The “Dumb” Way to Do Database Queries in Views

Just as Chapter 3 detailed a “dumb” way to produce output within a view (by hard-coding the text directly within the view), there’s a “dumb” way to retrieve data from a database in a view. It’s simple: just use any existing Python library to execute an SQL query and do something with the results.

In this example view, we use the MySQLdb library (available via http://www.djangoproject.com/r/python-mysql/) to connect to a MySQL database, retrieve some records, and feed them to a template for display as a Web page:

from django.shortcuts import render
import MySQLdb

def book_list(request):
    db = MySQLdb.connect(user='me', db='mydb', passwd='secret', host='localhost')
    cursor = db.cursor()
    cursor.execute('SELECT name FROM books ORDER BY name')
    names = [row[0] for row in cursor.fetchall()]
    db.close()
    return render(request, 'book_list.html', {'names': names})

This approach works, but some problems should jump out at you immediately:

• We’re hard-coding the database connection parameters. Ideally, these parameters would be stored in the Django configuration.
• We’re having to write a fair bit of boilerplate code: creating a connection, creating a cursor, executing a statement, and closing the connection. Ideally, all we’d have to do is specify which results we wanted.
• It ties us to MySQL. If, down the road, we switch from MySQL to PostgreSQL, we’ll have to use a different database adapter (e.g., psycopg rather than MySQLdb), alter the connection parameters, and – depending on the nature of the SQL statement – possibly rewrite the SQL. Ideally, the database server we’re using would be abstracted, so that a database server change could be made in a single place. (This feature is particularly relevant if you’re building an open-source Django application that you want to be used by as many people as possible.)

As you might expect, Django’s database layer aims to solve these problems. Here’s a sneak preview of how the previous view can be rewritten using Django’s database API:

from django.shortcuts import render
from mysite.books.models import Book

def book_list(request):
    books = Book.objects.order_by('name')
    return render(request, 'book_list.html', {'books': books})

We’ll explain this code a little later in the chapter. For now, just get a feel for how it looks.

The MTV (or MVC) Development Pattern

Before we delve into any more code, let’s take a moment to consider the overall design of a database-driven Django Web application.

As we mentioned in previous chapters, Django is designed to encourage loose coupling and strict separation between pieces of an application. If you follow this philosophy, it’s easy to make changes to one particular piece of the application without affecting the other pieces. In view functions, for instance, we discussed the importance of separating the business logic from the presentation logic by using a template system. With the database layer, we’re applying that same philosophy to data access logic.

Those three pieces together – data access logic, business logic, and presentation logic – comprise a concept that’s sometimes called the Model-View-Controller (MVC) pattern of software architecture. In this pattern, “Model” refers to the data access layer, “View” refers to the part of the system that selects what to display and how to display it, and “Controller” refers to the part of the system that decides which view to use, depending on user input, accessing the model as needed.

Django follows this MVC pattern closely enough that it can be called an MVC framework. Here’s roughly how the M, V, and C break down in Django:

• M, the data-access portion, is handled by Django’s database layer, which is described in this chapter.
• V, the portion that selects which data to display and how to display it, is handled by views and templates.
• C, the portion that delegates to a view depending on user input, is handled by the framework itself by following your URLconf and calling the appropriate Python function for the given URL.

Because the “C” is handled by the framework itself and most of the excitement in Django happens in models, templates and views, Django has been referred to as an MTV framework. In the MTV development pattern,

• M stands for “Model,” the data access layer. This layer contains anything and everything about the data: how to access it, how to validate it, which behaviors it has, and the relationships between the data.
• T stands for “Template,” the presentation layer. This layer contains presentation-related decisions: how something should be displayed on a Web page or other type of document.
• V stands for “View,” the business logic layer. This layer contains the logic that access the model and defers to the appropriate template(s). You can think of it as the bridge between models and templates.

