django/docs/ref/models/querysets.txt

.. _ref-models-querysets:

======================
QuerySet API reference
======================

.. currentmodule:: django.db.models

This document describes the details of the ``QuerySet`` API. It builds on the
material presented in the :ref:`model <topics-db-models>` and `database query
<topics-db-queries>` guides, so you'll probably want to read and understand
those documents before reading this one.

Throughout this reference we'll use the :ref:`example weblog models
<queryset-model-example>` presented in the :ref:`database query guide
<topics-db-queries>`.

.. _when-querysets-are-evaluated:

When QuerySets are evaluated
============================

Internally, a ``QuerySet`` can be constructed, filter, sliced, and generally
passed around without actually hitting the database. No database activity
actually occurs until you do something to evaluate the queryset.

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 :ref:`limiting-querysets`, 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.

.. _queryset-api:

QuerySet API
============

Though you usually won't create one manually -- you'll go through a :class:`Manager` -- here's the formal declaration of a ``QuerySet``:

.. class:: QuerySet([model=None])

Usually when you'll interact with a ``QuerySet`` you'll use it by :ref:`chaining
filters <chaining-filters>`. To make this work, most ``QuerySet`` methods return new querysets.

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 later than 2005-1-3
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 later than 2005-1-3
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('?')

Note: ``order_by('?')`` queries may be expensive and slow, depending on the
database backend you're using.

To order by a field in a different model, use the same syntax as when you are
querying across model relations. That is, the name of the field, followed by a
double underscore (``__``), followed by the name of the field in the new model,
and so on for as many models as you want to join. For example::

    Entry.objects.order_by('blog__name', 'headline')

If you try to order by a field that is a relation to another model, Django will
use the default ordering on the related model (or order by the related model's
primary key if there is no ``Meta.ordering`` specified. For example::

    Entry.objects.order_by('blog')

...is identical to::

    Entry.objects.order_by('blog__id')

...since the ``Blog`` model has no default ordering specified.

Be cautious when ordering by fields in related models if you are also using
``distinct()``. See the note in the `distinct()`_ section for an explanation
of how related model ordering can change the expected results.

It is permissible to specify a multi-valued field to order the results by (for
example, a ``ManyToMany`` field). Normally this won't be a sensible thing to
do and it's really an advanced usage feature. However, if you know that your
queryset's filtering or available data implies that there will only be one
ordering piece of data for each of the main items you are selecting, the
ordering may well be exactly what you want to do. Use ordering on multi-valued
fields with care and make sure the results are what you expect.

**New in Django development version:** If you don't want any ordering to be
applied to a query, not even the default ordering, call ``order_by()`` with no
parameters.

**New in Django development version:** The syntax for ordering across related
models has changed. See the `Django 0.96 documentation`_ for the old behaviour.

.. _Django 0.96 documentation: http://www.djangoproject.com/documentation/0.96/model-api/#floatfield

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.

Also, note that ``reverse()`` should generally only be called on a
``QuerySet`` which has a defined ordering (e.g., when querying against
a model which defines a default ordering, or when using
``order_by()``). If no such ordering is defined for a given
``QuerySet``, calling ``reverse()`` on it has no real effect (the
ordering was undefined prior to calling ``reverse()``, and will remain
undefined afterward).


``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()``.

.. note::
    Any fields used in an `order_by(*fields)`_ call are included in the SQL
    ``SELECT`` columns. This can sometimes lead to unexpected results when
    used in conjunction with ``distinct()``. If you order by fields from a
    related model, those fields will be added to the selected columns and they
    may make otherwise duplicate rows appear to be distinct. Since the extra
    columns don't appear in the returned results (they are only there to
    support ordering), it sometimes looks like non-distinct results are being
    returned.

    Similarly, if you use a ``values()`` query to restrict the columns
    selected, the columns used in any ``order_by()`` (or default model
    ordering) will still be involved and may affect uniqueness of the results.

