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Django ORM's Hidden Magic: Advanced Uses and Techniques, Part-1

Django ORM's Hidden Magic: Advanced Uses and Techniques, Part-1

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Azanul Haque
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Table of contents

I'm assuming you already know what Django is and what is ORM. If not:-
Django is a high-level web framework for building web applications quickly and with less code. It is written in Python and follows the Model-View-Template (MVT) architectural pattern. Django provides many built-in features such as a user authentication system, admin interface, and database abstraction layer, which makes it easier to develop web applications.

An important part of the database abstraction layer is ORM, which stands for Object-Relational Mapping. ORM is a feature of Django that allows you to interact with your database as if you were working with Python objects. Instead of writing raw SQL queries, you can use the Django ORM to perform database operations in a more intuitive and Pythonic way. The ORM provides a high-level API for creating, retrieving, updating, and deleting records in your database. It also supports complex operations such as aggregations, relationships, and custom lookups, allowing you to write efficient and scalable database code for your Django projects.

We'll be using the official Django polls app example.

from django.db import models


class Question(models.Model):
    question_text = models.CharField(max_length=200)
    pub_date = models.DateTimeField('date published')


class Choice(models.Model):
    question = models.ForeignKey(Question, on_delete=models.CASCADE)
    choice_text = models.CharField(max_length=200)
    votes = models.IntegerField(default=0)

Now let's jump into the cool stuff:

Custom Lookups

We can define custom lookups to perform complex database queries. For example, we can create a custom lookup to search for questions that lie within a certain length range. You can define the lookup as:

from django.db.models import Field, Lookup

@Field.register_lookup
class LengthWithinLookup(Lookup):
    lookup_name = 'length_within'

    def as_sql(self, compiler, connection):
        lhs, lhs_params = self.process_lhs(compiler, connection)
        rhs, rhs_params = self.process_rhs(compiler, connection)
        lower_limit, upper_limit = rhs_params[0][1:-1].split(", ")
        return f"LENGTH({lhs}) BETWEEN {lower_limit} AND {upper_limit}", []

...

We can query questions with length within the range [16, 40] by running:

Question.objects.filter(question_text__length_within=(16, 40))

For more info on custom lookups visit this link.

Aggregation & Annotation

Django ORM provides built-in support for database-level aggregation operations, such as counting, summing, averaging, grouping and more. These operations can be performed using the django.db.models API. The aggregate and annotate methods allow for powerful data analysis and manipulation and can help you write cleaner, more efficient code. Let's see a few examples:

# Total number of questions.
Question.objects.count()

# Max votes across all choices.
from django.db.models import Max
Choice.objects.aggregate(Max('votes'))

# Annotate each question with the no. of choices for it
Question.objects.annotate(num_choices=Count('choice'))

# Annotate each question with the choice_text of choice with highest votes
from django.db.models import Subquery, OuterRef
Question.objects.annotate(
    choice_text=Subquery(
        Choice.objects.filter(question=OuterRef('pk'))
        .order_by('-votes')
        .values('choice_text')[:1]
    )
)

I recommend that you take a look at the official documentation if you think you need either aggregation & annotation as it's much more detailed there, here's the link. Feel free to comment below if you have any queries not covered there. We need to be careful about yielding wrong results while aggregating & annotating, check out this link. In the last example we've used a subquery, let's look further into it.

Subqueries

Subqueries in Django ORM allow you to use the results of one query as input for another query. You can perform complex operations by chaining multiple queries together, which can lead to more efficient and readable code.

Subqueries can be used in several ways in the Django ORM, including as a filter, as an annotation, or as an expression. To use a subquery as a filter, you can use the Subquery expression in the filter method. To use a subquery as an annotation, you can use the Subquery expression in the annotate method. To use a subquery as an expression, you can use it as an input to other expressions, such as F expressions (we'll look into these in the next part). Lets take an example, let's say you want to find all questions that have at least one choice with a vote count greater than 5. One way to achieve this would be to use the exclude method along with a subquery:

from django.db.models import Subquery, OuterRef

question_with_high_votes = Choice.objects.filter(
    votes__gt=5, question=OuterRef('pk')
).values('question')

Question.objects.exclude(
    pk__in=Subquery(question_with_high_votes)
)

reference link.

