======================
Database API reference
======================

Once you've created your `data models`_, Django automatically gives you a
database-abstraction API that lets you create, retrieve, update and delete
objects. This document explains that API.

.. _`data models`: http://www.djangoproject.com/documentation/model_api/

Throughout this reference, we'll refer to the following models, which comprise
a weblog application::

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

        def __str__(self):
            return self.name

    class Author(models.Model):
        name = models.CharField(maxlength=50)
        email = models.URLField()

        def __str__(self):
            return self.name

    class Entry(models.Model):
        blog = models.ForeignKey(Blog)
        headline = models.CharField(maxlength=255)
        body_text = models.TextField()
        pub_date = models.DateTimeField()
        authors = models.ManyToManyField(Author)

        def __str__(self):
            return self.headline

Creating objects
================

To represent database-table data in Python objects, Django uses an intuitive
system: A model class represents a database table, and an instance of that
class represents a particular record in the database table.

To create an object, instantiate it using keyword arguments to the model class,
then call ``save()`` to save it to the database.

You import the model class from wherever it lives on the Python path, as you
may expect. (We point this out here because previous Django versions required
funky model importing.)

Assuming models live in a file ``mysite/blog/models.py``, here's an example::

    from mysite.blog.models import Blog
    b = Blog(name='Beatles Blog', tagline='All the latest Beatles news.')
    b.save()

This performs an ``INSERT`` SQL statement behind the scenes. Django doesn't hit
the database until you explicitly call ``save()``.

The ``save()`` method has no return value.

To create an object and save it all in one step see the `create`__ method.

__ `create(**kwargs)`_

Auto-incrementing primary keys
------------------------------

If a model has an ``AutoField`` -- an auto-incrementing primary key -- then
that auto-incremented value will be calculated and saved as an attribute on
your object the first time you call ``save()``.

Example::

    b2 = Blog(name='Cheddar Talk', tagline='Thoughts on cheese.')
    b2.id     # Returns None, because b doesn't have an ID yet.
    b2.save()
    b2.id     # Returns the ID of your new object.

There's no way to tell what the value of an ID will be before you call
``save()``, because that value is calculated by your database, not by Django.

(For convenience, each model has an ``AutoField`` named ``id`` by default
unless you explicitly specify ``primary_key=True`` on a field. See the
`AutoField documentation`_.)

.. _AutoField documentation: http://www.djangoproject.com/documentation/model_api/#autofield

Explicitly specifying auto-primary-key values
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

If a model has an ``AutoField`` but you want to define a new object's ID
explicitly when saving, just define it explicitly before saving, rather than
relying on the auto-assignment of the ID.

Example::

    b3 = Blog(id=3, name='Cheddar Talk', tagline='Thoughts on cheese.')
    b3.id     # Returns 3.
    b3.save()
    b3.id     # Returns 3.

If you assign auto-primary-key values manually, make sure not to use an
already-existing primary-key value! If you create a new object with an explicit
primary-key value that already exists in the database, Django will assume
you're changing the existing record rather than creating a new one.

Given the above ``'Cheddar Talk'`` blog example, this example would override
the previous record in the database::

    b4 = Blog(id=3, name='Not Cheddar', tagline='Anything but cheese.')
    b4.save()  # Overrides the previous blog with ID=3!

See _`How Django knows to UPDATE vs. INSERT`, below, for the reason this
happens.

Explicitly specifying auto-primary-key values is mostly useful for bulk-saving
objects, when you're confident you won't have primary-key collision.

Saving changes to objects
=========================

To save changes to an object that's already in the database, use ``save()``.

Given a ``Blog`` instance ``b5`` that has already been saved to the database,
this example changes its name and updates its record in the database::

    b5.name = 'New name'
    b5.save()

This performs an ``UPDATE`` SQL statement behind the scenes. Django doesn't hit
the database until you explicitly call ``save()``.

The ``save()`` method has no return value.

How Django knows to UPDATE vs. INSERT
-------------------------------------

You may have noticed Django database objects use the same ``save()`` method
for creating and changing objects. Django abstracts the need to use ``INSERT``
or ``UPDATE`` SQL statements. Specifically, when you call ``save()``, Django
follows this algorithm:

    * If the object's primary key attribute is set to a value that evaluates to
      ``False`` (such as ``None`` or the empty string), Django executes a
      ``SELECT`` query to determine whether a record with the given primary key
      already exists.
    * If the record with the given primary key does already exist, Django
      executes an ``UPDATE`` query.
    * If the object's primary key attribute is *not* set, or if it's set but a
      record doesn't exist, Django executes an ``INSERT``.

The one gotcha here is that you should be careful not to specify a primary-key
value explicitly when saving new objects, if you cannot guarantee the
primary-key value is unused. For more on this nuance, see
"Explicitly specifying auto-primary-key values" above.

Retrieving objects
==================

To retrieve objects from your database, you construct a ``QuerySet`` via a
``Manager`` on your model class.

A ``QuerySet`` represents a collection of objects from your database. It can
have zero, one or many *filters* -- criteria that narrow down the collection
based on given parameters. In SQL terms, a ``QuerySet`` equates to a ``SELECT``
statement, and a filter is a limiting clause such as ``WHERE`` or ``LIMIT``.

You get a ``QuerySet`` by using your model's ``Manager``. Each model has at
least one ``Manager``, and it's called ``objects`` by default. Access it
directly via the model class, like so::

    Blog.objects  # <django.db.models.manager.Manager object at ...>
    b = Blog(name='Foo', tagline='Bar')
    b.objects     # AttributeError: "Manager isn't accessible via Blog instances."

(``Managers`` are accessible only via model classes, rather than from model
instances, to enforce a separation between "table-level" operations and
"record-level" operations.)

The ``Manager`` is the main source of ``QuerySets`` for a model. It acts as a
"root" ``QuerySet`` that describes all objects in the model's database table.
For example, ``Blog.objects`` is the initial ``QuerySet`` that contains all
``Blog`` objects in the database.

Retrieving all objects
----------------------

The simplest way to retrieve objects from a table is to get all of them.
To do this, use the ``all()`` method on a ``Manager``.

Example::

    all_entries = Entry.objects.all()

The ``all()`` method returns a ``QuerySet`` of all the objects in the database.

(If ``Entry.objects`` is a ``QuerySet``, why can't we just do ``Entry.objects``?
That's because ``Entry.objects``, the root ``QuerySet``, is a special case
that cannot be evaluated. The ``all()`` method returns a ``QuerySet`` that
*can* be evaluated.)

Filtering objects
-----------------

The root ``QuerySet`` provided by the ``Manager`` describes all objects in the
database table. Usually, though, you'll need to select only a subset of the
complete set of objects.

To create such a subset, you refine the initial ``QuerySet``, adding filter
conditions. The two most common ways to refine a ``QuerySet`` are:

``filter(**kwargs)``
    Returns a new ``QuerySet`` containing objects that match the given lookup
    parameters.

