1
0
mirror of https://github.com/django/django.git synced 2024-12-23 17:46:27 +00:00
django/docs/howto/custom-lookups.txt
Jorge C. Leitão 8780849da0 Fixed #22812 -- Refactored lookup API documentation.
Thanks Anssi and Tim for reviews.
2014-07-08 20:05:49 -04:00

269 lines
12 KiB
Plaintext

==============
Custom Lookups
==============
.. versionadded:: 1.7
.. currentmodule:: django.db.models
Django offers a wide variety of :ref:`built-in lookups <field-lookups>` for
filtering (for example, ``exact`` and ``icontains``). This documentation
explains how to write custom lookups and how to alter the working of existing
lookups. For the API references of lookups, see the :doc:`/ref/models/lookups`.
A simple lookup example
~~~~~~~~~~~~~~~~~~~~~~~
Let's start with a simple custom lookup. We will write a custom lookup ``ne``
which works opposite to ``exact``. ``Author.objects.filter(name__ne='Jack')``
will translate to the SQL::
"author"."name" <> 'Jack'
This SQL is backend independent, so we don't need to worry about different
databases.
There are two steps to making this work. Firstly we need to implement the
lookup, then we need to tell Django about it. The implementation is quite
straightforward::
from django.db.models import Lookup
class NotEqual(Lookup):
lookup_name = 'ne'
def as_sql(self, qn, connection):
lhs, lhs_params = self.process_lhs(qn, connection)
rhs, rhs_params = self.process_rhs(qn, connection)
params = lhs_params + rhs_params
return '%s <> %s' % (lhs, rhs), params
To register the ``NotEqual`` lookup we will just need to call
``register_lookup`` on the field class we want the lookup to be available. In
this case, the lookup makes sense on all ``Field`` subclasses, so we register
it with ``Field`` directly::
from django.db.models.fields import Field
Field.register_lookup(NotEqual)
We can now use ``foo__ne`` for any field ``foo``. You will need to ensure that
this registration happens before you try to create any querysets using it. You
could place the implementation in a ``models.py`` file, or register the lookup
in the ``ready()`` method of an ``AppConfig``.
Taking a closer look at the implementation, the first required attribute is
``lookup_name``. This allows the ORM to understand how to interpret ``name__ne``
and use ``NotEqual`` to generate the SQL. By convention, these names are always
lowercase strings containing only letters, but the only hard requirement is
that it must not contain the string ``__``.
We then need to define the ``as_sql`` method. This takes a ``SQLCompiler``
object, called ``qn``, and the active database connection. ``SQLCompiler``
objects are not documented, but the only thing we need to know about them is
that they have a ``compile()`` method which returns a tuple containing a SQL
string, and the parameters to be interpolated into that string. In most cases,
you don't need to use it directly and can pass it on to ``process_lhs()`` and
``process_rhs()``.
A ``Lookup`` works against two values, ``lhs`` and ``rhs``, standing for
left-hand side and right-hand side. The left-hand side is usually a field
reference, but it can be anything implementing the :ref:`query expression API
<query-expression>`. The right-hand is the value given by the user. In the
example ``Author.objects.filter(name__ne='Jack')``, the left-hand side is a
reference to the ``name`` field of the ``Author`` model, and ``'Jack'`` is the
right-hand side.
We call ``process_lhs`` and ``process_rhs`` to convert them into the values we
need for SQL using the ``qn`` object described before. These methods return
tuples containing some SQL and the parameters to be interpolated into that SQL,
just as we need to return from our ``as_sql`` method. In the above example,
``process_lhs`` returns ``('"author"."name"', [])`` and ``process_rhs`` returns
``('"%s"', ['Jack'])``. In this example there were no parameters for the left
hand side, but this would depend on the object we have, so we still need to
include them in the parameters we return.
Finally we combine the parts into a SQL expression with ``<>``, and supply all
the parameters for the query. We then return a tuple containing the generated
SQL string and the parameters.
A simple transformer example
~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The custom lookup above is great, but in some cases you may want to be able to
chain lookups together. For example, let's suppose we are building an
application where we want to make use of the ``abs()`` operator.
We have an ``Experiment`` model which records a start value, end value, and the
change (start - end). We would like to find all experiments where the change
was equal to a certain amount (``Experiment.objects.filter(change__abs=27)``),
or where it did not exceed a certain amount
(``Experiment.objects.filter(change__abs__lt=27)``).
.. note::
This example is somewhat contrived, but it nicely demonstrates the range of
functionality which is possible in a database backend independent manner,
and without duplicating functionality already in Django.
We will start by writing a ``AbsoluteValue`` transformer. This will use the SQL
function ``ABS()`` to transform the value before comparison::
from django.db.models import Transform
class AbsoluteValue(Transform):
lookup_name = 'abs'
def as_sql(self, qn, connection):
lhs, params = qn.compile(self.lhs)
return "ABS(%s)" % lhs, params
Next, lets register it for ``IntegerField``::
from django.db.models import IntegerField
IntegerField.register_lookup(AbsoluteValue)
We can now run the queries we had before.
``Experiment.objects.filter(change__abs=27)`` will generate the following SQL::
SELECT ... WHERE ABS("experiments"."change") = 27
By using ``Transform`` instead of ``Lookup`` it means we are able to chain
further lookups afterwards. So
``Experiment.objects.filter(change__abs__lt=27)`` will generate the following
SQL::
SELECT ... WHERE ABS("experiments"."change") < 27
Subclasses of ``Transform`` usually only operate on the left-hand side of the
expression. Further lookups will work on the transformed value. Note that in
this case where there is no other lookup specified, Django interprets
``change__abs=27`` as ``change__abs__exact=27``.
