mirror of https://github.com/django/django.git
433 lines
15 KiB
Plaintext
433 lines
15 KiB
Plaintext
==========================
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Performing raw SQL queries
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==========================
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.. currentmodule:: django.db.models
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Django gives you two ways of performing raw SQL queries: you can use
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:meth:`Manager.raw()` to `perform raw queries and return model instances`__, or
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you can avoid the model layer entirely and `execute custom SQL directly`__.
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__ `performing raw queries`_
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__ `executing custom SQL directly`_
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.. admonition:: Explore the ORM before using raw SQL!
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The Django ORM provides many tools to express queries without writing raw
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SQL. For example:
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* The :doc:`QuerySet API </ref/models/querysets>` is extensive.
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* You can :meth:`annotate <.QuerySet.annotate>` and :doc:`aggregate
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</topics/db/aggregation>` using many built-in :doc:`database functions
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</ref/models/database-functions>`. Beyond those, you can create
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:doc:`custom query expressions </ref/models/expressions/>`.
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Before using raw SQL, explore :doc:`the ORM </topics/db/index>`. Ask on
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one of :doc:`the support channels </faq/help>` to see if the ORM supports
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your use case.
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.. warning::
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You should be very careful whenever you write raw SQL. Every time you use
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it, you should properly escape any parameters that the user can control
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by using ``params`` in order to protect against SQL injection attacks.
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Please read more about :ref:`SQL injection protection
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<sql-injection-protection>`.
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.. _executing-raw-queries:
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Performing raw queries
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======================
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The ``raw()`` manager method can be used to perform raw SQL queries that
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return model instances:
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.. method:: Manager.raw(raw_query, params=(), translations=None)
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This method takes a raw SQL query, executes it, and returns a
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``django.db.models.query.RawQuerySet`` instance. This ``RawQuerySet`` instance
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can be iterated over like a normal :class:`~django.db.models.query.QuerySet` to
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provide object instances.
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This is best illustrated with an example. Suppose you have the following model::
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class Person(models.Model):
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first_name = models.CharField(...)
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last_name = models.CharField(...)
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birth_date = models.DateField(...)
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You could then execute custom SQL like so:
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.. code-block:: pycon
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>>> for p in Person.objects.raw("SELECT * FROM myapp_person"):
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... print(p)
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...
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John Smith
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Jane Jones
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This example isn't very exciting -- it's exactly the same as running
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``Person.objects.all()``. However, ``raw()`` has a bunch of other options that
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make it very powerful.
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.. admonition:: Model table names
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Where did the name of the ``Person`` table come from in that example?
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By default, Django figures out a database table name by joining the
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model's "app label" -- the name you used in ``manage.py startapp`` -- to
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the model's class name, with an underscore between them. In the example
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we've assumed that the ``Person`` model lives in an app named ``myapp``,
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so its table would be ``myapp_person``.
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For more details check out the documentation for the
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:attr:`~Options.db_table` option, which also lets you manually set the
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database table name.
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.. warning::
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No checking is done on the SQL statement that is passed in to ``.raw()``.
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Django expects that the statement will return a set of rows from the
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database, but does nothing to enforce that. If the query does not
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return rows, a (possibly cryptic) error will result.
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.. warning::
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If you are performing queries on MySQL, note that MySQL's silent type coercion
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may cause unexpected results when mixing types. If you query on a string
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type column, but with an integer value, MySQL will coerce the types of all values
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in the table to an integer before performing the comparison. For example, if your
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table contains the values ``'abc'``, ``'def'`` and you query for ``WHERE mycolumn=0``,
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both rows will match. To prevent this, perform the correct typecasting
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before using the value in a query.
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Mapping query fields to model fields
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------------------------------------
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``raw()`` automatically maps fields in the query to fields on the model.
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The order of fields in your query doesn't matter. In other words, both
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of the following queries work identically:
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.. code-block:: pycon
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>>> Person.objects.raw("SELECT id, first_name, last_name, birth_date FROM myapp_person")
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>>> Person.objects.raw("SELECT last_name, birth_date, first_name, id FROM myapp_person")
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Matching is done by name. This means that you can use SQL's ``AS`` clauses to
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map fields in the query to model fields. So if you had some other table that
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had ``Person`` data in it, you could easily map it into ``Person`` instances:
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.. code-block:: pycon
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>>> Person.objects.raw(
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... """
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... SELECT first AS first_name,
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... last AS last_name,
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... bd AS birth_date,
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... pk AS id,
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... FROM some_other_table
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... """
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... )
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As long as the names match, the model instances will be created correctly.