    The moral here is that if you are using ``distinct()`` be careful about
    ordering by related models. Similarly, when using ``distinct()`` and
    ``values()`` together, be careful when ordering by fields not in the
    ``values()`` call.


``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')
    [<Blog: 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 couple of subtleties that are worth mentioning:

    * The ``values()`` method does not return anything for
      :class:`~django.db.models.ManyToManyField` attributes and will raise an
      error if you try to pass in this type of field to it.
    * If you have a field called ``foo`` that is a
      :class:`~django.db.models.ForeignKey`, the default ``values()`` call
      will return a dictionary key called ``foo_id``, since this is the name
      of the hidden model attribute that stores the actual value (the ``foo``
      attribute refers to the related model). When you are calling
      ``values()`` and passing in field names, you can pass in either ``foo``
      or ``foo_id`` and you will get back the same thing (the dictionary key
      will match the field name you passed in).

      For example::

        >>> Entry.objects.values()
        [{'blog_id: 1, 'headline': u'First Entry', ...}, ...]

        >>> Entry.objects.values('blog')
        [{'blog': 1}, ...]

        >>> Entry.objects.values('blog_id')
        [{'blog_id': 1}, ...]
    * When using ``values()`` together with ``distinct()``, be aware that
      ordering can affect the results. See the note in the `distinct()`_
      section, above, for details.

**New in Django development version:** Previously, it was not possible to pass
``blog_id`` to ``values()`` in the above example, only ``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.

``values_list(*fields)``
~~~~~~~~~~~~~~~~~~~~~~~~

**New in Django development version**

This is similar to ``values()`` except that instead of returning a list of
dictionaries, it returns a list of tuples. Each tuple contains the value from
the respective field passed into the ``values_list()`` call -- so the first
item is the first field, etc. For example::

    >>> Entry.objects.values_list('id', 'headline')
    [(1, u'First entry'), ...]

If you only pass in a single field, you can also pass in the ``flat``
parameter. If ``True``, this will mean the returned results are single values,
rather than one-tuples. An example should make the difference clearer::

    >>> Entry.objects.values_list('id').order_by('id')
    [(1,), (2,), (3,), ...]

    >>> Entry.objects.values_list('id', flat=True).order_by('id')
    [1, 2, 3, ...]

It is an error to pass in ``flat`` when there is more than one field.

If you don't pass any values to ``values_list()``, it will return all the
fields in the model, in the order they were declared.

``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)]

``none()``
~~~~~~~~~~

.. versionadded:: 1.0

Returns an ``EmptyQuerySet`` -- a ``QuerySet`` that always evaluates to
an empty list. This can be used in cases where you know that you should
return an empty result set and your caller is expecting a ``QuerySet``
object (instead of returning an empty list, for example.)

Examples::

    >>> Entry.objects.none()
    []

.. _select-related:

``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.

    b = 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``.

Usually, using ``select_related()`` can vastly improve performance because your
app can avoid many database calls. However, in situations with deeply nested
sets of relationships ``select_related()`` can sometimes end up following "too
many" relations, and can generate queries so large that they end up being slow.

In these situations, you can use the ``depth`` argument to ``select_related()``
to control how many "levels" of relations ``select_related()`` will actually
follow::

    b = Book.objects.select_related(depth=1).get(id=4)
    p = b.author         # Doesn't hit the database.
    c = p.hometown       # Requires a database call.

.. versionadded:: 1.0
   The ``depth`` argument is new in the Django development version.

``extra(select=None, where=None, params=None, tables=None, order_by=None, select_params=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.

    .. versionadded:: 1.0

    In some rare cases, you might wish to pass parameters to the SQL fragments
    in ``extra(select=...)```. For this purpose, use the ``select_params``
    parameter. Since ``select_params`` is a sequence and the ``select``
    attribute is a dictionary, some care is required so that the parameters
    are matched up correctly with the extra select pieces.  In this situation,
    you should use a ``django.utils.datastructures.SortedDict`` for the
    ``select`` value, not just a normal Python dictionary.

