Defining Models in Python

As we discussed earlier in Chapter 1, Introduction to Django and Getting Started, the M in MTV stands for Model. A Django model is a description of the data in your database, represented as Python code. It's your data layout-the equivalent of your SQL CREATE TABLE statements-except it's in Python instead of SQL, and it includes more than just database column definitions.

Django uses a model to execute SQL code behind the scenes and return convenient Python data structures representing the rows in your database tables. Django also uses models to represent higher-level concepts that SQL can't necessarily handle.

If you're familiar with databases, your immediate thought might be, "Isn't it redundant to define data models in Python instead of in SQL?" Django works the way it does for several reasons:

  • Introspection requires overhead and is imperfect. In order to provide convenient data-access APIs, Django needs to know the database layout somehow, and there are two ways of accomplishing this. The first way would be to explicitly describe the data in Python, and the second way would be to introspect the database at runtime to determine the data models.
  • This second way seems cleaner, because the metadata about your tables lives in only one place, but it introduces a few problems. First, introspecting a database at runtime obviously requires overhead. If the framework had to introspect the database each time it processed a request, or even only when the web server was initialized, this would incur an unacceptable level of overhead. (While some believe that level of overhead is acceptable, Django's developers aim to trim as much framework overhead as possible.) Second, some databases, notably older versions of MySQL, do not store sufficient metadata for accurate and complete introspection.
  • Writing Python is fun, and keeping everything in Python limits the number of times your brain has to do a "context switch". It helps productivity if you keep yourself in a single programming environment/mentality for as long as possible. Having to write SQL, then Python, and then SQL again is disruptive.
  • Having data models stored as code rather than in your database makes it easier to keep your models under version control. This way, you can easily keep track of changes to your data layouts.
  • SQL allows for only a certain level of metadata about a data layout. Most database systems, for example, do not provide a specialized data type for representing email addresses or URLs. Django models do. The advantage of higher-level data types is higher productivity and more reusable code.
  • SQL is inconsistent across database platforms. If you're distributing a web application, for example, it's much more pragmatic to distribute a Python module that describes your data layout than separate sets of CREATE TABLE statements for MySQL, PostgreSQL, and SQLite.

A drawback of this approach, however, is that it's possible for the Python code to get out of sync with what's actually in the database. If you make changes to a Django model, you'll need to make the same changes inside your database to keep your database consistent with the model. I'll show you how to handle this problem when we discuss migrations later in this chapter.

Finally, you should note that Django includes a utility that can generate models by introspecting an existing database. This is useful for quickly getting up and running with legacy data. We'll cover this in Chapter 21, Advanced Database Management.

Your first model

As an ongoing example in this chapter and the next chapter, I'll focus on a basic book/author/publisher data layout. I use this as our example because the conceptual relationships between books, authors, and publishers are well known, and this is a common data layout used in introductory SQL textbooks. You're also reading a book that was written by authors and produced by a publisher!

I'll suppose the following concepts, fields, and relationships:

  • An author has a first name, a last name, and an email address.
  • A publisher has a name, a street address, a city, a state/province, a country, and a website.
  • A book has a title and a publication date. It also has one or more authors (a many-to-many relationship with authors) and a single publisher (a one-to-many relationship-aka foreign key-to publishers).

The first step in using this database layout with Django is to express it as Python code. In the models.py file that was created by the startapp command, enter the following:

from django.db import models 
 
class Publisher(models.Model): 
    name = models.CharField(max_length=30) 
    address = models.CharField(max_length=50) 
    city = models.CharField(max_length=60) 
    state_province = models.CharField(max_length=30) 
    country = models.CharField(max_length=50) 
    website = models.URLField() 
 
class Author(models.Model): 
    first_name = models.CharField(max_length=30) 
    last_name = models.CharField(max_length=40) 
    email = models.EmailField() 
 
class Book(models.Model): 
    title = models.CharField(max_length=100) 
    authors = models.ManyToManyField(Author) 
    publisher = models.ForeignKey(Publisher) 
    publication_date = models.DateField() 

Let's quickly examine this code to cover the basics. The first thing to notice is that each model is represented by a Python class that is a subclass of django.db.models.Model. The parent class, Model, contains all the machinery necessary to make these objects capable of interacting with a database-and that leaves our models responsible solely for defining their fields, in a nice and compact syntax.