If you’re familiar with other MVC Web-development frameworks, such as Ruby on Rails, you may consider Django views to be the “controllers” and Django templates to be the “views.” This is an unfortunate confusion brought about by differing interpretations of MVC. In Django’s interpretation of MVC, the “view” describes the data that gets presented to the user; it’s not necessarily just how the data looks, but which data is presented. In contrast, Ruby on Rails and similar frameworks suggest that the controller’s job includes deciding which data gets presented to the user, whereas the view is strictly how the data looks, not which data is presented.

Neither interpretation is more “correct” than the other. The important thing is to understand the underlying concepts.

Configuring the Database

With all of that philosophy in mind, let’s start exploring Django’s database layer. First, we need to take care of some initial configuration; we need to tell Django which database server to use and how to connect to it.

We’ll assume you’ve set up a database server, activated it, and created a database within it (e.g., using a CREATE DATABASE statement). If you’re using SQLite, no such setup is required, because SQLite uses standalone files on the filesystem to store its data.

As with TEMPLATE_DIRS in the previous chapter, database configuration lives in the Django settings file, called settings.py by default. Edit that file and look for the database settings:

DATABASES = {
    'default': {
        'ENGINE': 'django.db.backends.', # Add 'postgresql_psycopg2', 'mysql', 'sqlite3' or 'oracle'.
        'NAME': '',                      # Or path to database file if using sqlite3.
        'USER': '',                      # Not used with sqlite3.
        'PASSWORD': '',                  # Not used with sqlite3.
        'HOST': '',                      # Set to empty string for localhost. Not used with sqlite3.
        'PORT': '',                      # Set to empty string for default. Not used with sqlite3.
    }
}

Here’s a rundown of each setting.

• ENGINE tells Django which database engine to use. If you’re using a database with Django, ENGINE must be set to one of the strings shown in Table 5-1.

  Table 5-1. Database Engine Settings

  Setting	Database	Required Adapter
  django.db.backends.postgresql_psycopg2	PostgreSQL	psycopg version 2.x, http://www.djangoproject.com/r/python-pgsql/.
  django.db.backends.mysql	MySQL	MySQLdb, http://www.djangoproject.com/r/python-mysql/.
  django.db.backends.sqlite3	SQLite	No adapter needed.
  django.db.backends.oracle	Oracle	cx_Oracle, http://www.djangoproject.com/r/python-oracle/.

  Note that for whichever database back-end you use, you’ll need to download and install the appropriate database adapter. Each one is available for free on the Web; just follow the links in the “Required Adapter” column in Table 5-1. If you’re on Linux, your distribution’s package-management system might offer convenient packages. (Look for packages called python-postgresql or python-psycopg, for example.)

  Example:

  'ENGINE': 'django.db.backends.postgresql_psycopg2',

• NAME tells Django the name of your database. For example:

  'NAME': 'mydb',

  If you’re using SQLite, specify the full filesystem path to the database file on your filesystem. For example:

  'NAME': '/home/django/mydata.db',

  As for where you put that SQLite database, we’re using the /home/django directory in this example, but you should pick a directory that works best for you.

• USER tells Django which username to use when connecting to your database. For example: If you’re using SQLite, leave this blank.

• PASSWORD tells Django which password to use when connecting to your database. If you’re using SQLite or have an empty password, leave this blank.

• HOST tells Django which host to use when connecting to your database. If your database is on the same computer as your Django installation (i.e., localhost), leave this blank. If you’re using SQLite, leave this blank.

  MySQL is a special case here. If this value starts with a forward slash ('/') and you’re using MySQL, MySQL will connect via a Unix socket to the specified socket, for example:

  'HOST': '/var/run/mysql',

• PORT tells Django which port to use when connecting to your database. If you’re using SQLite, leave this blank. Otherwise, if you leave this blank, the underlying database adapter will use whichever port is default for your given database server. In most cases, the default port is fine, so you can leave this blank.

Once you’ve entered those settings and saved settings.py, it’s a good idea to test your configuration. To do this, run python manage.py shell as in the last chapter, from within the mysite project directory. (As we pointed out last chapter manage.py shell is a way to run the Python interpreter with the correct Django settings activated. This is necessary in our case, because Django needs to know which settings file to use in order to get your database connection information.)