``exclude(**kwargs)``
    Returns a new ``QuerySet`` containing objects that do *not* match the given
    lookup parameters.

The lookup parameters (``**kwargs`` in the above function definitions) should
be in the format described in `Field lookups`_ below.

For example, to get a ``QuerySet`` of blog entries from the year 2006, use
``filter()`` like so::

    Entry.objects.filter(pub_date__year=2006)

(Note we don't have to add an ``all()`` -- ``Entry.objects.all().filter(...)``.
That would still work, but you only need ``all()`` when you want all objects
from the root ``QuerySet``.)

Chaining filters
~~~~~~~~~~~~~~~~

The result of refining a ``QuerySet`` is itself a ``QuerySet``, so it's
possible to chain refinements together. For example::

    Entry.objects.filter(
        headline__startswith='What').exclude(
            pub_date__gte=datetime.now()).filter(
                pub_date__gte=datetime(2005, 1, 1))

...takes the initial ``QuerySet`` of all entries in the database, adds a
filter, then an exclusion, then another filter. The final result is a
``QuerySet`` containing all entries with a headline that starts with "What",
that were published between January 1, 2005, and the current day.

Filtered QuerySets are unique
-----------------------------

Each time you refine a ``QuerySet``, you get a brand-new ``QuerySet`` that is
in no way bound to the previous ``QuerySet``. Each refinement creates a
separate and distinct ``QuerySet`` that can be stored, used and reused.

Example::

    q1 = Entry.objects.filter(headline__startswith="What")
    q2 = q1.exclude(pub_date__gte=datetime.now())
    q3 = q1.filter(pub_date__gte=datetime.now())

These three ``QuerySets`` are separate. The first is a base ``QuerySet``
containing all entries that contain a headline starting with "What". The second
is a subset of the first, with an additional criteria that excludes records
whose ``pub_date`` is greater than now. The third is a subset of the first,
with an additional criteria that selects only the records whose ``pub_date`` is
greater than now. The initial ``QuerySet`` (``q1``) is unaffected by the
refinement process.

QuerySets are lazy
------------------

``QuerySets`` are lazy -- the act of creating a ``QuerySet`` doesn't involve
any database activity. You can stack filters together all day long, and Django
won't actually run the query until the ``QuerySet`` is *evaluated*.

When QuerySets are evaluated
~~~~~~~~~~~~~~~~~~~~~~~~~~~~

You can evaluate a ``QuerySet`` in the following ways:

    * **Iteration.** A ``QuerySet`` is iterable, and it executes its database
      query the first time you iterate over it. For example, this will print
      the headline of all entries in the database::

          for e in Entry.objects.all():
              print e.headline

    * **Slicing.** As explained in `Limiting QuerySets`_ below, a ``QuerySet``
      can be sliced, using Python's array-slicing syntax. Usually slicing a
      ``QuerySet`` returns another (unevaluated )``QuerySet``, but Django will
      execute the database query if you use the "step" parameter of slice
      syntax.

    * **repr().** A ``QuerySet`` is evaluated when you call ``repr()`` on it.
      This is for convenience in the Python interactive interpreter, so you can
      immediately see your results when using the API interactively.

    * **len().** A ``QuerySet`` is evaluated when you call ``len()`` on it.
      This, as you might expect, returns the length of the result list.

      Note: *Don't* use ``len()`` on ``QuerySet``\s if all you want to do is
      determine the number of records in the set. It's much more efficient to
      handle a count at the database level, using SQL's ``SELECT COUNT(*)``,
      and Django provides a ``count()`` method for precisely this reason. See
      ``count()`` below.

    * **list().** Force evaluation of a ``QuerySet`` by calling ``list()`` on
      it. For example::

          entry_list = list(Entry.objects.all())

      Be warned, though, that this could have a large memory overhead, because
      Django will load each element of the list into memory. In contrast,
      iterating over a ``QuerySet`` will take advantage of your database to
      load data and instantiate objects only as you need them.

Limiting QuerySets
------------------

Use Python's array-slicing syntax to limit your ``QuerySet`` to a certain
number of results. This is the equivalent of SQL's ``LIMIT`` and ``OFFSET``
clauses.

For example, this returns the first 5 objects (``LIMIT 5``)::

    Entry.objects.all()[:5]

This returns the fifth through tenth objects (``OFFSET 5 LIMIT 5``)::

    Entry.objects.all()[5:10]

Generally, slicing a ``QuerySet`` returns a new ``QuerySet`` -- it doesn't
evaluate the query. An exception is if you use the "step" parameter of Python
slice syntax. For example, this would actually execute the query in order to
return a list of every *second* object of the first 10::

    Entry.objects.all()[:10:2]

To retrieve a *single* object rather than a list
(e.g. ``SELECT foo FROM bar LIMIT 1``), use a simple index instead of a
slice. For example, this returns the first ``Entry`` in the database, after
ordering entries alphabetically by headline::

    Entry.objects.order_by('headline')[0]

This is roughly equivalent to::

    Entry.objects.order_by('headline')[0:1].get()

Note, however, that the first of these will raise ``IndexError`` while the
second will raise ``DoesNotExist`` if no objects match the given criteria.

QuerySet methods that return new QuerySets
------------------------------------------

Django provides a range of ``QuerySet`` refinement methods that modify either
the types of results returned by the ``QuerySet`` or the way its SQL query is
executed.

``filter(**kwargs)``
~~~~~~~~~~~~~~~~~~~~

Returns a new ``QuerySet`` containing objects that match the given lookup
parameters.

The lookup parameters (``**kwargs``) should be in the format described in
`Field lookups`_ below. Multiple parameters are joined via ``AND`` in the
underlying SQL statement.

``exclude(**kwargs)``
~~~~~~~~~~~~~~~~~~~~~

Returns a new ``QuerySet`` containing objects that do *not* match the given
lookup parameters.

The lookup parameters (``**kwargs``) should be in the format described in
`Field lookups`_ below. Multiple parameters are joined via ``AND`` in the
underlying SQL statement, and the whole thing is enclosed in a ``NOT()``.

This example excludes all entries whose ``pub_date`` is the current date/time
AND whose ``headline`` is "Hello"::

    Entry.objects.exclude(pub_date__gt=datetime.date(2005, 1, 3), headline='Hello')

In SQL terms, that evaluates to::

    SELECT ...
    WHERE NOT (pub_date > '2005-1-3' AND headline = 'Hello')

This example excludes all entries whose ``pub_date`` is the current date/time
OR whose ``headline`` is "Hello"::

    Entry.objects.exclude(pub_date__gt=datetime.date(2005, 1, 3)).exclude(headline='Hello')

In SQL terms, that evaluates to::

    SELECT ...
    WHERE NOT pub_date > '2005-1-3'
    AND NOT headline = 'Hello'

Note the second example is more restrictive.