Believe it or not, this is all the code we need to write to have basic data access with Django. Each model generally corresponds to a single database table, and each attribute on a model generally corresponds to a column in that database table. The attribute name corresponds to the column's name, and the type of field (example, CharField) corresponds to the database column type (example, varchar). For example, the Publisher model is equivalent to the following table (assuming PostgreSQL CREATE TABLE syntax):

CREATE TABLE "books_publisher" ( 
    "id" serial NOT NULL PRIMARY KEY, 
    "name" varchar(30) NOT NULL, 
    "address" varchar(50) NOT NULL, 
    "city" varchar(60) NOT NULL, 
    "state_province" varchar(30) NOT NULL, 
    "country" varchar(50) NOT NULL, 
    "website" varchar(200) NOT NULL 
); 

Indeed, Django can generate that CREATE TABLE statement automatically, as we'll show you in a moment. The exception to the one-class-per-database-table rule is the case of many-to-many relationships. In our example models, Book has a ManyToManyField called authors. This designates that a book has one or many authors, but the Book database table doesn't get an authors column. Rather, Django creates an additional table-a many-to-many join table-that handles the mapping of books to authors.

For a full list of field types and model syntax options, see Appendix B, Database API Reference. Finally, note we haven't explicitly defined a primary key in any of these models. Unless you instruct it otherwise, Django automatically gives every model an auto-incrementing integer primary key field called id. Each Django model is required to have a single-column primary key.

Installing the Model

We've written the code; now let's create the tables in our database. In order to do that, the first step is to activate these models in our Django project. We do that by adding the books app to the list of installed apps in the settings file. Edit the settings.py file again, and look for the INSTALLED_APPS setting. INSTALLED_APPS tells Django which apps are activated for a given project. By default, it looks something like this:

INSTALLED_APPS = ( 
'django.contrib.admin', 
'django.contrib.auth', 
'django.contrib.contenttypes', 
'django.contrib.sessions', 
'django.contrib.messages', 
'django.contrib.staticfiles', 
) 

To register our books app, add 'books' to INSTALLED_APPS, so the setting ends up looking like this ('books' refers to the "books" app we're working on):

INSTALLED_APPS = ( 
'django.contrib.admin', 
'django.contrib.auth', 
'django.contrib.contenttypes', 
'django.contrib.sessions', 
'django.contrib.messages', 
'django.contrib.staticfiles', 
'books', 
) 

Each app in INSTALLED_APPS is represented by its full Python path-that is, the path of packages, separated by dots, leading to the app package. Now that the Django app has been activated in the settings file, we can create the database tables in our database. First, let's validate the models by running this command:

python manage.py check

The check command runs the Django system check framework-a set of static checks for validating Django projects. If all is well, you'll see the message System check identified no issues (0 silenced). If you don't, make sure you typed in the model code correctly. The error output should give you helpful information about what was wrong with the code. Anytime you think you have problems with your models, run python manage.py check. It tends to catch all the common model problems.

