mirror of https://github.com/django/django.git
1120 lines
43 KiB
Plaintext
1120 lines
43 KiB
Plaintext
==============
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Making queries
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==============
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.. currentmodule:: django.db.models
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Once you've created your :doc:`data models </topics/db/models>`, Django
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automatically gives you a database-abstraction API that lets you create,
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retrieve, update and delete objects. This document explains how to use this
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API. Refer to the :doc:`data model reference </ref/models/index>` for full
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details of all the various model lookup options.
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Throughout this guide (and in the reference), we'll refer to the following
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models, which comprise a Weblog application:
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.. _queryset-model-example:
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.. code-block:: python
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class Blog(models.Model):
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name = models.CharField(max_length=100)
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tagline = models.TextField()
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def __unicode__(self):
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return self.name
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class Author(models.Model):
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name = models.CharField(max_length=50)
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email = models.EmailField()
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def __unicode__(self):
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return self.name
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class Entry(models.Model):
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blog = models.ForeignKey(Blog)
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headline = models.CharField(max_length=255)
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body_text = models.TextField()
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pub_date = models.DateTimeField()
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mod_date = models.DateTimeField()
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authors = models.ManyToManyField(Author)
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n_comments = models.IntegerField()
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n_pingbacks = models.IntegerField()
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rating = models.IntegerField()
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def __unicode__(self):
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return self.headline
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Creating objects
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================
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To represent database-table data in Python objects, Django uses an intuitive
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system: A model class represents a database table, and an instance of that
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class represents a particular record in the database table.
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To create an object, instantiate it using keyword arguments to the model class,
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then call ``save()`` to save it to the database.
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You import the model class from wherever it lives on the Python path, as you
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may expect. (We point this out here because previous Django versions required
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funky model importing.)
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Assuming models live in a file ``mysite/blog/models.py``, here's an example::
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>>> from blog.models import Blog
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>>> b = Blog(name='Beatles Blog', tagline='All the latest Beatles news.')
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>>> b.save()
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This performs an ``INSERT`` SQL statement behind the scenes. Django doesn't hit
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the database until you explicitly call ``save()``.
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The ``save()`` method has no return value.
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.. seealso::
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``save()`` takes a number of advanced options not described here.
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See the documentation for ``save()`` for complete details.
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To create an object and save it all in one step see the ```create()```
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method.
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Saving changes to objects
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=========================
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To save changes to an object that's already in the database, use ``save()``.
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Given a ``Blog`` instance ``b5`` that has already been saved to the database,
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this example changes its name and updates its record in the database::
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>> b5.name = 'New name'
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>> b5.save()
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This performs an ``UPDATE`` SQL statement behind the scenes. Django doesn't hit
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the database until you explicitly call ``save()``.
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Saving ``ForeignKey`` and ``ManyToManyField`` fields
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----------------------------------------------------
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Updating a ``ForeignKey`` field works exactly the same way as saving a normal
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field; simply assign an object of the right type to the field in question.
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This example updates the ``blog`` attribute of an ``Entry`` instance ``entry``::
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>>> from blog.models import Entry
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>>> entry = Entry.objects.get(pk=1)
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>>> cheese_blog = Blog.objects.get(name="Cheddar Talk")
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>>> entry.blog = cheese_blog
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>>> entry.save()
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Updating a ``ManyToManyField`` works a little differently; use the ``add()``
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method on the field to add a record to the relation. This example adds the
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``Author`` instance ``joe`` to the ``entry`` object::
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>>> from blog.models import Author
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>>> joe = Author.objects.create(name="Joe")
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>>> entry.authors.add(joe)
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Django will complain if you try to assign or add an object of the wrong type.
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Retrieving objects
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==================
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To retrieve objects from your database, you construct a ``QuerySet`` via a
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``Manager`` on your model class.