``order_by(*fields)``
~~~~~~~~~~~~~~~~~~~~~

By default, results returned by a ``QuerySet`` are ordered by the ordering
tuple given by the ``ordering`` option in the model's ``Meta``. You can
override this on a per-``QuerySet`` basis by using the ``order_by`` method.

Example::

    Entry.objects.filter(pub_date__year=2005).order_by('-pub_date', 'headline')

The result above will be ordered by ``pub_date`` descending, then by
``headline`` ascending. The negative sign in front of ``"-pub_date"`` indicates
*descending* order. Ascending order is implied. To order randomly, use ``"?"``,
like so::

    Entry.objects.order_by('?')

To order by a field in a different table, add the other table's name and a dot,
like so::

    Entry.objects.order_by('blogs_blog.name', 'headline')

There's no way to specify whether ordering should be case sensitive. With
respect to case-sensitivity, Django will order results however your database
backend normally orders them.

``distinct()``
~~~~~~~~~~~~~~

Returns a new ``QuerySet`` that uses ``SELECT DISTINCT`` in its SQL query. This
eliminates duplicate rows from the query results.

By default, a ``QuerySet`` will not eliminate duplicate rows. In practice, this
is rarely a problem, because simple queries such as ``Blog.objects.all()``
don't introduce the possibility of duplicate result rows.

However, if your query spans multiple tables, it's possible to get duplicate
results when a ``QuerySet`` is evaluated. That's when you'd use ``distinct()``.

``values(*fields)``
~~~~~~~~~~~~~~~~~~~

Returns a ``ValuesQuerySet`` -- a ``QuerySet`` that evaluates to a list of
dictionaries instead of model-instance objects.

Each of those dictionaries represents an object, with the keys corresponding to
the attribute names of model objects.

This example compares the dictionaries of ``values()`` with the normal model
objects::

    # This list contains a Blog object.
    >>> Blog.objects.filter(name__startswith='Beatles')
    [Beatles Blog]

    # This list contains a dictionary.
    >>> Blog.objects.filter(name__startswith='Beatles').values()
    [{'id': 1, 'name': 'Beatles Blog', 'tagline': 'All the latest Beatles news.'}]

``values()`` takes optional positional arguments, ``*fields``, which specify
field names to which the ``SELECT`` should be limited. If you specify the
fields, each dictionary will contain only the field keys/values for the fields
you specify. If you don't specify the fields, each dictionary will contain a
key and value for every field in the database table.

Example::

    >>> Blog.objects.values()
    [{'id': 1, 'name': 'Beatles Blog', 'tagline': 'All the latest Beatles news.'}],
    >>> Blog.objects.values('id', 'name')
    [{'id': 1, 'name': 'Beatles Blog'}]

A ``ValuesQuerySet`` is useful when you know you're only going to need values
from a small number of the available fields and you won't need the
functionality of a model instance object. It's more efficient to select only
the fields you need to use.

Finally, note a ``ValuesQuerySet`` is a subclass of ``QuerySet``, so it has all
methods of ``QuerySet``. You can call ``filter()`` on it, or ``order_by()``, or
whatever. Yes, that means these two calls are identical::

    Blog.objects.values().order_by('id')
    Blog.objects.order_by('id').values()

The people who made Django prefer to put all the SQL-affecting methods first,
followed (optionally) by any output-affecting methods (such as ``values()``),
but it doesn't really matter. This is your chance to really flaunt your
individualism.

``dates(field, kind, order='ASC')``
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Returns a ``DateQuerySet`` -- a ``QuerySet`` that evaluates to a list of
``datetime.datetime`` objects representing all available dates of a particular
kind within the contents of the ``QuerySet``.

``field`` should be the name of a ``DateField`` or ``DateTimeField`` of your
model.

``kind`` should be either ``"year"``, ``"month"`` or ``"day"``. Each
``datetime.datetime`` object in the result list is "truncated" to the given
``type``.

    * ``"year"`` returns a list of all distinct year values for the field.
    * ``"month"`` returns a list of all distinct year/month values for the field.
    * ``"day"`` returns a list of all distinct year/month/day values for the field.

``order``, which defaults to ``'ASC'``, should be either ``'ASC'`` or
``'DESC'``. This specifies how to order the results.

Examples::

    >>> Entry.objects.dates('pub_date', 'year')
    [datetime.datetime(2005, 1, 1)]
    >>> Entry.objects.dates('pub_date', 'month')
    [datetime.datetime(2005, 2, 1), datetime.datetime(2005, 3, 1)]
    >>> Entry.objects.dates('pub_date', 'day')
    [datetime.datetime(2005, 2, 20), datetime.datetime(2005, 3, 20)]
    >>> Entry.objects.dates('pub_date', 'day', order='DESC')
    [datetime.datetime(2005, 3, 20), datetime.datetime(2005, 2, 20)]
    >>> Entry.objects.filter(headline__contains='Lennon').dates('pub_date', 'day')
    [datetime.datetime(2005, 3, 20)]

``select_related()``
~~~~~~~~~~~~~~~~~~~~

Returns a ``QuerySet`` that will automatically "follow" foreign-key
relationships, selecting that additional related-object data when it executes
its query. This is a performance booster which results in (sometimes much)
larger queries but means later use of foreign-key relationships won't require
database queries.

The following examples illustrate the difference between plain lookups and
``select_related()`` lookups. Here's standard lookup::

    # Hits the database.
    e = Entry.objects.get(id=5)

    # Hits the database again to get the related Blog object.
    b = e.blog

And here's ``select_related`` lookup::

    # Hits the database.
    e = Entry.objects.select_related().get(id=5)

    # Doesn't hit the database, because e.blog has been prepopulated
    # in the previous query.
    b = e.blog

``select_related()`` follows foreign keys as far as possible. If you have the
following models::

    class City(models.Model):
        # ...

    class Person(models.Model):
        # ...
        hometown = models.ForeignKey(City)

    class Book(models.Model):
        # ...
        author = models.ForeignKey(Person)

...then a call to ``Book.objects.select_related().get(id=4)`` will cache the
related ``Person`` *and* the related ``City``::

    b = Book.objects.select_related().get(id=4)
    p = b.author         # Doesn't hit the database.
    c = p.hometown       # Doesn't hit the database.

    sv = Book.objects.get(id=4) # No select_related() in this example.
    p = b.author         # Hits the database.
    c = p.hometown       # Hits the database.

Note that ``select_related()`` does not follow foreign keys that have
``null=True``.

``extra(select=None, where=None, params=None, tables=None)``
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Sometimes, the Django query syntax by itself can't easily express a complex
``WHERE`` clause. For these edge cases, Django provides the ``extra()``
``QuerySet`` modifier -- a hook for injecting specific clauses into the SQL
generated by a ``QuerySet``.

By definition, these extra lookups may not be portable to different database
engines (because you're explicitly writing SQL code) and violate the DRY
principle, so you should avoid them if possible.

Specify one or more of ``params``, ``select``, ``where`` or ``tables``. None
of the arguments is required, but you should use at least one of them.

``select``
    The ``select`` argument lets you put extra fields in the ``SELECT`` clause.
    It should be a dictionary mapping attribute names to SQL clauses to use to
    calculate that attribute.