If your models are valid, run the following command to tell Django that you have made some changes to your models (in this case, you have made a new one):

python manage.py makemigrations books 

You should see something similar to the following:

Migrations for 'books': 
  0001_initial.py: 
   -Create model Author 
   -Create model Book 
   -Create model Publisher 
   -Add field publisher to book 

Migrations are how Django stores changes to your models (and thus your database schema)-they're just files on disk. In this instance, you will find  file names 0001_initial.py in the 'migrations' folder of the books app. The migrate command will take your latest migration file and update your database schema automatically, but first, let's see what SQL that migration would run. The sqlmigrate command takes migration names and returns their SQL:

python manage.py sqlmigrate books 0001

You should see something similar to the following (reformatted for readability):

BEGIN; 
 
CREATE TABLE "books_author" ( 
    "id" integer NOT NULL PRIMARY KEY AUTOINCREMENT, 
    "first_name" varchar(30) NOT NULL, 
    "last_name" varchar(40) NOT NULL, 
    "email" varchar(254) NOT NULL 
); 
CREATE TABLE "books_book" ( 
    "id" integer NOT NULL PRIMARY KEY AUTOINCREMENT, 
    "title" varchar(100) NOT NULL, 
    "publication_date" date NOT NULL 
); 
CREATE TABLE "books_book_authors" ( 
    "id" integer NOT NULL PRIMARY KEY AUTOINCREMENT, 
    "book_id" integer NOT NULL REFERENCES "books_book" ("id"), 
    "author_id" integer NOT NULL REFERENCES "books_author" ("id"), 
    UNIQUE ("book_id", "author_id") 
); 
CREATE TABLE "books_publisher" ( 
    "id" integer NOT NULL PRIMARY KEY AUTOINCREMENT, 
    "name" varchar(30) NOT NULL, 
    "address" varchar(50) NOT NULL, 
    "city" varchar(60) NOT NULL, 
    "state_province" varchar(30) NOT NULL, 
    "country" varchar(50) NOT NULL, 
    "website" varchar(200) NOT NULL 
); 
CREATE TABLE "books_book__new" ( 
    "id" integer NOT NULL PRIMARY KEY AUTOINCREMENT, 
    "title" varchar(100) NOT NULL, 
    "publication_date" date NOT NULL, 
    "publisher_id" integer NOT NULL REFERENCES 
    "books_publisher" ("id") 
); 
 
INSERT INTO "books_book__new" ("id", "publisher_id", "title", 
"publication_date") SELECT "id", NULL, "title", "publication_date" FROM 
"books_book"; 
 
DROP TABLE "books_book"; 
 
ALTER TABLE "books_book__new" RENAME TO "books_book"; 
 
CREATE INDEX "books_book_2604cbea" ON "books_book" ("publisher_id"); 
 
COMMIT; 

Note the following:

  • Table names are automatically generated by combining the name of the app (books) and the lowercase name of the model (publisher, book, and author). You can override this behavior, as detailed in Appendix B, Database API Reference.
  • As we mentioned earlier, Django adds a primary key for each table automatically-the id fields. You can override this, too. By convention, Django appends "_id" to the foreign key field name. As you might have guessed, you can override this behavior, too.
  • The foreign key relationship is made explicit by a REFERENCES statement.

These CREATE TABLE statements are tailored to the database you're using, so database-specific field types such as auto_increment (MySQL), serial (PostgreSQL), or integer primary key (SQLite) are handled for you automatically. The same goes for quoting of column names (example, using double quotes or single quotes). This example output is in PostgreSQL syntax.

The sqlmigrate command doesn't actually create the tables or otherwise touch your database-it just prints output to the screen so you can see what SQL Django would execute if you asked it. If you wanted to, you could copy and paste this SQL into your database client, however, Django provides an easier way of committing the SQL to the database: the migrate command:

python manage.py migrate

Run that command, and you'll see something like this:

Operations to perform:
  Apply all migrations: books
Running migrations:
  Rendering model states... DONE
  # ...
  Applying books.0001_initial... OK
  # ...

In case you were wondering what all the extras are (commented out above), the first time you run migrate, Django will also create all the system tables that Django needs for the inbuilt apps. Migrations are Django's way of propagating changes you make to your models (adding a field, deleting a model, and so on.) into your database schema. They're designed to be mostly automatic, however, there are some caveats. For more information on migrations, see Chapter 21, Advanced Database Management.

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