In the shell, type these commands to test your database configuration:

>>> from django.db import connection
>>> cursor = connection.cursor()

If nothing happens, then your database is configured properly. Otherwise, check the error message for clues about what’s wrong. Table 5-2 shows some common errors.

Your First App

Now that you’ve verified the connection is working, it’s time to create a Django app – a bundle of Django code, including models and views, that lives together in a single Python package and represents a full Django application.

It’s worth explaining the terminology here, because this tends to trip up beginners. We’d already created a project, in Chapter 2, so what’s the difference between a project and an app? The difference is that of configuration vs. code:

• A project is an instance of a certain set of Django apps, plus the configuration for those apps.

  Technically, the only requirement of a project is that it supplies a settings file, which defines the database connection information, the list of installed apps, the TEMPLATE_DIRS, and so forth.

• An app is a portable set of Django functionality, usually including models and views, that lives together in a single Python package.

  For example, Django comes with a number of apps, such as a commenting system and an automatic admin interface. A key thing to note about these apps is that they’re portable and reusable across multiple projects.

There are very few hard-and-fast rules about how you fit your Django code into this scheme. If you’re building a simple Web site, you may use only a single app. If you’re building a complex Web site with several unrelated pieces such as an e-commerce system and a message board, you’ll probably want to split those into separate apps so that you’ll be able to reuse them individually in the future.

Indeed, you don’t necessarily need to create apps at all, as evidenced by the example view functions we’ve created so far in this book. In those cases, we simply created a file called views.py, filled it with view functions, and pointed our URLconf at those functions. No “apps” were needed.

However, there’s one requirement regarding the app convention: if you’re using Django’s database layer (models), you must create a Django app. Models must live within apps. Thus, in order to start writing our models, we’ll need to create a new app.

Within the mysite project directory, type this command to create a books app:

python manage.py startapp books

This command does not produce any output, but it does create a books directory within the mysite directory. Let’s look at the contents of that directory:

books/
    __init__.py
    models.py
    tests.py
    views.py

These files will contain the models and views for this app.

Have a look at models.py and views.py in your favorite text editor. Both files are empty, except for comments and an import in models.py. This is the blank slate for your Django app.

Defining Models in Python

As we discussed earlier in this chapter, 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. We’ll discuss some strategies for handling this problem later in this chapter.

Finally, we 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 18.

Your First Model

As an ongoing example in this chapter and the next chapter, we’ll focus on a basic book/author/publisher data layout. We 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!

We’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 Web site.
• 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 (e.g., CharField) corresponds to the database column type (e.g., 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.

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.auth',
    'django.contrib.contenttypes',
    'django.contrib.sessions',
    'django.contrib.sites',
    'django.contrib.messages',
    'django.contrib.staticfiles',
)

Temporarily comment out all six of those strings by putting a hash character (#) in front of them. (They’re included by default as a common-case convenience, but we’ll activate and discuss them in subsequent chapters.) While you’re at it, comment out the default MIDDLEWARE_CLASSES setting, too; the default values in MIDDLEWARE_CLASSES depend on some of the apps we just commented out. Then, add 'books' to the INSTALLED_APPS list, so the setting ends up looking like this:

MIDDLEWARE_CLASSES = (
    # 'django.middleware.common.CommonMiddleware',
    # 'django.contrib.sessions.middleware.SessionMiddleware',
    # 'django.middleware.csrf.CsrfViewMiddleware',
    # 'django.contrib.auth.middleware.AuthenticationMiddleware',
    # 'django.contrib.messages.middleware.MessageMiddleware',
)

INSTALLED_APPS = (
    # 'django.contrib.auth',
    # 'django.contrib.contenttypes',
    # 'django.contrib.sessions',
    # 'django.contrib.sites',
    'books',
)

(As we mentioned last chapter when setting TEMPLATE_DIRS, you’ll need to be sure to include the trailing comma in INSTALLED_APPS, because it’s a single-element tuple. By the way, this book’s authors prefer to put a comma after every element of a tuple, regardless of whether the tuple has only a single element. This avoids the issue of forgetting commas, and there’s no penalty for using that extra comma.)