    Example::

        Entry.objects.extra(select={'is_recent': "pub_date > '2006-01-01'"})

    As a result, each ``Entry`` object will have an extra attribute,
    ``is_recent``, a boolean representing whether the entry's ``pub_date`` is
    greater than Jan. 1, 2006.

    Django inserts the given SQL snippet directly into the ``SELECT``
    statement, so the resulting SQL of the above example would be::

        SELECT blog_entry.*, (pub_date > '2006-01-01')
        FROM blog_entry;


    The next example is more advanced; it does a subquery to give each
    resulting ``Blog`` object an ``entry_count`` attribute, an integer count
    of associated ``Entry`` objects::

        Blog.objects.extra(
            select={
                'entry_count': 'SELECT COUNT(*) FROM blog_entry WHERE blog_entry.blog_id = blog_blog.id'
            },
        )

    (In this particular case, we're exploiting the fact that the query will
    already contain the ``blog_blog`` table in its ``FROM`` clause.)

    The resulting SQL of the above example would be::

        SELECT blog_blog.*, (SELECT COUNT(*) FROM blog_entry WHERE blog_entry.blog_id = blog_blog.id)
        FROM blog_blog;

    Note that the parenthesis required by most database engines around
    subqueries are not required in Django's ``select`` clauses. Also note that
    some database backends, such as some MySQL versions, don't support
    subqueries.

``where`` / ``tables``
    You can define explicit SQL ``WHERE`` clauses -- perhaps to perform
    non-explicit joins -- by using ``where``. You can manually add tables to
    the SQL ``FROM`` clause by using ``tables``.

    ``where`` and ``tables`` both take a list of strings. All ``where``
    parameters are "AND"ed to any other search criteria.

    Example::

        Entry.objects.extra(where=['id IN (3, 4, 5, 20)'])

    ...translates (roughly) into the following SQL::

        SELECT * FROM blog_entry WHERE id IN (3, 4, 5, 20);

``params``
    The ``select`` and ``where`` parameters described above may use standard
    Python database string placeholders -- ``'%s'`` to indicate parameters the
    database engine should automatically quote. The ``params`` argument is a
    list of any extra parameters to be substituted.

    Example::

        Entry.objects.extra(where=['headline=%s'], params=['Lennon'])

    Always use ``params`` instead of embedding values directly into ``select``
    or ``where`` because ``params`` will ensure values are quoted correctly
    according to your particular backend. (For example, quotes will be escaped
    correctly.)

    Bad::

        Entry.objects.extra(where=["headline='Lennon'"])

    Good::

        Entry.objects.extra(where=['headline=%s'], params=['Lennon'])

QuerySet methods that do not return QuerySets
---------------------------------------------

The following ``QuerySet`` methods evaluate the ``QuerySet`` and return
something *other than* a ``QuerySet``.

These methods do not use a cache (see _`Caching and QuerySets` below). Rather,
they query the database each time they're called.

``get(**kwargs)``
~~~~~~~~~~~~~~~~~

Returns the object matching the given lookup parameters, which should be in
the format described in `Field lookups`_.

``get()`` raises ``AssertionError`` if more than one object was found.

``get()`` raises a ``DoesNotExist`` exception if an object wasn't found for the
given parameters. The ``DoesNotExist`` exception is an attribute of the model
class. Example::

    Entry.objects.get(id='foo') # raises Entry.DoesNotExist

The ``DoesNotExist`` exception inherits from
``django.core.exceptions.ObjectDoesNotExist``, so you can target multiple
``DoesNotExist`` exceptions. Example::

    from django.core.exceptions import ObjectDoesNotExist
    try:
        e = Entry.objects.get(id=3)
        b = Blog.objects.get(id=1)
    except ObjectDoesNotExist:
        print "Either the entry or blog doesn't exist."

``create(**kwargs)``
~~~~~~~~~~~~~~~~~~~~

A convenience method for creating an object and saving it all in one step.  Thus::

    p = Person.objects.create(first_name="Bruce", last_name="Springsteen")

and::

    p = Person(first_name="Bruce", last_name="Springsteen")
    p.save()

are equivalent.

``get_or_create(**kwargs)``
~~~~~~~~~~~~~~~~~~~~~~~~~~~

A convenience method for looking up an object with the given kwargs, creating
one if necessary.

Returns a tuple of ``(object, created)``, where ``object`` is the retrieved or
created object and ``created`` is a boolean specifying whether a new object was
created.

This is meant as a shortcut to boilerplatish code and is mostly useful for
data-import scripts. For example::

    try:
        obj = Person.objects.get(first_name='John', last_name='Lennon')
    except Person.DoesNotExist:
        obj = Person(first_name='John', last_name='Lennon', birthday=date(1940, 10, 9))
        obj.save()

This pattern gets quite unwieldy as the number of fields in a model goes up.
The above example can be rewritten using ``get_or_create()`` like so::

    obj, created = Person.objects.get_or_create(first_name='John', last_name='Lennon',
                      defaults={'birthday': date(1940, 10, 9)})

Any keyword arguments passed to ``get_or_create()`` -- *except* an optional one
called ``defaults`` -- will be used in a ``get()`` call. If an object is found,
``get_or_create()`` returns a tuple of that object and ``False``. If an object
is *not* found, ``get_or_create()`` will instantiate and save a new object,
returning a tuple of the new object and ``True``. The new object will be
created according to this algorithm::

    defaults = kwargs.pop('defaults', {})
    params = dict([(k, v) for k, v in kwargs.items() if '__' not in k])
    params.update(defaults)
    obj = self.model(**params)
    obj.save()

In English, that means start with any non-``'defaults'`` keyword argument that
doesn't contain a double underscore (which would indicate a non-exact lookup).
Then add the contents of ``defaults``, overriding any keys if necessary, and
use the result as the keyword arguments to the model class.

If you have a field named ``defaults`` and want to use it as an exact lookup in
``get_or_create()``, just use ``'defaults__exact'``, like so::

    Foo.objects.get_or_create(defaults__exact='bar', defaults={'defaults': 'baz'})

Finally, a word on using ``get_or_create()`` in Django views. As mentioned
earlier, ``get_or_create()`` is mostly useful in scripts that need to parse
data and create new records if existing ones aren't available. But if you need
to use ``get_or_create()`` in a view, please make sure to use it only in
``POST`` requests unless you have a good reason not to. ``GET`` requests
shouldn't have any effect on data; use ``POST`` whenever a request to a page
has a side effect on your data. For more, see `Safe methods`_ in the HTTP spec.

.. _Safe methods: http://www.w3.org/Protocols/rfc2616/rfc2616-sec9.html#sec9.1.1

``count()``
~~~~~~~~~~~

Returns an integer representing the number of objects in the database matching
the ``QuerySet``. ``count()`` never raises exceptions.

