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https://github.com/Jdsleppy/django-orm-cheatsheet
A cheatsheet for the Django ORM
https://github.com/Jdsleppy/django-orm-cheatsheet
Last synced: about 2 months ago
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A cheatsheet for the Django ORM
- Host: GitHub
- URL: https://github.com/Jdsleppy/django-orm-cheatsheet
- Owner: Jdsleppy
- License: mit
- Created: 2022-05-07T19:53:06.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2022-05-08T12:29:10.000Z (over 2 years ago)
- Last Synced: 2024-07-05T13:23:17.279Z (3 months ago)
- Size: 5.86 KB
- Stars: 424
- Watchers: 9
- Forks: 36
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Django ORM Cheatsheet
If you wanted to read a lot of text you'd be reading the Django docs, especially these pages:
- [Queryset API (select_related, bulk_update, etc.)](https://docs.djangoproject.com/en/dev/ref/models/querysets/)
- [Query Expressions (Subquery, F, annotate, aggregate, etc.)](https://docs.djangoproject.com/en/dev/ref/models/expressions/)
- [Aggregation](https://docs.djangoproject.com/en/dev/topics/db/aggregation/)
- [Database Functions](https://docs.djangoproject.com/en/dev/ref/models/database-functions/)
But you don't want that, so you're here. I'll get to the point.
# Our models
```python
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
```python
Entry.objects.all()
# SELECT "blog_entry"."id", "blog_entry"."blog_id", ...
# FROM "blog_entry" ...;
# [,
# ,
# ,
# ...
# ]
```
# 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()`
```python
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()`
```python
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()`
```python
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()`
```python
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()`
```python
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()`
```python
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.
```python
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.
```python
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](https://docs.djangoproject.com/en/dev/ref/models/expressions/). 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.
```python
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](https://docs.djangoproject.com/en/dev/ref/models/conditional-expressions/)
`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.
```python
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.
```python
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;
# [(, 'Three space maintain subject much.'),
# (, 'Rock authority enjoy hundred reduce behavior.'),
# (, 'Visit beyond base.'),
# (, 'Tree look culture minute affect.'),
# (, '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:
```python
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.
```python
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](https://docs.djangoproject.com/en/dev/topics/db/aggregation/#values):
> "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?
```python
[
(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.