'mysite.books' refers to the books app we’re working on. 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 validate

The validate command checks whether your models’ syntax and logic are correct. If all is well, you’ll see the message 0 errors found. 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.

Any time you think you have problems with your models, run python manage.py validate. It tends to catch all the common model problems.

If your models are valid, run the following command for Django to generate CREATE TABLE statements for your models in the books app (with colorful syntax highlighting available, if you’re using Unix):

python manage.py sqlall books

In this command, books is the name of the app. It’s what you specified when you ran the command manage.py startapp. When you run the command, you should see something like this:

BEGIN;
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
)
;
CREATE TABLE "books_author" (
    "id" serial NOT NULL PRIMARY KEY,
    "first_name" varchar(30) NOT NULL,
    "last_name" varchar(40) NOT NULL,
    "email" varchar(75) NOT NULL
)
;
CREATE TABLE "books_book" (
    "id" serial NOT NULL PRIMARY KEY,
    "title" varchar(100) NOT NULL,
    "publisher_id" integer NOT NULL REFERENCES "books_publisher" ("id") DEFERRABLE INITIALLY DEFERRED,
    "publication_date" date NOT NULL
)
;
CREATE TABLE "books_book_authors" (
    "id" serial NOT NULL PRIMARY KEY,
    "book_id" integer NOT NULL REFERENCES "books_book" ("id") DEFERRABLE INITIALLY DEFERRED,
    "author_id" integer NOT NULL REFERENCES "books_author" ("id") DEFERRABLE INITIALLY DEFERRED,
    UNIQUE ("book_id", "author_id")
)
;
CREATE INDEX "books_book_publisher_id" 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.
• 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 (e.g., using double quotes or single quotes). This example output is in PostgreSQL syntax.

The sqlall 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, or use Unix pipes to pass it directly (e.g., python manage.py sqlall books | psql mydb). However, Django provides an easier way of committing the SQL to the database: the syncdb command:

python manage.py syncdb

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

Creating table books_publisher
Creating table books_author
Creating table books_book
Installing index for books.Book model

The syncdb command is a simple “sync” of your models to your database. It looks at all of the models in each app in your INSTALLED_APPS setting, checks the database to see whether the appropriate tables exist yet, and creates the tables if they don’t yet exist. Note that syncdb does not sync changes in models or deletions of models; if you make a change to a model or delete a model, and you want to update the database, syncdb will not handle that. (More on this in the “Making Changes to a Database Schema” section toward the end of this chapter.)

If you run python manage.py syncdb again, nothing happens, because you haven’t added any models to the books app or added any apps to INSTALLED_APPS. Ergo, it’s always safe to run python manage.py syncdb – it won’t clobber things.

If you’re interested, take a moment to dive into your database server’s command-line client and see the database tables Django created. You can manually run the command-line client (e.g., psql for PostgreSQL) or you can run the command python manage.py dbshell, which will figure out which command-line client to run, depending on your DATABASE_SERVER setting. The latter is almost always more convenient.

Basic Data Access

Once you’ve created a model, Django automatically provides a high-level Python API for working with those models. Try it out by running python manage.py shell and typing the following:

>>> from books.models import Publisher
>>> p1 = Publisher(name='Apress', address='2855 Telegraph Avenue',
...     city='Berkeley', state_province='CA', country='U.S.A.',
...     website='http://www.apress.com/')
>>> p1.save()
>>> p2 = Publisher(name="O'Reilly", address='10 Fawcett St.',
...     city='Cambridge', state_province='MA', country='U.S.A.',
...     website='http://www.oreilly.com/')
>>> p2.save()
>>> publisher_list = Publisher.objects.all()
>>> publisher_list
[<Publisher: Publisher object>, <Publisher: Publisher object>]

These few lines of code accomplish quite a bit. Here are the highlights:

• First, we import our Publisher model class. This lets us interact with the database table that contains publishers.
• We create a Publisher object by instantiating it with values for each field – name, address, etc.
• To save the object to the database, call its save() method. Behind the scenes, Django executes an SQL INSERT statement here.
• To retrieve publishers from the database, use the attribute Publisher.objects, which you can think of as a set of all publishers. Fetch a list of all Publisher objects in the database with the statement Publisher.objects.all(). Behind the scenes, Django executes an SQL SELECT statement here.