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Alternatively, you can map fields in the query to model fields using the
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``translations`` argument to ``raw()``. This is a dictionary mapping names of
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fields in the query to names of fields on the model. For example, the above
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query could also be written:
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.. code-block:: pycon
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>>> name_map = {"first": "first_name", "last": "last_name", "bd": "birth_date", "pk": "id"}
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>>> Person.objects.raw("SELECT * FROM some_other_table", translations=name_map)
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Index lookups
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-------------
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``raw()`` supports indexing, so if you need only the first result you can
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write:
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.. code-block:: pycon
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>>> first_person = Person.objects.raw("SELECT * FROM myapp_person")[0]
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However, the indexing and slicing are not performed at the database level. If
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you have a large number of ``Person`` objects in your database, it is more
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efficient to limit the query at the SQL level:
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.. code-block:: pycon
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>>> first_person = Person.objects.raw("SELECT * FROM myapp_person LIMIT 1")[0]
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Deferring model fields
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----------------------
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Fields may also be left out:
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.. code-block:: pycon
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>>> people = Person.objects.raw("SELECT id, first_name FROM myapp_person")
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The ``Person`` objects returned by this query will be deferred model instances
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(see :meth:`~django.db.models.query.QuerySet.defer()`). This means that the
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fields that are omitted from the query will be loaded on demand. For example:
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.. code-block:: pycon
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>>> for p in Person.objects.raw("SELECT id, first_name FROM myapp_person"):
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... print(
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... p.first_name, # This will be retrieved by the original query
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... p.last_name, # This will be retrieved on demand
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... )
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...
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John Smith
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Jane Jones
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From outward appearances, this looks like the query has retrieved both
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the first name and last name. However, this example actually issued 3
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queries. Only the first names were retrieved by the ``raw()`` query -- the
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last names were both retrieved on demand when they were printed.
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There is only one field that you can't leave out - the primary key
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field. Django uses the primary key to identify model instances, so it
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must always be included in a raw query. A
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:class:`~django.core.exceptions.FieldDoesNotExist` exception will be raised if
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you forget to include the primary key.
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Adding annotations
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------------------
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You can also execute queries containing fields that aren't defined on the
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model. For example, we could use `PostgreSQL's age() function`__ to get a list
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of people with their ages calculated by the database:
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.. code-block:: pycon
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>>> people = Person.objects.raw("SELECT *, age(birth_date) AS age FROM myapp_person")
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>>> for p in people:
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... print("%s is %s." % (p.first_name, p.age))
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...
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John is 37.
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Jane is 42.
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...
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You can often avoid using raw SQL to compute annotations by instead using a
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:ref:`Func() expression <func-expressions>`.
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__ https://www.postgresql.org/docs/current/functions-datetime.html
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Passing parameters into ``raw()``
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---------------------------------
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If you need to perform parameterized queries, you can use the ``params``
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argument to ``raw()``:
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.. code-block:: pycon
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>>> lname = "Doe"
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>>> Person.objects.raw("SELECT * FROM myapp_person WHERE last_name = %s", [lname])
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``params`` is a list or dictionary of parameters. You'll use ``%s``
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placeholders in the query string for a list, or ``%(key)s``
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placeholders for a dictionary (where ``key`` is replaced by a
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dictionary key), regardless of your database engine. Such placeholders will be
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replaced with parameters from the ``params`` argument.
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.. note::
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Dictionary params are not supported with the SQLite backend; with
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this backend, you must pass parameters as a list.
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.. warning::
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**Do not use string formatting on raw queries or quote placeholders in your
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SQL strings!**
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It's tempting to write the above query as:
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.. code-block:: pycon
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>>> query = "SELECT * FROM myapp_person WHERE last_name = %s" % lname
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>>> Person.objects.raw(query)
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You might also think you should write your query like this (with quotes
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around ``%s``):
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.. code-block:: pycon
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>>> query = "SELECT * FROM myapp_person WHERE last_name = '%s'"
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**Don't make either of these mistakes.**
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As discussed in :ref:`sql-injection-protection`, using the ``params``
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argument and leaving the placeholders unquoted protects you from `SQL
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injection attacks`__, a common exploit where attackers inject arbitrary
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SQL into your database. If you use string interpolation or quote the
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placeholder, you're at risk for SQL injection.