    This will work, for example::

        Blog.objects.extra(
            select=SortedDict([('a', '%s'), ('b', '%s')]),
            select_params=('one', 'two'))

    The only thing to be careful about when using select parameters in
    ``extra()`` is to avoid using the substring ``"%%s"`` (that's *two*
    percent characters before the ``s``) in the select strings. Django's
    tracking of parameters looks for ``%s`` and an escaped ``%`` character
    like this isn't detected. That will lead to incorrect results.

``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);

    Be careful when using the ``tables`` parameter if you're specifying
    tables that are already used in the query. When you add extra tables
    via the ``tables`` parameter, Django assumes you want that table included
    an extra time, if it is already included. That creates a problem,
    since the table name will then be given an alias. If a table appears
    multiple times in an SQL statement, the second and subsequent occurrences
    must use aliases so the database can tell them apart. If you're
    referring to the extra table you added in the extra ``where`` parameter
    this is going to cause errors.

    Normally you'll only be adding extra tables that don't already appear in
    the query. However, if the case outlined above does occur, there are a few
    solutions. First, see if you can get by without including the extra table
    and use the one already in the query. If that isn't possible, put your
    ``extra()`` call at the front of the queryset construction so that your
    table is the first use of that table. Finally, if all else fails, look at
    the query produced and rewrite your ``where`` addition to use the alias
    given to your extra table. The alias will be the same each time you
    construct the queryset in the same way, so you can rely upon the alias
    name to not change.

``order_by``
    If you need to order the resulting queryset using some of the new fields
    or tables you have included via ``extra()`` use the ``order_by`` parameter
    to ``extra()`` and pass in a sequence of strings. These strings should
    either be model fields (as in the normal ``order_by()`` method on
    querysets), of the form ``table_name.column_name`` or an alias for a column
    that you specified in the ``select`` parameter to ``extra()``.

    For example::

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

    This would sort all the items for which ``is_recent`` is true to the front
    of the result set (``True`` sorts before ``False`` in a descending
    ordering).

    This shows, by the way, that you can make multiple calls to
    ``extra()`` and it will behave as you expect (adding new constraints each
    time).

``params``
    The ``where`` parameter 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 ``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 :ref:`caching-and-querysets`). Rather,
they query the database each time they're called.

.. _get-kwargs:

``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(force_insert=True)

are equivalent.

The :ref:`force_insert <ref-models-force-insert>` parameter is documented
elsewhere, but all it means is that a new object will always be created.
Normally you won't need to worry about this. However, if your model contains a
manual primary key value that you set and if that value already exists in the
database, a call to ``create()`` will fail with an ``IntegrityError`` since
primary keys must be unique. So remember to be prepared to handle the
exception if you are using manual primary keys.

``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 roughly 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. As hinted at
above, this is a simplification of the algorithm that is used, but it contains
all the pertinent details. The internal implementation has some more
error-checking than this and handles some extra edge-conditions; if you're
interested, read the code.

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'})


The ``get_or_create()`` method has similar error behaviour to ``create()``
when you are using manually specified primary keys. If an object needs to be
created and the key already exists in the database, an ``IntegrityError`` will
be raised.

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

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

``iterator()``
~~~~~~~~~~~~~~

Evaluates the ``QuerySet`` (by performing the query) and returns an
`iterator`_ over the results. A ``QuerySet`` typically reads all of
its results and instantiates all of the corresponding objects the
first time you access it; ``iterator()`` will instead read results and
instantiate objects in discrete chunks, yielding them one at a
time. For a ``QuerySet`` which returns a large number of objects, this
often results in better performance and a significant reduction in
memory use.

Note that using ``iterator()`` on a ``QuerySet`` which has already
been evaluated will force it to evaluate again, repeating the query.

.. _iterator: http://www.python.org/dev/peps/pep-0234/

``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
-------------

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()``.

For an introduction, see :ref:`field-lookups-intro`.

exact
~~~~~

Exact match. If the value provided for comparison is ``None``, it will
be interpreted as an SQL ``NULL`` (See isnull_ for more details).