One thing is worth mentioning, in case it wasn’t clear from this example. When you’re creating objects using the Django model API, Django doesn’t save the objects to the database until you call the save() method:

p1 = Publisher(...)
# At this point, p1 is not saved to the database yet!
p1.save()
# Now it is.

If you want to create an object and save it to the database in a single step, use the objects.create() method. This example is equivalent to the example above:

>>> p1 = Publisher.objects.create(name='Apress',
...     address='2855 Telegraph Avenue',
...     city='Berkeley', state_province='CA', country='U.S.A.',
...     website='http://www.apress.com/')
>>> p2 = Publisher.objects.create(name="O'Reilly",
...     address='10 Fawcett St.', city='Cambridge',
...     state_province='MA', country='U.S.A.',
...     website='http://www.oreilly.com/')
>>> publisher_list = Publisher.objects.all()
>>> publisher_list

Naturally, you can do quite a lot with the Django database API – but first, let’s take care of a small annoyance.

Adding Model String Representations

When we printed out the list of publishers, all we got was this unhelpful display that makes it difficult to tell the Publisher objects apart:

[<Publisher: Publisher object>, <Publisher: Publisher object>]

We can fix this easily by adding a method called __unicode__() to our Publisher class. A __unicode__() method tells Python how to display the “unicode” representation of an object. You can see this in action by adding a __unicode__() method to the three models:

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()

    def __unicode__(self):
        return self.name

class Author(models.Model):
    first_name = models.CharField(max_length=30)
    last_name = models.CharField(max_length=40)
    email = models.EmailField()

    def __unicode__(self):
        return u'%s %s' % (self.first_name, self.last_name)

class Book(models.Model):
    title = models.CharField(max_length=100)
    authors = models.ManyToManyField(Author)
    publisher = models.ForeignKey(Publisher)
    publication_date = models.DateField()

    def __unicode__(self):
        return self.title

As you can see, a __unicode__() method can do whatever it needs to do in order to return a representation of an object. Here, the __unicode__() methods for Publisher and Book simply return the object’s name and title, respectively, but the __unicode__() for Author is slightly more complex – it pieces together the first_name and last_name fields, separated by a space.

The only requirement for __unicode__() is that it return a Unicode object. If __unicode__() doesn’t return a Unicode object – if it returns, say, an integer – then Python will raise a TypeError with a message like "coercing to Unicode: need string or buffer, int found".

For the __unicode__() changes to take effect, exit out of the Python shell and enter it again with python manage.py shell. (This is the simplest way to make code changes take effect.) Now the list of Publisher objects is much easier to understand:

>>> from books.models import Publisher
>>> publisher_list = Publisher.objects.all()
>>> publisher_list
[<Publisher: Apress>, <Publisher: O'Reilly>]

Make sure any model you define has a __unicode__() method – not only for your own convenience when using the interactive interpreter, but also because Django uses the output of __unicode__() in several places when it needs to display objects.

Finally, note that __unicode__() is a good example of adding behavior to models. A Django model describes more than the database table layout for an object; it also describes any functionality that object knows how to do. __unicode__() is one example of such functionality – a model knows how to display itself.