Model Inheritance

This section can be an entire article all by itself and we still won't be able to cover it all. I hope you're already familiar with OOP. Django ORM supports several forms of model inheritance. The main forms are:

  1. Abstract Base Classes: An abstract base class is a model that is meant to be used as a base class for other models, but it won't be instantiated itself. It provides fields that can be reused by other models but it is not stored in the database. Let's update our Question and Choice models to have created_at and updated_at times. We'll do so by making both of them extend an abstract class BaseModel.

     # Abstract class
 class BaseModel(models.Model):
     created_at = models.DateTimeField(auto_now_add=True)
     updated_at = models.DateTimeField(auto_now=True)

     class Meta:
         abstract = True

 class Question(BaseModel):
     question_text = models.CharField(max_length=200)
     pub_date = models.DateTimeField('date published')

 class Choice(BaseModel):
     question = models.ForeignKey(Question, on_delete=models.CASCADE)
     choice_text = models.CharField(max_length=200)
     votes = models.IntegerField(default=0)

    Both Question and Choice will have all their fields and those of BaseModel .

  2. Multi-table Inheritance: Multi-table inheritance allows a model to inherit fields and methods from multiple parent models. The fields and methods of the parent models are stored in separate tables in the database, with the child model having its table for its fields. Let's extend our example for this:

     class BaseModel(models.Model):
     created_at = models.DateTimeField(auto_now_add=True)
     updated_at = models.DateTimeField(auto_now=True)

     class Meta:
         abstract = True

 class CommunityModel(models.Model):
     author = models.CharField(max_length=100)

 class Question(BaseModel):
     question_text = models.CharField(max_length=200)
     pub_date = models.DateTimeField('date published')

 class Choice(BaseModel):
     question = models.ForeignKey(Question, on_delete=models.CASCADE)
     choice_text = models.CharField(max_length=200)
     votes = models.IntegerField(default=0)

 class CommunityChoice(Choice, CommunityModel):
     pass

    CommunityChoice will have all fields from Choice as well as from CommunityModel .

  3. Proxy models: Proxy models are models that inherit from an existing model, but don't add any fields or methods. They are typically used to change the manager for a model, or change the default ordering of the model's objects.

     class PublishedQuestion(Question):
     class Meta:
         proxy = True

     def was_published_recently(self):
         return self.pub_date >= timezone.now() - datetime.timedelta(days=1)

    In this example, PublishedQuestion is a proxy model that extends the Question model. The PublishedQuestion model has a method was_published_recently that checks if the question was published on the last day. Because PublishedQuestion is a proxy model, it has the same fields and behavior as the Question model, but can have additional methods and attributes.

Let me clear up any dangling confusion among these three. Abstract models do not create DB tables, neither do Proxy models. Proxy models inherit a solid (has a DB table) model class, Abstract models are inherited for adding extra fields.

Raw SQL Query

If nothing else works for you, but you know SQL then you can run raw SQL queries directly to the connected database. We don't even have to create a new connection. We use the same persistent connection created by Django. Let's fetch all questions published before 1st Feb 2023.

from django.db import connection


cursor = connection.cursor()
cursor.execute("SELECT * FROM polls_question WHERE pub_date < %s", ['2023-02-01'])

result = cursor.fetchall()

cursor.close()

But what if we wanted Question objects instead of raw query results. We can get it like this:

Question.objects.raw("SELECT * FROM polls_question WHERE pub_date < %s", ['2023-02-01'])

We can even fetch question data from a different table, all we need is to provide the mapping from the source fields to destination fields if fields are differently numbered or named. Let's take a separate table

class NotQuestion(models.Model):
    question_text = models.CharField(max_length=200)
    due_date = models.DateTimeField('due date')
    category = models.CharField(max_length=100)

Now there are still two ways to do this:

field_map = {'due_date': 'pub_date'}
Question.objects.raw('SELECT * FROM polls_notquestion', translations=field_map)

This way we get the fields from NotQuestion in Question objects. The other way is to use the AS syntax in SQL.

Question.objects.raw('SELECT question_text, due_date AS pub_date FROM polls_notquestion')

Conclusion

Soon enough I'll add the next part to it, in which we'll cover Relationships, Prefetch, F expressions, Transactions and Indexing & Caching. To get notified when it releases, follow me on Twitter at AzanulZ or connect with me on LinkedIn, Azanul Haque.

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