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A ``QuerySet`` represents a collection of objects from your database. It can
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have zero, one or many *filters* -- criteria that narrow down the collection
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based on given parameters. In SQL terms, a ``QuerySet`` equates to a ``SELECT``
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statement, and a filter is a limiting clause such as ``WHERE`` or ``LIMIT``.
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You get a ``QuerySet`` by using your model's ``Manager``. Each model has at
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least one ``Manager``, and it's called ``objects`` by default. Access it
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directly via the model class, like so::
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>>> Blog.objects
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<django.db.models.manager.Manager object at ...>
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>>> b = Blog(name='Foo', tagline='Bar')
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>>> b.objects
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Traceback:
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...
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AttributeError: "Manager isn't accessible via Blog instances."
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.. note::
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``Managers`` are accessible only via model classes, rather than from model
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instances, to enforce a separation between "table-level" operations and
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"record-level" operations.
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The ``Manager`` is the main source of ``QuerySets`` for a model. It acts as a
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"root" ``QuerySet`` that describes all objects in the model's database table.
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For example, ``Blog.objects`` is the initial ``QuerySet`` that contains all
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``Blog`` objects in the database.
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Retrieving all objects
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----------------------
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The simplest way to retrieve objects from a table is to get all of them.
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To do this, use the ``all()`` method on a ``Manager``::
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>>> all_entries = Entry.objects.all()
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The ``all()`` method returns a ``QuerySet`` of all the objects in the database.
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(If ``Entry.objects`` is a ``QuerySet``, why can't we just do ``Entry.objects``?
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That's because ``Entry.objects``, the root ``QuerySet``, is a special case
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that cannot be evaluated. The ``all()`` method returns a ``QuerySet`` that
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*can* be evaluated.)
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Retrieving specific objects with filters
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----------------------------------------
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The root ``QuerySet`` provided by the ``Manager`` describes all objects in the
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database table. Usually, though, you'll need to select only a subset of the
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complete set of objects.
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To create such a subset, you refine the initial ``QuerySet``, adding filter
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conditions. The two most common ways to refine a ``QuerySet`` are:
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``filter(**kwargs)``
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Returns a new ``QuerySet`` containing objects that match the given
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lookup parameters.
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``exclude(**kwargs)``
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Returns a new ``QuerySet`` containing objects that do *not* match the
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given lookup parameters.
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The lookup parameters (``**kwargs`` in the above function definitions) should
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be in the format described in `Field lookups`_ below.
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For example, to get a ``QuerySet`` of blog entries from the year 2006, use
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``filter()`` like so::
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Entry.objects.filter(pub_date__year=2006)
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We don't have to add an ``all()`` -- ``Entry.objects.all().filter(...)``. That
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would still work, but you only need ``all()`` when you want all objects from the
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root ``QuerySet``.
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.. _chaining-filters:
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Chaining filters
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~~~~~~~~~~~~~~~~
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The result of refining a ``QuerySet`` is itself a ``QuerySet``, so it's
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possible to chain refinements together. For example::
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>>> Entry.objects.filter(
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... headline__startswith='What'
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... ).exclude(
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... pub_date__gte=datetime.now()
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... ).filter(
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... pub_date__gte=datetime(2005, 1, 1)
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... )
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This takes the initial ``QuerySet`` of all entries in the database, adds a
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filter, then an exclusion, then another filter. The final result is a
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``QuerySet`` containing all entries with a headline that starts with "What",
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that were published between January 1, 2005, and the current day.
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.. _filtered-querysets-are-unique:
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Filtered QuerySets are unique
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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Each time you refine a ``QuerySet``, you get a brand-new ``QuerySet`` that is
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in no way bound to the previous ``QuerySet``. Each refinement creates a
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separate and distinct ``QuerySet`` that can be stored, used and reused.