Examples::

    Entry.objects.get(id__exact=14)
    Entry.objects.get(id__exact=None)

SQL equivalents::

    SELECT ... WHERE id = 14;
    SELECT ... WHERE id IS NULL;

.. versionchanged:: 1.0
   The semantics of ``id__exact=None`` have
   changed in the development version. Previously, it was (intentionally)
   converted to ``WHERE id = NULL`` at the SQL level, which would never match
   anything. It has now been changed to behave the same as ``id__isnull=True``.

.. admonition:: MySQL comparisons

    In MySQL, whether or not ``exact`` comparisons are case-insensitive by
    default. This is controlled by the collation setting on the database
    tables (this is a database setting, *not* a Django setting).  It is
    possible to configured you MySQL tables to use case-sensitive comparisons,
    however there are some trade-offs involved. For more information about
    this, see the :ref:`collation section <mysql-collation>` in the
    :ref:`databases <ref-databases>` documentation.

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%';

in
~~

In a given list.

Example::

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

SQL equivalent::

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

You can also use a queryset to dynamically evaluate the list of values
instead of providing a list of literal values. The queryset must be
reduced to a list of individual values using the ``values()`` method,
and then converted into a query using the ``query`` attribute::

    Entry.objects.filter(blog__in=Blog.objects.filter(name__contains='Cheddar').values('pk').query)

This queryset will be evaluated as subselect statement::

    SELECT ... WHERE blog.id IN (SELECT id FROM ... WHERE NAME LIKE '%Cheddar%')

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
~~~~~~

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

Example::

    Entry.objects.filter(pub_date__isnull=True)

SQL equivalent::

    SELECT ... WHERE pub_date IS NULL;

.. admonition:: ``__isnull=True`` vs ``__exact=None``

    There is an important difference between ``__isnull=True`` and
    ``__exact=None``. ``__exact=None`` will *always* return an empty result
    set, because SQL requires that no value is equal to ``NULL``.
    ``__isnull`` determines if the field is currently holding the value
    of ``NULL`` without performing a comparison.

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.

regex
~~~~~

.. versionadded:: 1.0

Case-sensitive regular expression match.

The regular expression syntax is that of the database backend in use. In the
case of SQLite, which doesn't natively support regular-expression lookups, the
syntax is that of Python's ``re`` module.

Example::

    Entry.objects.get(title__regex=r'^(An?|The) +')

SQL equivalents::

    SELECT ... WHERE title REGEXP BINARY '^(An?|The) +'; -- MySQL

    SELECT ... WHERE REGEXP_LIKE(title, '^(an?|the) +', 'c'); -- Oracle

    SELECT ... WHERE title ~ '^(An?|The) +'; -- PostgreSQL

    SELECT ... WHERE title REGEXP '^(An?|The) +'; -- SQLite

Using raw strings (e.g., ``r'foo'`` instead of ``'foo'``) for passing in the
regular expression syntax is recommended.

iregex
~~~~~~

.. versionadded:: 1.0

Case-insensitive regular expression match.

Example::

    Entry.objects.get(title__iregex=r'^(an?|the) +')

SQL equivalents::

    SELECT ... WHERE title REGEXP '^(an?|the) +'; -- MySQL

    SELECT ... WHERE REGEXP_LIKE(title, '^(an?|the) +', 'i'); -- Oracle

    SELECT ... WHERE title ~* '^(an?|the) +'; -- PostgreSQL

    SELECT ... WHERE title REGEXP '(?i)^(an?|the) +'; -- SQLite