Example::

    # Returns the total number of entries in the database.
    Entry.objects.count()

    # Returns the number of entries whose headline contains 'Lennon'
    Entry.objects.filter(headline__contains='Lennon').count()

``count()`` performs a ``SELECT COUNT(*)`` behind the scenes, so you should
always use ``count()`` rather than loading all of the record into Python
objects and calling ``len()`` on the result.

Depending on which database you're using (e.g. PostgreSQL vs. MySQL),
``count()`` may return a long integer instead of a normal Python integer. This
is an underlying implementation quirk that shouldn't pose any real-world
problems.

``in_bulk(id_list)``
~~~~~~~~~~~~~~~~~~~~

Takes a list of primary-key values and returns a dictionary mapping each
primary-key value to an instance of the object with the given ID.

Example::

    >>> Blog.objects.in_bulk([1])
    {1: Beatles Blog}
    >>> Blog.objects.in_bulk([1, 2])
    {1: Beatles Blog, 2: Cheddar Talk}
    >>> Blog.objects.in_bulk([])
    {}

If you pass ``in_bulk()`` an empty list, you'll get an empty dictionary.

``latest(field_name=None)``
~~~~~~~~~~~~~~~~~~~~~~~~~~~

Returns the latest object in the table, by date, using the ``field_name``
provided as the date field.

This example returns the latest ``Entry`` in the table, according to the
``pub_date`` field::

    Entry.objects.latest('pub_date')

If your model's ``Meta`` specifies ``get_latest_by``, you can leave off the
``field_name`` argument to ``latest()``. Django will use the field specified in
``get_latest_by`` by default.

Like ``get()``, ``latest()`` raises ``DoesNotExist`` if an object doesn't
exist with the given parameters.

Note ``latest()`` exists purely for convenience and readability.

Field lookups
-------------

Field lookups are how you specify the meat of an SQL ``WHERE`` clause. They're
specified as keyword arguments to the ``QuerySet`` methods ``filter()``,
``exclude()`` and ``get()``.

Basic lookups keyword arguments take the form ``field__lookuptype=value``.
(That's a double-underscore). For example::

    Entry.objects.filter(pub_date__lte='2006-01-01')

translates (roughly) into the following SQL::

    SELECT * FROM blog_entry WHERE pub_date <= '2006-01-01';

.. admonition:: How this is possible

   Python has the ability to define functions that accept arbitrary name-value
   arguments whose names and values are evaluated at runtime. For more
   information, see `Keyword Arguments`_ in the official Python tutorial.

   .. _`Keyword Arguments`: http://docs.python.org/tut/node6.html#SECTION006720000000000000000

If you pass an invalid keyword argument, a lookup function will raise
``TypeError``.

The database API supports the following lookup types:

exact
~~~~~

Exact match.

Example::

    Entry.objects.get(id__exact=14)

SQL equivalent::

    SELECT ... WHERE id = 14;

iexact
~~~~~~

Case-insensitive exact match.

Example::

    Blog.objects.get(name__iexact='beatles blog')

SQL equivalent::

    SELECT ... WHERE name ILIKE 'beatles blog';

Note this will match ``'Beatles Blog'``, ``'beatles blog'``,
``'BeAtLes BLoG'``, etc.

contains
~~~~~~~~

Case-sensitive containment test.

Example::

    Entry.objects.get(headline__contains='Lennon')

SQL equivalent::

    SELECT ... WHERE headline LIKE '%Lennon%';

Note this will match the headline ``'Today Lennon honored'`` but not
``'today lennon honored'``.

SQLite doesn't support case-sensitive ``LIKE`` statements; ``contains`` acts
like ``icontains`` for SQLite.

icontains
~~~~~~~~~

Case-insensitive containment test.

Example::

    Entry.objects.get(headline__icontains='Lennon')

SQL equivalent::

    SELECT ... WHERE headline ILIKE '%Lennon%';

gt
~~

Greater than.

Example::

    Entry.objects.filter(id__gt=4)

SQL equivalent::

    SELECT ... WHERE id > 4;

gte
~~~

Greater than or equal to.

lt
~~

Less than.

lte
~~~

Less than or equal to.

in
~~

In a given list.

Example::

    Entry.objects.filter(id__in=[1, 3, 4])

SQL equivalent::

    SELECT ... WHERE id IN (1, 3, 4);

startswith
~~~~~~~~~~

Case-sensitive starts-with.

Example::

    Entry.objects.filter(headline__startswith='Will')

SQL equivalent::

    SELECT ... WHERE headline LIKE 'Will%';

SQLite doesn't support case-sensitive ``LIKE`` statements; ``startswith`` acts
like ``istartswith`` for SQLite.

istartswith
~~~~~~~~~~~

Case-insensitive starts-with.

Example::

    Entry.objects.filter(headline__istartswith='will')

SQL equivalent::

    SELECT ... WHERE headline ILIKE 'Will%';

endswith
~~~~~~~~

Case-sensitive ends-with.

Example::

    Entry.objects.filter(headline__endswith='cats')

SQL equivalent::

    SELECT ... WHERE headline LIKE '%cats';

SQLite doesn't support case-sensitive ``LIKE`` statements; ``endswith`` acts
like ``iendswith`` for SQLite.

iendswith
~~~~~~~~~

Case-insensitive ends-with.

Example::

    Entry.objects.filter(headline__iendswith='will')

SQL equivalent::

    SELECT ... WHERE headline ILIKE '%will'

range
~~~~~

Range test (inclusive).

Example::

    start_date = datetime.date(2005, 1, 1)
    end_date = datetime.date(2005, 3, 31)
    Entry.objects.filter(pub_date__range=(start_date, end_date))

SQL equivalent::

    SELECT ... WHERE pub_date BETWEEN '2005-01-01' and '2005-03-31';

You can use ``range`` anywhere you can use ``BETWEEN`` in SQL -- for dates,
numbers and even characters.

year
~~~~

For date/datetime fields, exact year match. Takes a four-digit year.

Example::

    Entry.objects.filter(pub_date__year=2005)

SQL equivalent::

    SELECT ... WHERE EXTRACT('year' FROM pub_date) = '2005';

(The exact SQL syntax varies for each database engine.)

month
~~~~~

For date/datetime fields, exact month match. Takes an integer 1 (January)
through 12 (December).

Example::

    Entry.objects.filter(pub_date__month=12)

SQL equivalent::

    SELECT ... WHERE EXTRACT('month' FROM pub_date) = '12';

(The exact SQL syntax varies for each database engine.)

day
~~~

For date/datetime fields, exact day match.

Example::

    Entry.objects.filter(pub_date__day=3)

SQL equivalent::

    SELECT ... WHERE EXTRACT('day' FROM pub_date) = '3';

(The exact SQL syntax varies for each database engine.)

Note this will match any record with a pub_date on the third day of the month,
such as January 3, July 3, etc.

isnull
~~~~~~

``NULL`` or ``IS NOT NULL`` match. Takes either ``True`` or ``False``, which
correspond to ``IS NULL`` and ``IS NOT NULL``, respectively.

Example::

    Entry.objects.filter(pub_date__isnull=True)

SQL equivalent::

    SELECT ... WHERE pub_date IS NULL;

search
~~~~~~

A boolean full-text search, taking advantage of full-text indexing. This is
like ``contains`` but is significantly faster due to full-text indexing.