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Example::
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>> q1 = Entry.objects.filter(headline__startswith="What")
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>> q2 = q1.exclude(pub_date__gte=datetime.now())
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>> q3 = q1.filter(pub_date__gte=datetime.now())
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These three ``QuerySets`` are separate. The first is a base ``QuerySet``
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containing all entries that contain a headline starting with "What". The second
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is a subset of the first, with an additional criteria that excludes records
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whose ``pub_date`` is greater than now. The third is a subset of the first,
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with an additional criteria that selects only the records whose ``pub_date`` is
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greater than now. The initial ``QuerySet`` (``q1``) is unaffected by the
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refinement process.
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.. _querysets-are-lazy:
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QuerySets are lazy
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~~~~~~~~~~~~~~~~~~
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``QuerySets`` are lazy -- the act of creating a ``QuerySet`` doesn't involve any
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database activity. You can stack filters together all day long, and Django won't
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actually run the query until the ``QuerySet`` is *evaluated*. Take a look at
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this example::
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>>> q = Entry.objects.filter(headline__startswith="What")
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>>> q = q.filter(pub_date__lte=datetime.now())
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>>> q = q.exclude(body_text__icontains="food")
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>>> print q
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Though this looks like three database hits, in fact it hits the database only
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once, at the last line (``print q``). In general, the results of a ``QuerySet``
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aren't fetched from the database until you "ask" for them. When you do, the
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``QuerySet`` is *evaluated* by accessing the database. For more details on
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exactly when evaluation takes place, see :ref:`when-querysets-are-evaluated`.
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.. _retrieving-single-object-with-get:
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Retrieving a single object with get
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-----------------------------------
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``.filter()`` will always give you a ``QuerySet``, even if only a single
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object matches the query - in this case, it will be a ``QuerySet`` containing
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a single element.
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If you know there is only one object that matches your query, you can use
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the ``get()`` method on a `Manager` which returns the object directly::
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>>> one_entry = Entry.objects.get(pk=1)
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You can use any query expression with ``get()``, just like with ``filter()`` -
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again, see `Field lookups`_ below.
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Note that there is a difference between using ``.get()``, and using
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``.filter()`` with a slice of ``[0]``. If there are no results that match the
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query, ``.get()`` will raise a ``DoesNotExist`` exception. This exception is an
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attribute of the model class that the query is being performed on - so in the
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code above, if there is no ``Entry`` object with a primary key of 1, Django will
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raise ``Entry.DoesNotExist``.
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Similarly, Django will complain if more than one item matches the ``get()``
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query. In this case, it will raise ``MultipleObjectsReturned``, which again is
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an attribute of the model class itself.
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Other QuerySet methods
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----------------------
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Most of the time you'll use ``all()``, ``get()``, ``filter()`` and ``exclude()``
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when you need to look up objects from the database. However, that's far from all
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there is; see the :ref:`QuerySet API Reference <queryset-api>` for a complete
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list of all the various ``QuerySet`` methods.
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.. _limiting-querysets:
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Limiting QuerySets
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------------------
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Use a subset of Python's array-slicing syntax to limit your ``QuerySet`` to a
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certain number of results. This is the equivalent of SQL's ``LIMIT`` and
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``OFFSET`` clauses.
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For example, this returns the first 5 objects (``LIMIT 5``)::
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>>> Entry.objects.all()[:5]
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This returns the sixth through tenth objects (``OFFSET 5 LIMIT 5``)::
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>>> Entry.objects.all()[5:10]
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Negative indexing (i.e. ``Entry.objects.all()[-1]``) is not supported.
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Generally, slicing a ``QuerySet`` returns a new ``QuerySet`` -- it doesn't
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evaluate the query. An exception is if you use the "step" parameter of Python
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slice syntax. For example, this would actually execute the query in order to
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return a list of every *second* object of the first 10::
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>>> Entry.objects.all()[:10:2]
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To retrieve a *single* object rather than a list
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(e.g. ``SELECT foo FROM bar LIMIT 1``), use a simple index instead of a
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slice. For example, this returns the first ``Entry`` in the database, after
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ordering entries alphabetically by headline::
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>>> Entry.objects.order_by('headline')[0]
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This is roughly equivalent to::
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>>> Entry.objects.order_by('headline')[0:1].get()
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Note, however, that the first of these will raise ``IndexError`` while the
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second will raise ``DoesNotExist`` if no objects match the given criteria. See
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:meth:`~django.db.models.QuerySet.get` for more details.