Inserting and Updating Data

You’ve already seen this done: to insert a row into your database, first create an instance of your model using keyword arguments, like so:

>>> p = Publisher(name='Apress',
...         address='2855 Telegraph Ave.',
...         city='Berkeley',
...         state_province='CA',
...         country='U.S.A.',
...         website='http://www.apress.com/')

As we noted above, this act of instantiating a model class does not touch the database. The record isn’t saved into the database until you call save(), like this:

>>> p.save()

In SQL, this can roughly be translated into the following:

INSERT INTO books_publisher
    (name, address, city, state_province, country, website)
VALUES
    ('Apress', '2855 Telegraph Ave.', 'Berkeley', 'CA',
     'U.S.A.', 'http://www.apress.com/');

Because the Publisher model uses an autoincrementing primary key id, the initial call to save() does one more thing: it calculates the primary key value for the record and sets it to the id attribute on the instance:

>>> p.id
52    # this will differ based on your own data

Subsequent calls to save() will save the record in place, without creating a new record (i.e., performing an SQL UPDATE statement instead of an INSERT):

>>> p.name = 'Apress Publishing'
>>> p.save()

The preceding save() statement will result in roughly the following SQL:

UPDATE books_publisher SET
    name = 'Apress Publishing',
    address = '2855 Telegraph Ave.',
    city = 'Berkeley',
    state_province = 'CA',
    country = 'U.S.A.',
    website = 'http://www.apress.com'
WHERE id = 52;

Yes, note that all of the fields will be updated, not just the ones that have been changed. Depending on your application, this may cause a race condition. See “Updating Multiple Objects in One Statement” below to find out how to execute this (slightly different) query:

UPDATE books_publisher SET
    name = 'Apress Publishing'
WHERE id=52;

Selecting Objects

Knowing how to create and update database records is essential, but chances are that the Web applications you’ll build will be doing more querying of existing objects than creating new ones. We’ve already seen a way to retrieve every record for a given model:

>>> Publisher.objects.all()
[<Publisher: Apress>, <Publisher: O'Reilly>]

This roughly translates to this SQL:

SELECT id, name, address, city, state_province, country, website
FROM books_publisher;

Let’s take a close look at each part of this Publisher.objects.all() line:

• First, we have the model we defined, Publisher. No surprise here: when you want to look up data, you use the model for that data.

• Next, we have the objects attribute. This is called a manager. Managers are discussed in detail in Chapter 10. For now, all you need to know is that managers take care of all “table-level” operations on data including, most important, data lookup.

  All models automatically get a objects manager; you’ll use it any time you want to look up model instances.

• Finally, we have all(). This is a method on the objects manager that returns all the rows in the database. Though this object looks like a list, it’s actually a QuerySet – an object that represents a specific set of rows from the database. Appendix C deals with QuerySets in detail. For the rest of this chapter, we’ll just treat them like the lists they emulate.

Any database lookup is going to follow this general pattern – we’ll call methods on the manager attached to the model we want to query against.

>>> Publisher.objects.filter(name='Apress')
[<Publisher: Apress>]

SELECT id, name, address, city, state_province, country, website
FROM books_publisher
WHERE name = 'Apress';

>>> Publisher.objects.filter(country="U.S.A.", state_province="CA")
[<Publisher: Apress>]

SELECT id, name, address, city, state_province, country, website
FROM books_publisher
WHERE country = 'U.S.A.'
AND state_province = 'CA';

>>> Publisher.objects.filter(name__contains="press")
[<Publisher: Apress>]

SELECT id, name, address, city, state_province, country, website
FROM books_publisher
WHERE name LIKE '%press%';

>>> Publisher.objects.get(name="Apress")
<Publisher: Apress>

>>> Publisher.objects.get(country="U.S.A.")
Traceback (most recent call last):
    ...
MultipleObjectsReturned: get() returned more than one Publisher --
    it returned 2! Lookup parameters were {'country': 'U.S.A.'}

>>> Publisher.objects.get(name="Penguin")
Traceback (most recent call last):
    ...
DoesNotExist: Publisher matching query does not exist.

try:
    p = Publisher.objects.get(name='Apress')
except Publisher.DoesNotExist:
    print "Apress isn't in the database yet."
else:
    print "Apress is in the database."