Note this is only available in MySQL and requires direct manipulation of the
database to add the full-text index.

Default lookups are exact
-------------------------

If you don't provide a lookup type -- that is, if your keyword argument doesn't
contain a double underscore -- the lookup type is assumed to be ``exact``.

For example, the following two statements are equivalent::

    Blog.objects.get(id__exact=14) # Explicit form
    Blog.objects.get(id=14) # __exact is implied

This is for convenience, because ``exact`` lookups are the common case.

The pk lookup shortcut
----------------------

For convenience, Django provides a ``pk`` lookup type, which stands for
"primary_key". 

In the example ``Blog`` model, the primary key is the ``id`` field, so these
three statements are equivalent::

    Blog.objects.get(id__exact=14) # Explicit form
    Blog.objects.get(id=14) # __exact is implied
    Blog.objects.get(pk=14) # pk implies id__exact

The use of ``pk`` isn't limited to ``__exact`` queries -- any query term 
can be combined with ``pk`` to perform a query on the primary key of a model::

    # Get blogs entries  with id 1, 4 and 7
    Blog.objects.filter(pk__in=[1,4,7])
    # Get all blog entries with id > 14
    Blog.objects.filter(pk__gt=14) 
    
``pk`` lookups also work across joins. For example, these three statements are
equivalent::

    Entry.objects.filter(blog__id__exact=3) # Explicit form
    Entry.objects.filter(blog__id=3) # __exact is implied
    Entry.objects.filter(blog__pk=3) # __pk implies __id__exact

Lookups that span relationships
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Django offers a powerful and intuitive way to "follow" relationships in
lookups, taking care of the SQL ``JOIN``\s for you automatically, behind the
scenes. To span a relationship, just use the field name of related fields
across models, separated by double underscores, until you get to the field you
want.

This example retrieves all ``Entry`` objects with a ``Blog`` whose ``name``
is ``'Beatles Blog'``::

    Entry.objects.filter(blog__name__exact='Beatles Blog')

This spanning can be as deep as you'd like.

It works backwards, too. To refer to a "reverse" relationship, just use the
lowercase name of the model.

This example retrieves all ``Blog`` objects which have at least one ``Entry``
whose ``headline`` contains ``'Lennon'``::

    Blog.objects.filter(entry__headline__contains='Lennon')

Escaping parenthesis and underscores in LIKE statements
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The field lookups that equate to ``LIKE`` SQL statements (``iexact``,
``contains``, ``icontains``, ``startswith``, ``istartswith``, ``endswith``
and ``iendswith``) will automatically escape the two special characters used in
``LIKE`` statements -- the percent sign and the underscore. (In a ``LIKE``
statement, the percent sign signifies a multiple-character wildcard and the
underscore signifies a single-character wildcard.)

This means things should work intuitively, so the abstraction doesn't leak.
For example, to retrieve all the entries that contain a percent sign, just use
the percent sign as any other character::

    Entry.objects.filter(headline__contains='%')

Django takes care of the quoting for you; the resulting SQL will look something
like this::

    SELECT ... WHERE headline LIKE '%\%%';

Same goes for underscores. Both percentage signs and underscores are handled
for you transparently.

Caching and QuerySets
---------------------

Each ``QuerySet`` contains a cache, to minimize database access. It's important
to understand how it works, in order to write the most efficient code.

In a newly created ``QuerySet``, the cache is empty. The first time a
``QuerySet`` is evaluated -- and, hence, a database query happens -- Django
saves the query results in the ``QuerySet``'s cache and returns the results
that have been explicitly requested (e.g., the next element, if the
``QuerySet`` is being iterated over). Subsequent evaluations of the
``QuerySet`` reuse the cached results.

Keep this caching behavior in mind, because it may bite you if you don't use
your ``QuerySet``\s correctly. For example, the following will create two
``QuerySet``\s, evaluate them, and throw them away::

    print [e.headline for e in Entry.objects.all()]
    print [e.pub_date for e in Entry.objects.all()]

That means the same database query will be executed twice, effectively doubling
your database load. Also, there's a possibility the two lists may not include
the same database records, because an ``Entry`` may have been added or deleted
in the split second between the two requests.

To avoid this problem, simply save the ``QuerySet`` and reuse it::

    queryset = Poll.objects.all()
    print [p.headline for p in queryset] # Evaluate the query set.
    print [p.pub_date for p in queryset] # Re-use the cache from the evaluation.

Comparing objects
=================

To compare two model instances, just use the standard Python comparison operator,
the double equals sign: ``==``. Behind the scenes, that compares the primary
key values of two models.

Using the ``Entry`` example above, the following two statements are equivalent::

    some_entry == other_entry
    some_entry.id == other_entry.id

If a model's primary key isn't called ``id``, no problem. Comparisons will
always use the primary key, whatever it's called. For example, if a model's
primary key field is called ``name``, these two statements are equivalent::

    some_obj == other_obj
    some_obj.name == other_obj.name

Complex lookups with Q objects
==============================

Keyword argument queries -- in ``filter()``, etc. -- are "AND"ed together. If
you need to execute more complex queries (for example, queries with ``OR``
statements), you can use ``Q`` objects.

A ``Q`` object (``django.db.models.Q``) is an object used to encapsulate a
collection of keyword arguments. These keyword arguments are specified as in
"Field lookups" above.

For example, this ``Q`` object encapsulates a single ``LIKE`` query::

    Q(question__startswith='What')

``Q`` objects can be combined using the ``&`` and ``|`` operators. When an
operator is used on two ``Q`` objects, it yields a new ``Q`` object.

For example, this statement yields a single ``Q`` object that represents the
"OR" of two ``"question__startswith"`` queries::

    Q(question__startswith='Who') | Q(question__startswith='What')

This is equivalent to the following SQL ``WHERE`` clause::

    WHERE question LIKE 'Who%' OR question LIKE 'What%'

You can compose statements of arbitrary complexity by combining ``Q`` objects
with the ``&`` and ``|`` operators. You can also use parenthetical grouping.

Each lookup function that takes keyword-arguments (e.g. ``filter()``,
``exclude()``, ``get()``) can also be passed one or more ``Q`` objects as
positional (not-named) arguments. If you provide multiple ``Q`` object
arguments to a lookup function, the arguments will be "AND"ed together. For
example::

    Poll.objects.get(
        Q(question__startswith='Who'),
        Q(pub_date=date(2005, 5, 2)) | Q(pub_date=date(2005, 5, 6))
    )

... roughly translates into the SQL::

    SELECT * from polls WHERE question LIKE 'Who%'
        AND (pub_date = '2005-05-02' OR pub_date = '2005-05-06')

Lookup functions can mix the use of ``Q`` objects and keyword arguments. All
arguments provided to a lookup function (be they keyword arguments or ``Q``
objects) are "AND"ed together. However, if a ``Q`` object is provided, it must
precede the definition of any keyword arguments. For example::

    Poll.objects.get(
        Q(pub_date=date(2005, 5, 2)) | Q(pub_date=date(2005, 5, 6)),
        question__startswith='Who')

... would be a valid query, equivalent to the previous example; but::

    # INVALID QUERY
    Poll.objects.get(
        question__startswith='Who',
        Q(pub_date=date(2005, 5, 2)) | Q(pub_date=date(2005, 5, 6)))

... would not be valid.