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.. _field-lookups-intro:
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Field lookups
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-------------
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Field lookups are how you specify the meat of an SQL ``WHERE`` clause. They're
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specified as keyword arguments to the ``QuerySet`` methods ``filter()``,
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``exclude()`` and ``get()``.
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Basic lookups keyword arguments take the form ``field__lookuptype=value``.
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(That's a double-underscore). For example::
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>>> Entry.objects.filter(pub_date__lte='2006-01-01')
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translates (roughly) into the following SQL::
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SELECT * FROM blog_entry WHERE pub_date <= '2006-01-01';
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.. admonition:: How this is possible
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Python has the ability to define functions that accept arbitrary name-value
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arguments whose names and values are evaluated at runtime. For more
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information, see `Keyword Arguments`_ in the official Python tutorial.
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.. _`Keyword Arguments`: http://docs.python.org/tutorial/controlflow.html#keyword-arguments
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If you pass an invalid keyword argument, a lookup function will raise
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``TypeError``.
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The database API supports about two dozen lookup types; a complete reference
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can be found in the :ref:`field lookup reference <field-lookups>`. To give you a taste of what's available, here's some of the more common lookups
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you'll probably use:
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:lookup:`exact`
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An "exact" match. For example::
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>>> Entry.objects.get(headline__exact="Man bites dog")
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Would generate SQL along these lines:
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.. code-block:: sql
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SELECT ... WHERE headline = 'Man bites dog';
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If you don't provide a lookup type -- that is, if your keyword argument
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doesn't contain a double underscore -- the lookup type is assumed to be
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``exact``.
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For example, the following two statements are equivalent::
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>>> Blog.objects.get(id__exact=14) # Explicit form
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>>> Blog.objects.get(id=14) # __exact is implied
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This is for convenience, because ``exact`` lookups are the common case.
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:lookup:`iexact`
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A case-insensitive match. So, the query::
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>>> Blog.objects.get(name__iexact="beatles blog")
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Would match a ``Blog`` titled "Beatles Blog", "beatles blog", or even
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"BeAtlES blOG".
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:lookup:`contains`
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Case-sensitive containment test. For example::
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Entry.objects.get(headline__contains='Lennon')
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Roughly translates to this SQL:
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.. code-block:: sql
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SELECT ... WHERE headline LIKE '%Lennon%';
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Note this will match the headline ``'Today Lennon honored'`` but not
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``'today lennon honored'``.
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There's also a case-insensitive version, :lookup:`icontains`.
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:lookup:`startswith`, :lookup:`endswith`
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Starts-with and ends-with search, respectively. There are also
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case-insensitive versions called :lookup:`istartswith` and
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:lookup:`iendswith`.
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Again, this only scratches the surface. A complete reference can be found in the
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:ref:`field lookup reference <field-lookups>`.
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Lookups that span relationships
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-------------------------------
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Django offers a powerful and intuitive way to "follow" relationships in
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lookups, taking care of the SQL ``JOIN``\s for you automatically, behind the
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scenes. To span a relationship, just use the field name of related fields
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across models, separated by double underscores, until you get to the field you
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want.
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This example retrieves all ``Entry`` objects with a ``Blog`` whose ``name``
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is ``'Beatles Blog'``::
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>>> Entry.objects.filter(blog__name__exact='Beatles Blog')
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This spanning can be as deep as you'd like.
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It works backwards, too. To refer to a "reverse" relationship, just use the
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lowercase name of the model.