When looking for which lookups are allowable after the ``Transform`` has been
applied, Django uses the ``output_field`` attribute. We didn't need to specify
this here as it didn't change, but supposing we were applying ``AbsoluteValue``
to some field which represents a more complex type (for example a point
relative to an origin, or a complex number) then we may have wanted to specify
``output_field = FloatField``, which will ensure that further lookups like
``abs__lte`` behave as they would for a ``FloatField``.
Writing an efficient abs__lt lookup
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
When using the above written ``abs`` lookup, the SQL produced will not use
indexes efficiently in some cases. In particular, when we use
``change__abs__lt=27``, this is equivalent to ``change__gt=-27`` AND
``change__lt=27``. (For the ``lte`` case we could use the SQL ``BETWEEN``).
So we would like ``Experiment.objects.filter(change__abs__lt=27)`` to generate
the following SQL::
SELECT .. WHERE "experiments"."change" < 27 AND "experiments"."change" > -27
The implementation is::
from django.db.models import Lookup
class AbsoluteValueLessThan(Lookup):
lookup_name = 'lt'
def as_sql(self, qn, connection):
lhs, lhs_params = qn.compile(self.lhs.lhs)
rhs, rhs_params = self.process_rhs(qn, connection)
params = lhs_params + rhs_params + lhs_params + rhs_params
return '%s < %s AND %s > -%s' % (lhs, rhs, lhs, rhs), params
AbsoluteValue.register_lookup(AbsoluteValueLessThan)
There are a couple of notable things going on. First, ``AbsoluteValueLessThan``
isn't calling ``process_lhs()``. Instead it skips the transformation of the
``lhs`` done by ``AbsoluteValue`` and uses the original ``lhs``. That is, we
want to get ``27`` not ``ABS(27)``. Referring directly to ``self.lhs.lhs`` is
safe as ``AbsoluteValueLessThan`` can be accessed only from the
``AbsoluteValue`` lookup, that is the ``lhs`` is always an instance of
``AbsoluteValue``.
Notice also that as both sides are used multiple times in the query the params
need to contain ``lhs_params`` and ``rhs_params`` multiple times.
The final query does the inversion (``27`` to ``-27``) directly in the
database. The reason for doing this is that if the self.rhs is something else
than a plain integer value (for example an ``F()`` reference) we can't do the
transformations in Python.
.. note::
In fact, most lookups with ``__abs`` could be implemented as range queries
like this, and on most database backends it is likely to be more sensible to
do so as you can make use of the indexes. However with PostgreSQL you may
want to add an index on ``abs(change)`` which would allow these queries to
be very efficient.
Writing alternative implementations for existing lookups
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Sometimes different database vendors require different SQL for the same
operation. For this example we will rewrite a custom implementation for
MySQL for the NotEqual operator. Instead of ``<>`` we will be using ``!=``
operator. (Note that in reality almost all databases support both, including
all the official databases supported by Django).
We can change the behavior on a specific backend by creating a subclass of
``NotEqual`` with a ``as_mysql`` method::
class MySQLNotEqual(NotEqual):
def as_mysql(self, qn, connection):
lhs, lhs_params = self.process_lhs(qn, connection)
rhs, rhs_params = self.process_rhs(qn, connection)
params = lhs_params + rhs_params
return '%s != %s' % (lhs, rhs), params
Field.register_lookup(MySQLNotExact)
We can then register it with ``Field``. It takes the place of the original
``NotEqual`` class as it has the same ``lookup_name``.
When compiling a query, Django first looks for ``as_%s % connection.vendor``
methods, and then falls back to ``as_sql``. The vendor names for the in-built
backends are ``sqlite``, ``postgresql``, ``oracle`` and ``mysql``.
How Django determines the lookups and transforms which are used
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
In some cases you may which to dynamically change which ``Transform`` or
``Lookup`` is returned based on the name passed in, rather than fixing it. As
an example, you could have a field which stores coordinates or an arbitrary
dimension, and wish to allow a syntax like ``.filter(coords__x7=4)`` to return
the objects where the 7th coordinate has value 4. In order to do this, you
would override ``get_lookup`` with something like::
class CoordinatesField(Field):
def get_lookup(self, lookup_name):
if lookup_name.startswith('x'):
try:
dimension = int(lookup_name[1:])
except ValueError:
pass
finally:
return get_coordinate_lookup(dimension)
return super(CoordinatesField, self).get_lookup(lookup_name)
You would then define ``get_coordinate_lookup`` appropriately to return a
``Lookup`` subclass which handles the relevant value of ``dimension``.
There is a similarly named method called ``get_transform()``. ``get_lookup()``
should always return a ``Lookup`` subclass, and ``get_transform()`` a
``Transform`` subclass. It is important to remember that ``Transform``
objects can be further filtered on, and ``Lookup`` objects cannot.
When filtering, if there is only one lookup name remaining to be resolved, we
will look for a ``Lookup``. If there are multiple names, it will look for a
``Transform``. In the situation where there is only one name and a ``Lookup``
is not found, we look for a ``Transform`` and then the ``exact`` lookup on that
``Transform``. All call sequences always end with a ``Lookup``. To clarify:
- ``.filter(myfield__mylookup)`` will call ``myfield.get_lookup('mylookup')``.
- ``.filter(myfield__mytransform__mylookup)`` will call
``myfield.get_transform('mytransform')``, and then
``mytransform.get_lookup('mylookup')``.
- ``.filter(myfield__mytransform)`` will first call
``myfield.get_lookup('mytransform')``, which will fail, so it will fall back
to calling ``myfield.get_transform('mytransform')`` and then
``mytransform.get_lookup('exact')``.