See the `OR lookups examples page`_ for more examples.

.. _OR lookups examples page: http://www.djangoproject.com/documentation/models/or_lookups/

Related objects
===============

When you define a relationship in a model (i.e., a ``ForeignKey``,
``OneToOneField``, or ``ManyToManyField``), instances of that model will have
a convenient API to access the related object(s).

Using the models at the top of this page, for example, an ``Entry`` object ``e``
can get its associated ``Blog`` object by accessing the ``blog`` attribute:
``e.blog``.

(Behind the scenes, this functionality is implemented by Python descriptors_.
This shouldn't really matter to you, but we point it out here for the curious.)

Django also creates API accessors for the "other" side of the relationship --
the link from the related model to the model that defines the relationship.
For example, a ``Blog`` object ``b`` has access to a list of all related
``Entry`` objects via the ``entry_set`` attribute: ``b.entry_set.all()``.

All examples in this section use the sample ``Blog``, ``Author`` and ``Entry``
models defined at the top of this page.

.. _descriptors: http://users.rcn.com/python/download/Descriptor.htm

One-to-many relationships
-------------------------

Forward
~~~~~~~

If a model has a ``ForeignKey``, instances of that model will have access to
the related (foreign) object via a simple attribute of the model.

Example::

    e = Entry.objects.get(id=2)
    e.blog # Returns the related Blog object.

You can get and set via a foreign-key attribute. As you may expect, changes to
the foreign key aren't saved to the database until you call ``save()``.
Example::

    e = Entry.objects.get(id=2)
    e.blog = some_blog
    e.save()

If a ``ForeignKey`` field has ``null=True`` set (i.e., it allows ``NULL``
values), you can assign ``None`` to it. Example::

    e = Entry.objects.get(id=2)
    e.blog = None
    e.save() # "UPDATE blog_entry SET blog_id = NULL ...;"

Forward access to one-to-many relationships is cached the first time the
related object is accessed. Subsequent accesses to the foreign key on the same
object instance are cached. Example::

    e = Entry.objects.get(id=2)
    print e.blog  # Hits the database to retrieve the associated Blog.
    print e.blog  # Doesn't hit the database; uses cached version.

Note that the ``select_related()`` ``QuerySet`` method recursively prepopulates
the cache of all one-to-many relationships ahead of time. Example::

    e = Entry.objects.select_related().get(id=2)
    print e.blog  # Doesn't hit the database; uses cached version.
    print e.blog  # Doesn't hit the database; uses cached version.

``select_related()`` is documented in the "QuerySet methods that return new
QuerySets" section above.

Backward
~~~~~~~~

If a model has a ``ForeignKey``, instances of the foreign-key model will have
access to a ``Manager`` that returns all instances of the first model. By
default, this ``Manager`` is named ``FOO_set``, where ``FOO`` is the source
model name, lowercased. This ``Manager`` returns ``QuerySets``, which can be
filtered and manipulated as described in the "Retrieving objects" section
above.

Example::

    b = Blog.objects.get(id=1)
    b.entry_set.all() # Returns all Entry objects related to Blog.

    # b.entry_set is a Manager that returns QuerySets.
    b.entry_set.filter(headline__contains='Lennon')
    b.entry_set.count()

You can override the ``FOO_set`` name by setting the ``related_name``
parameter in the ``ForeignKey()`` definition. For example, if the ``Entry``
model was altered to ``blog = ForeignKey(Blog, related_name='entries')``, the
above example code would look like this::

    b = Blog.objects.get(id=1)
    b.entries.all() # Returns all Entry objects related to Blog.

    # b.entries is a Manager that returns QuerySets.
    b.entries.filter(headline__contains='Lennon')
    b.entries.count()

You cannot access a reverse ``ForeignKey`` ``Manager`` from the class; it must
be accessed from an instance. Example::

    Blog.entry_set # Raises AttributeError: "Manager must be accessed via instance".

In addition to the ``QuerySet`` methods defined in "Retrieving objects" above,
the ``ForeignKey`` ``Manager`` has these additional methods:

    * ``add(obj1, obj2, ...)``: Adds the specified model objects to the related
      object set.

      Example::

          b = Blog.objects.get(id=1)
          e = Entry.objects.get(id=234)
          b.entry_set.add(e) # Associates Entry e with Blog b.

    * ``create(**kwargs)``: Creates a new object, saves it and puts it in the
      related object set. Returns the newly created object.

      Example::

          b = Blog.objects.get(id=1)
          e = b.entry_set.create(headline='Hello', body_text='Hi', pub_date=datetime.date(2005, 1, 1))
          # No need to call e.save() at this point -- it's already been saved.

      This is equivalent to (but much simpler than)::

          b = Blog.objects.get(id=1)
          e = Entry(blog=b, headline='Hello', body_text='Hi', pub_date=datetime.date(2005, 1, 1))
          e.save()

      Note that there's no need to specify the keyword argument of the model
      that defines the relationship. In the above example, we don't pass the
      parameter ``blog`` to ``create()``. Django figures out that the new
      ``Entry`` object's ``blog`` field should be set to ``b``.

    * ``remove(obj1, obj2, ...)``: Removes the specified model objects from the
      related object set.

      Example::

          b = Blog.objects.get(id=1)
          e = Entry.objects.get(id=234)
          b.entry_set.remove(e) # Disassociates Entry e from Blog b.

      In order to prevent database inconsistency, this method only exists on
      ``ForeignKey`` objects where ``null=True``. If the related field can't be
      set to ``None`` (``NULL``), then an object can't be removed from a
      relation without being added to another. In the above example, removing
      ``e`` from ``b.entry_set()`` is equivalent to doing ``e.blog = None``,
      and because the ``blog`` ``ForeignKey`` doesn't have ``null=True``, this
      is invalid.

    * ``clear()``: Removes all objects from the related object set.

      Example::

          b = Blog.objects.get(id=1)
          b.entry_set.clear()

      Note this doesn't delete the related objects -- it just disassociates
      them.

      Just like ``remove()``, ``clear()`` is only available on ``ForeignKey``s
      where ``null=True``.

To assign the members of a related set in one fell swoop, just assign to it
from any iterable object. Example::

    b = Blog.objects.get(id=1)
    b.entry_set = [e1, e2]

If the ``clear()`` method is available, any pre-existing objects will be
removed from the ``entry_set`` before all objects in the iterable (in this
case, a list) are added to the set. If the ``clear()`` method is *not*
available, all objects in the iterable will be added without removing any
existing elements.