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This example retrieves all ``Blog`` objects which have at least one ``Entry``
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whose ``headline`` contains ``'Lennon'``::
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>>> Blog.objects.filter(entry__headline__contains='Lennon')
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If you are filtering across multiple relationships and one of the intermediate
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models doesn't have a value that meets the filter condition, Django will treat
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it as if there is an empty (all values are ``NULL``), but valid, object there.
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All this means is that no error will be raised. For example, in this filter::
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Blog.objects.filter(entry__authors__name='Lennon')
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(if there was a related ``Author`` model), if there was no ``author``
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associated with an entry, it would be treated as if there was also no ``name``
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attached, rather than raising an error because of the missing ``author``.
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Usually this is exactly what you want to have happen. The only case where it
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might be confusing is if you are using ``isnull``. Thus::
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Blog.objects.filter(entry__authors__name__isnull=True)
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will return ``Blog`` objects that have an empty ``name`` on the ``author`` and
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also those which have an empty ``author`` on the ``entry``. If you don't want
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those latter objects, you could write::
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Blog.objects.filter(entry__authors__isnull=False,
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entry__authors__name__isnull=True)
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Spanning multi-valued relationships
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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When you are filtering an object based on a ``ManyToManyField`` or a reverse
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``ForeignKey``, there are two different sorts of filter you may be
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interested in. Consider the ``Blog``/``Entry`` relationship (``Blog`` to
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``Entry`` is a one-to-many relation). We might be interested in finding blogs
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that have an entry which has both *"Lennon"* in the headline and was published
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in 2008. Or we might want to find blogs that have an entry with *"Lennon"* in
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the headline as well as an entry that was published in 2008. Since there are
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multiple entries associated with a single ``Blog``, both of these queries are
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possible and make sense in some situations.
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The same type of situation arises with a ``ManyToManyField``. For example, if
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an ``Entry`` has a ``ManyToManyField`` called ``tags``, we might want to find
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entries linked to tags called *"music"* and *"bands"* or we might want an
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entry that contains a tag with a name of *"music"* and a status of *"public"*.
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To handle both of these situations, Django has a consistent way of processing
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``filter()`` and ``exclude()`` calls. Everything inside a single ``filter()``
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call is applied simultaneously to filter out items matching all those
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requirements. Successive ``filter()`` calls further restrict the set of
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objects, but for multi-valued relations, they apply to any object linked to
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the primary model, not necessarily those objects that were selected by an
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earlier ``filter()`` call.
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That may sound a bit confusing, so hopefully an example will clarify. To
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select all blogs that contain entries with both *"Lennon"* in the headline
|
|
and that were published in 2008 (the same entry satisfying both conditions),
|
|
we would write::
|
|
|
|
Blog.objects.filter(entry__headline__contains='Lennon',
|
|
entry__pub_date__year=2008)
|
|
|
|
To select all blogs that contain an entry with *"Lennon"* in the headline
|
|
**as well as** an entry that was published in 2008, we would write::
|
|
|
|
Blog.objects.filter(entry__headline__contains='Lennon').filter(
|
|
entry__pub_date__year=2008)
|
|
|
|
In this second example, the first filter restricted the queryset to all those
|
|
blogs linked to that particular type of entry. The second filter restricted
|
|
the set of blogs *further* to those that are also linked to the second type of
|
|
entry. The entries select by the second filter may or may not be the same as
|
|
the entries in the first filter. We are filtering the ``Blog`` items with each
|
|
filter statement, not the ``Entry`` items.
|
|
|
|
All of this behavior also applies to ``exclude()``: all the conditions in a
|
|
single ``exclude()`` statement apply to a single instance (if those conditions
|
|
are talking about the same multi-valued relation). Conditions in subsequent
|
|
``filter()`` or ``exclude()`` calls that refer to the same relation may end up
|
|
filtering on different linked objects.
|
|
|
|
.. _query-expressions:
|
|
|
|
Filters can reference fields on the model
|
|
-----------------------------------------
|
|
|
|
In the examples given so far, we have constructed filters that compare
|
|
the value of a model field with a constant. But what if you want to compare
|
|
the value of a model field with another field on the same model?