>>> Publisher.objects.order_by("name")
[<Publisher: Apress>, <Publisher: O'Reilly>]

SELECT id, name, address, city, state_province, country, website
FROM books_publisher
ORDER BY name;

>>> Publisher.objects.order_by("address")
[<Publisher: O'Reilly>, <Publisher: Apress>]

>>> Publisher.objects.order_by("state_province")
[<Publisher: Apress>, <Publisher: O'Reilly>]

>>> Publisher.objects.order_by("state_province", "address")
 [<Publisher: Apress>, <Publisher: O'Reilly>]

>>> Publisher.objects.order_by("-name")
[<Publisher: O'Reilly>, <Publisher: Apress>]

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()

    def __unicode__(self):
        return self.name

    class Meta:
        ordering = ['name']

>>> Publisher.objects.filter(country="U.S.A.").order_by("-name")
[<Publisher: O'Reilly>, <Publisher: Apress>]

SELECT id, name, address, city, state_province, country, website
FROM books_publisher
WHERE country = 'U.S.A'
ORDER BY name DESC;

>>> Publisher.objects.order_by('name')[0]
<Publisher: Apress>

SELECT id, name, address, city, state_province, country, website
FROM books_publisher
ORDER BY name
LIMIT 1;

>>> Publisher.objects.order_by('name')[0:2]

SELECT id, name, address, city, state_province, country, website
FROM books_publisher
ORDER BY name
OFFSET 0 LIMIT 2;

>>> Publisher.objects.order_by('name')[-1]
Traceback (most recent call last):
  ...
AssertionError: Negative indexing is not supported.

>>> Publisher.objects.order_by('-name')[0]

>>> p = Publisher.objects.get(name='Apress')
>>> p.name = 'Apress Publishing'
>>> p.save()

SELECT id, name, address, city, state_province, country, website
FROM books_publisher
WHERE name = 'Apress';

UPDATE books_publisher SET
    name = 'Apress Publishing',
    address = '2855 Telegraph Ave.',
    city = 'Berkeley',
    state_province = 'CA',
    country = 'U.S.A.',
    website = 'http://www.apress.com'
WHERE id = 52;

>>> Publisher.objects.filter(id=52).update(name='Apress Publishing')

UPDATE books_publisher
SET name = 'Apress Publishing'
WHERE id = 52;

>>> Publisher.objects.all().update(country='USA')
2

Deleting Objects

To delete an object from your database, simply call the object’s delete() method:

>>> p = Publisher.objects.get(name="O'Reilly")
>>> p.delete()
>>> Publisher.objects.all()
[<Publisher: Apress Publishing>]

You can also delete objects in bulk by calling delete() on the result of any QuerySet. This is similar to the update() method we showed in the last section:

>>> Publisher.objects.filter(country='USA').delete()
>>> Publisher.objects.all().delete()
>>> Publisher.objects.all()
[]

Be careful deleting your data! As a precaution against deleting all of the data in a particular table, Django requires you to explicitly use all() if you want to delete everything in your table. For example, this won’t work:

>>> Publisher.objects.delete()
Traceback (most recent call last):
  File "<console>", line 1, in <module>
AttributeError: 'Manager' object has no attribute 'delete'

But it’ll work if you add the all() method:

>>> Publisher.objects.all().delete()

If you’re just deleting a subset of your data, you don’t need to include all(). To repeat a previous example:

>>> Publisher.objects.filter(country='USA').delete()

What’s Next?

Having read this chapter, you have enough knowledge of Django models to be able to write basic database applications. Chapter 10 will provide some information on more advanced usage of Django’s database layer.

Once you’ve defined your models, the next step is to populate your database with data. You might have legacy data, in which case Chapter 18 will give you advice about integrating with legacy databases. You might rely on site users to supply your data, in which case Chapter 7 will teach you how to process user-submitted form data.

But in some cases, you or your team might need to enter data manually, in which case it would be helpful to have a Web-based interface for entering and managing data. The next chapter Chapter 6 covers Django’s admin interface, which exists precisely for that reason.