Each "reverse" operation described in this section has an immediate effect on
the database. Every addition, creation and deletion is immediately and
automatically saved to the database.

Many-to-many relationships
--------------------------

Both ends of a many-to-many relationship get automatic API access to the other
end. The API works just as a "backward" one-to-many relationship. See Backward_
above.

The only difference is in the attribute naming: The model that defines the
``ManyToManyField`` uses the attribute name of that field itself, whereas the
"reverse" model uses the lowercased model name of the original model, plus
``'_set'`` (just like reverse one-to-many relationships).

An example makes this easier to understand::

    e = Entry.objects.get(id=3)
    e.authors.all() # Returns all Author objects for this Entry.
    e.authors.count()
    e.authors.filter(name__contains='John')

    a = Author.objects.get(id=5)
    a.entry_set.all() # Returns all Entry objects for this Author.

Like ``ForeignKey``, ``ManyToManyField`` can specify ``related_name``. In the
above example, if the ``ManyToManyField`` in ``Entry`` had specified
``related_name='entries'``, then each ``Author`` instance would have an
``entries`` attribute instead of ``entry_set``.

One-to-one relationships
------------------------

The semantics of one-to-one relationships will be changing soon, so we don't
recommend you use them.

How are the backward relationships possible?
--------------------------------------------

Other object-relational mappers require you to define relationships on both
sides. The Django developers believe this is a violation of the DRY (Don't
Repeat Yourself) principle, so Django only requires you to define the
relationship on one end.

But how is this possible, given that a model class doesn't know which other
model classes are related to it until those other model classes are loaded?

The answer lies in the ``INSTALLED_APPS`` setting. The first time any model is
loaded, Django iterates over every model in ``INSTALLED_APPS`` and creates the
backward relationships in memory as needed. Essentially, one of the functions
of ``INSTALLED_APPS`` is to tell Django the entire model domain.

Queries over related objects
----------------------------

Queries involving related objects follow the same rules as queries involving
normal value fields. When specifying the the value for a query to match, you
may use either an object instance itself, or the primary key value for the
object.

For example, if you have a Blog object ``b`` with ``id=5``, the following
three queries would be identical::

    Entry.objects.filter(blog=b) # Query using object instance
    Entry.objects.filter(blog=b.id) # Query using id from instance
    Entry.objects.filter(blog=5) # Query using id directly

Deleting objects
================

The delete method, conveniently, is named ``delete()``. This method immediately
deletes the object and has no return value. Example::

    e.delete()

You can also delete objects in bulk. Every ``QuerySet`` has a ``delete()``
method, which deletes all members of that ``QuerySet``.

For example, this deletes all ``Entry`` objects with a ``pub_date`` year of
2005::

    Entry.objects.filter(pub_date__year=2005).delete()

Note that ``delete()`` is the only ``QuerySet`` method that is not exposed on a
``Manager`` itself. This is a safety mechanism to prevent you from accidentally
requesting ``Entry.objects.delete()``, and deleting *all* the entries. If you
*do* want to delete all the objects, then you have to explicitly request a
complete query set::

    Entry.objects.all().delete()

Extra instance methods
======================

In addition to ``save()``, ``delete()``, a model object might get any or all
of the following methods:

get_FOO_display()
-----------------

For every field that has ``choices`` set, the object will have a
``get_FOO_display()`` method, where ``FOO`` is the name of the field. This
method returns the "human-readable" value of the field. For example, in the
following model::

    GENDER_CHOICES = (
        ('M', 'Male'),
        ('F', 'Female'),
    )
    class Person(models.Model):
        name = models.CharField(maxlength=20)
        gender = models.CharField(maxlength=1, choices=GENDER_CHOICES)

...each ``Person`` instance will have a ``get_gender_display()`` method. Example::

    >>> p = Person(name='John', gender='M')
    >>> p.save()
    >>> p.gender
    'M'
    >>> p.get_gender_display()
    'Male'

get_next_by_FOO(\**kwargs) and get_previous_by_FOO(\**kwargs)
-------------------------------------------------------------

For every ``DateField`` and ``DateTimeField`` that does not have ``null=True``,
the object will have ``get_next_by_FOO()`` and ``get_previous_by_FOO()``
methods, where ``FOO`` is the name of the field. This returns the next and
previous object with respect to the date field, raising the appropriate
``DoesNotExist`` exception when appropriate.

Both methods accept optional keyword arguments, which should be in the format
described in `Field lookups`_ above.

Note that in the case of identical date values, these methods will use the ID
as a fallback check. This guarantees that no records are skipped or duplicated.
For a full example, see the `lookup API sample model`_.

.. _lookup API sample model: http://www.djangoproject.com/documentation/models/lookup/

get_FOO_filename()
------------------

For every ``FileField``, the object will have a ``get_FOO_filename()`` method,
where ``FOO`` is the name of the field. This returns the full filesystem path
to the file, according to your ``MEDIA_ROOT`` setting.

Note that ``ImageField`` is technically a subclass of ``FileField``, so every
model with an ``ImageField`` will also get this method.

get_FOO_url()
-------------

For every ``FileField``, the object will have a ``get_FOO_url()`` method,
where ``FOO`` is the name of the field. This returns the full URL to the file,
according to your ``MEDIA_URL`` setting. If the value is blank, this method
returns an empty string.

get_FOO_size()
--------------

For every ``FileField``, the object will have a ``get_FOO_size()`` method,
where ``FOO`` is the name of the field. This returns the size of the file, in
bytes. (Behind the scenes, it uses ``os.path.getsize``.)

save_FOO_file(filename, raw_contents)
-------------------------------------

For every ``FileField``, the object will have a ``save_FOO_file()`` method,
where ``FOO`` is the name of the field. This saves the given file to the
filesystem, using the given filename. If a file with the given filename already
exists, Django adds an underscore to the end of the filename (but before the
extension) until the filename is available.

get_FOO_height() and get_FOO_width()
------------------------------------

For every ``ImageField``, the object will have ``get_FOO_height()`` and
``get_FOO_width()`` methods, where ``FOO`` is the name of the field. This
returns the height (or width) of the image, as an integer, in pixels.

Falling back to raw SQL
=======================

If you find yourself needing to write an SQL query that is too complex for
Django's database-mapper to handle, you can fall back into raw-SQL statement
mode.

The preferred way to do this is by giving your model custom methods or custom
manager methods that execute queries. Although there's nothing in Django that
*requires* database queries to live in the model layer, this approach keeps all
your data-access logic in one place, which is smart from an code-organization
standpoint. For instructions, see `Executing custom SQL`_.

Finally, it's important to note that the Django database layer is merely an
interface to your database. You can access your database via other tools,
programming languages or database frameworks; there's nothing Django-specific
about your database.

.. _Executing custom SQL: http://www.djangoproject.com/documentation/model_api/#executing-custom-sql