|
|
|
|
Django provides the ``F()`` object to allow such comparisons. Instances
|
|
of ``F()`` act as a reference to a model field within a query. These
|
|
references can then be used in query filters to compare the values of two
|
|
different fields on the same model instance.
|
|
|
|
For example, to find a list of all blog entries that have had more comments
|
|
than pingbacks, we construct an ``F()`` object to reference the comment count,
|
|
and use that ``F()`` object in the query::
|
|
|
|
>>> from django.db.models import F
|
|
>>> Entry.objects.filter(n_comments__gt=F('n_pingbacks'))
|
|
|
|
Django supports the use of addition, subtraction, multiplication,
|
|
division and modulo arithmetic with ``F()`` objects, both with constants
|
|
and with other ``F()`` objects. To find all the blog entries with more than
|
|
*twice* as many comments as pingbacks, we modify the query::
|
|
|
|
>>> Entry.objects.filter(n_comments__gt=F('n_pingbacks') * 2)
|
|
|
|
To find all the entries where the rating of the entry is less than the
|
|
sum of the pingback count and comment count, we would issue the
|
|
query::
|
|
|
|
>>> Entry.objects.filter(rating__lt=F('n_comments') + F('n_pingbacks'))
|
|
|
|
You can also use the double underscore notation to span relationships in
|
|
an ``F()`` object. An ``F()`` object with a double underscore will introduce
|
|
any joins needed to access the related object. For example, to retrieve all
|
|
the entries where the author's name is the same as the blog name, we could
|
|
issue the query::
|
|
|
|
>>> Entry.objects.filter(authors__name=F('blog__name'))
|
|
|
|
.. versionadded:: 1.3
|
|
|
|
For date and date/time fields, you can add or subtract a ``datetime.timedelta``
|
|
object. The following would return all entries that were modified more than 3 days
|
|
after they were published::
|
|
|
|
>>> from datetime import timedelta
|
|
>>> Entry.objects.filter(mod_date__gt=F('pub_date') + timedelta(days=3))
|
|
|
|
The pk lookup shortcut
|
|
----------------------
|
|
|
|
For convenience, Django provides a ``pk`` lookup shortcut, 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
|
|
|
|
Escaping percent signs 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:
|
|
|
|
.. code-block:: sql
|
|
|
|
SELECT ... WHERE headline LIKE '%\%%';
|
|
|
|
Same goes for underscores. Both percentage signs and underscores are handled
|
|
for you transparently.
|
|
|
|
.. _caching-and-querysets:
|
|
|
|
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 = Entry.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.
|
|
|
|
.. _complex-lookups-with-q:
|
|
|
|
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 and use parenthetical grouping. Also, ``Q``
|
|
objects can be negated using the ``~`` operator, allowing for combined lookups
|
|
that combine both a normal query and a negated (``NOT``) query::
|
|
|
|
Q(question__startswith='Who') | ~Q(pub_date__year=2005)
|
|
|
|
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.
|
|
|
|
.. seealso::
|
|
|
|
The `OR lookups examples`_ in the Django unit tests show some possible uses
|
|
of ``Q``.
|
|
|
|
.. _OR lookups examples: http://code.djangoproject.com/browser/django/trunk/tests/modeltests/or_lookups/tests.py
|
|
|
|
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
|
|
|
|
.. _topics-db-queries-delete:
|
|
|
|
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()
|
|
|
|
Keep in mind that this will, whenever possible, be executed purely in
|
|
SQL, and so the ``delete()`` methods of individual object instances
|
|
will not necessarily be called during the process. If you've provided
|
|
a custom ``delete()`` method on a model class and want to ensure that
|
|
it is called, you will need to "manually" delete instances of that
|
|
model (e.g., by iterating over a ``QuerySet`` and calling ``delete()``
|
|
on each object individually) rather than using the bulk ``delete()``
|
|
method of a ``QuerySet``.
