIT 1;

unrealistic_data_exists
# True

`only()`

Like values(), but you get a model instance back instead of a dictionary. Be warned, though: you will make an extra DB query if you access any of the fields you didn't fetch originally.

Grouping data

`values()` (part 2) and `GROUP BY`

The Django docs contain this hidden gem:

"Ordinarily, annotations are generated on a per-object basis - an annotated QuerySet will return one result for each object in the original QuerySet. However, when a values() clause is used to constrain the columns that are returned in the result set... the original results are grouped according to the unique combinations of the fields specified in the values() clause. An annotation is then provided for each unique group; the annotation is computed over all members of the group."

The word "group" is in there because this is how you make a GROUP BY clause with Django's ORM. Very useful for reports.

Which day has the highest average blog entry rating?

[
    (str(e["pub_date"]), e["avg_rating"])
    for e in Entry.objects.values("pub_date").annotate(avg_rating=Avg("rating"))
]
# SELECT
#   "blog_entry"."pub_date",
#   AVG("blog_entry"."rating") AS "avg_rating"
# FROM "blog_entry"
# GROUP BY "blog_entry"."pub_date";

# [
#  ('2022-04-07', 2.235294117647059),
#  ('2022-04-08', 2.8157894736842106),
#  ('2022-04-09', 2.0285714285714285),
#  ('2022-04-10', 2.96875),
#  ('2022-04-11', 2.3636363636363638),
#  ('2022-04-12', 2.725),
#  ('2022-04-13', 2.5),
#  ('2022-04-14', 2.761904761904762),
#  ...
# ]

`aggregate()`

Like annotate(), but instead of adding a value for each row it reduces the query to a single row.

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Django ORM Cheatsheet

Our models

Starting point

Make fewer queries

`select_related()`

without `select_related()`

with `select_related()`

`prefetch_related()`

without `prefetch_related()`

with `prefetch_related()`

`update()`

without `update()`

with `update()`

Query things other than columns, AKA do your work in the DB, not in Python

`annotate()` (first look)

`filter()` and `Q()`

Query Expressions

`F()`

`CASE` and conditional logic

`Subquery()` and `OuterRef()`

Select less data

`values()` (part 1)

`exists()`

`only()`

Grouping data

`values()` (part 2) and `GROUP BY`

`aggregate()`

About

Releases

Packages

License

Jdsleppy/django-orm-cheatsheet

Folders and files

Latest commit

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Repository files navigation

Django ORM Cheatsheet

Our models

Starting point

Make fewer queries

select_related()

without select_related()

with select_related()

prefetch_related()

without prefetch_related()

with prefetch_related()

update()

without update()

with update()

Query things other than columns, AKA do your work in the DB, not in Python

annotate() (first look)

filter() and Q()

Query Expressions

F()

CASE and conditional logic

Subquery() and OuterRef()

Select less data

values() (part 1)

exists()

only()

Grouping data

values() (part 2) and GROUP BY

aggregate()

About

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License

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Releases

Packages 0

`select_related()`

without `select_related()`

with `select_related()`

`prefetch_related()`

without `prefetch_related()`

with `prefetch_related()`

`update()`

without `update()`

with `update()`

`annotate()` (first look)

`filter()` and `Q()`

`F()`

`CASE` and conditional logic

`Subquery()` and `OuterRef()`

`values()` (part 1)

`exists()`

`only()`

`values()` (part 2) and `GROUP BY`

`aggregate()`

Packages