|
|
|
|
When Django deletes an object, by default it emulates the behavior of the SQL
|
|
constraint ``ON DELETE CASCADE`` -- in other words, any objects which had
|
|
foreign keys pointing at the object to be deleted will be deleted along with
|
|
it. For example::
|
|
|
|
b = Blog.objects.get(pk=1)
|
|
# This will delete the Blog and all of its Entry objects.
|
|
b.delete()
|
|
|
|
.. versionadded:: 1.3
|
|
This cascade behavior is customizable via the
|
|
:attr:`~django.db.models.ForeignKey.on_delete` argument to the
|
|
:class:`~django.db.models.ForeignKey`.
|
|
|
|
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()
|
|
|
|
.. _topics-db-queries-update:
|
|
|
|
Updating multiple objects at once
|
|
=================================
|
|
|
|
Sometimes you want to set a field to a particular value for all the objects in
|
|
a ``QuerySet``. You can do this with the ``update()`` method. For example::
|
|
|
|
# Update all the headlines with pub_date in 2007.
|
|
Entry.objects.filter(pub_date__year=2007).update(headline='Everything is the same')
|
|
|
|
You can only set non-relation fields and ``ForeignKey`` fields using this
|
|
method. To update a non-relation field, provide the new value as a constant.
|
|
To update ``ForeignKey`` fields, set the new value to be the new model
|
|
instance you want to point to. For example::
|
|
|
|
>>> b = Blog.objects.get(pk=1)
|
|
|
|
# Change every Entry so that it belongs to this Blog.
|
|
>>> Entry.objects.all().update(blog=b)
|
|
|
|
The ``update()`` method is applied instantly and returns the number of rows
|
|
affected by the query. The only restriction on the ``QuerySet`` that is
|
|
updated is that it can only access one database table, the model's main
|
|
table. You can filter based on related fields, but you can only update columns
|
|
in the model's main table. Example::
|
|
|
|
>>> b = Blog.objects.get(pk=1)
|
|
|
|
# Update all the headlines belonging to this Blog.
|
|
>>> Entry.objects.select_related().filter(blog=b).update(headline='Everything is the same')
|
|
|
|
Be aware that the ``update()`` method is converted directly to an SQL
|
|
statement. It is a bulk operation for direct updates. It doesn't run any
|
|
``save()`` methods on your models, or emit the ``pre_save`` or ``post_save``
|
|
signals (which are a consequence of calling ``save()``). If you want to save
|
|
every item in a ``QuerySet`` and make sure that the ``save()`` method is
|
|
called on each instance, you don't need any special function to handle that.
|
|
Just loop over them and call ``save()``::
|
|
|
|
for item in my_queryset:
|
|
item.save()
|
|
|
|
Calls to update can also use :ref:`F() objects <query-expressions>` to update
|
|
one field based on the value of another field in the model. This is especially
|
|
useful for incrementing counters based upon their current value. For example, to
|
|
increment the pingback count for every entry in the blog::
|
|
|
|
>>> Entry.objects.all().update(n_pingbacks=F('n_pingbacks') + 1)
|
|
|
|
However, unlike ``F()`` objects in filter and exclude clauses, you can't
|
|
introduce joins when you use ``F()`` objects in an update -- you can only
|
|
reference fields local to the model being updated. If you attempt to introduce
|
|
a join with an ``F()`` object, a ``FieldError`` will be raised::
|
|
|
|
# THIS WILL RAISE A FieldError
|
|
>>> Entry.objects.update(headline=F('blog__name'))
|
|
|
|
.. _topics-db-queries-related:
|
|
|
|
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.
|
|
|
|
.. _backwards-related-objects:
|
|
|
|
Following relationships "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::
|
|
|
|
>>> Blog.entry_set
|
|
Traceback:
|
|
...
|
|
AttributeError: "Manager must be accessed via instance".
|
|
|
|
In addition to the ``QuerySet`` methods defined in "Retrieving objects" above,
|
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the ``ForeignKey`` ``Manager`` has additional methods used to handle the set of
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related objects. A synopsis of each is below, and complete details can be found
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in the :doc:`related objects reference </ref/models/relations>`.
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``add(obj1, obj2, ...)``
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Adds the specified model objects to the related object set.
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``create(**kwargs)``
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Creates a new object, saves it and puts it in the related object set.
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Returns the newly created object.
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``remove(obj1, obj2, ...)``
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Removes the specified model objects from the related object set.
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``clear()``
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Removes all objects from the related object set.
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To assign the members of a related set in one fell swoop, just assign to it
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from any iterable object. The iterable can contain object instances, or just
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a list of primary key values. For example::
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b = Blog.objects.get(id=1)
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b.entry_set = [e1, e2]
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In this example, ``e1`` and ``e2`` can be full Entry instances, or integer
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primary key values.
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If the ``clear()`` method is available, any pre-existing objects will be
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removed from the ``entry_set`` before all objects in the iterable (in this
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|
case, a list) are added to the set. If the ``clear()`` method is *not*
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available, all objects in the iterable will be added without removing any
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|
existing elements.
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|
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Each "reverse" operation described in this section has an immediate effect on
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|
the database. Every addition, creation and deletion is immediately and
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|
automatically saved to the database.
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|
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|
Many-to-many relationships
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|
--------------------------
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|
|
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Both ends of a many-to-many relationship get automatic API access to the other
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|
end. The API works just as a "backward" one-to-many relationship, above.
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|
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|
The only difference is in the attribute naming: The model that defines the
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``ManyToManyField`` uses the attribute name of that field itself, whereas the
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|
"reverse" model uses the lowercased model name of the original model, plus
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|
``'_set'`` (just like reverse one-to-many relationships).
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|
|
|
An example makes this easier to understand::
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|
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|
e = Entry.objects.get(id=3)
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e.authors.all() # Returns all Author objects for this Entry.
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|
e.authors.count()
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|
e.authors.filter(name__contains='John')
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|
a = Author.objects.get(id=5)
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a.entry_set.all() # Returns all Entry objects for this Author.
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|
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|
Like ``ForeignKey``, ``ManyToManyField`` can specify ``related_name``. In the
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|
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
|
|
------------------------
|
|
|
|
One-to-one relationships are very similar to many-to-one relationships. If you
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|
define a :class:`~django.db.models.OneToOneField` on your model, instances of
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|
that model will have access to the related object via a simple attribute of the
|
|
model.
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|
|
|
For example::
|
|
|
|
class EntryDetail(models.Model):
|
|
entry = models.OneToOneField(Entry)
|
|
details = models.TextField()
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|
|
|
ed = EntryDetail.objects.get(id=2)
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|
ed.entry # Returns the related Entry object.
|
|
|
|
The difference comes in "reverse" queries. The related model in a one-to-one
|
|
relationship also has access to a :class:`~django.db.models.Manager` object, but
|
|
that :class:`~django.db.models.Manager` represents a single object, rather than
|
|
a collection of objects::
|
|
|
|
e = Entry.objects.get(id=2)
|
|
e.entrydetail # returns the related EntryDetail object
|
|
|
|
If no object has been assigned to this relationship, Django will raise
|
|
a ``DoesNotExist`` exception.
|
|
|
|
Instances can be assigned to the reverse relationship in the same way as
|
|
you would assign the forward relationship::
|
|
|
|
e.entrydetail = ed
|
|
|
|
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 :setting:`INSTALLED_APPS` setting. The first time any model is
|
|
loaded, Django iterates over every model in :setting:`INSTALLED_APPS` and creates the
|
|
backward relationships in memory as needed. Essentially, one of the functions
|
|
of :setting:`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 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
|
|
|
|
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 on writing SQL by hand.
|
|
Django has a couple of options for writing raw SQL queries; see
|
|
:doc:`/topics/db/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.
|