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__ https://en.wikipedia.org/wiki/SQL_injection
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.. _executing-custom-sql:
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Executing custom SQL directly
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=============================
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Sometimes even :meth:`Manager.raw` isn't quite enough: you might need to
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perform queries that don't map cleanly to models, or directly execute
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``UPDATE``, ``INSERT``, or ``DELETE`` queries.
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In these cases, you can always access the database directly, routing around
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the model layer entirely.
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The object ``django.db.connection`` represents the default database
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connection. To use the database connection, call ``connection.cursor()`` to
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get a cursor object. Then, call ``cursor.execute(sql, [params])`` to execute
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the SQL and ``cursor.fetchone()`` or ``cursor.fetchall()`` to return the
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resulting rows.
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For example::
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from django.db import connection
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def my_custom_sql(self):
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with connection.cursor() as cursor:
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cursor.execute("UPDATE bar SET foo = 1 WHERE baz = %s", [self.baz])
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cursor.execute("SELECT foo FROM bar WHERE baz = %s", [self.baz])
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row = cursor.fetchone()
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return row
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To protect against SQL injection, you must not include quotes around the ``%s``
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placeholders in the SQL string.
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Note that if you want to include literal percent signs in the query, you have to
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double them in the case you are passing parameters::
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cursor.execute("SELECT foo FROM bar WHERE baz = '30%'")
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cursor.execute("SELECT foo FROM bar WHERE baz = '30%%' AND id = %s", [self.id])
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If you are using :doc:`more than one database </topics/db/multi-db>`, you can
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use ``django.db.connections`` to obtain the connection (and cursor) for a
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specific database. ``django.db.connections`` is a dictionary-like
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object that allows you to retrieve a specific connection using its
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alias::
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from django.db import connections
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with connections["my_db_alias"].cursor() as cursor:
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# Your code here
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...
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By default, the Python DB API will return results without their field names,
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which means you end up with a ``list`` of values, rather than a ``dict``. At a
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small performance and memory cost, you can return results as a ``dict`` by
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using something like this::
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def dictfetchall(cursor):
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"""
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Return all rows from a cursor as a dict.
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Assume the column names are unique.
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"""
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columns = [col[0] for col in cursor.description]
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return [dict(zip(columns, row)) for row in cursor.fetchall()]
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Another option is to use :func:`collections.namedtuple` from the Python
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standard library. A ``namedtuple`` is a tuple-like object that has fields
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accessible by attribute lookup; it's also indexable and iterable. Results are
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immutable and accessible by field names or indices, which might be useful::
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from collections import namedtuple
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def namedtuplefetchall(cursor):
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"""
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Return all rows from a cursor as a namedtuple.
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Assume the column names are unique.
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"""
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desc = cursor.description
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nt_result = namedtuple("Result", [col[0] for col in desc])
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return [nt_result(*row) for row in cursor.fetchall()]
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The ``dictfetchall()`` and ``namedtuplefetchall()`` examples assume unique
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column names, since a cursor cannot distinguish columns from different tables.
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Here is an example of the difference between the three:
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.. code-block:: pycon
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>>> cursor.execute("SELECT id, parent_id FROM test LIMIT 2")
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>>> cursor.fetchall()
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((54360982, None), (54360880, None))
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>>> cursor.execute("SELECT id, parent_id FROM test LIMIT 2")
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>>> dictfetchall(cursor)
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[{'parent_id': None, 'id': 54360982}, {'parent_id': None, 'id': 54360880}]
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>>> cursor.execute("SELECT id, parent_id FROM test LIMIT 2")
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>>> results = namedtuplefetchall(cursor)
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>>> results
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[Result(id=54360982, parent_id=None), Result(id=54360880, parent_id=None)]
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>>> results[0].id
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54360982
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>>> results[0][0]
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54360982
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Connections and cursors
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-----------------------
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``connection`` and ``cursor`` mostly implement the standard Python DB-API
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described in :pep:`249` — except when it comes to :doc:`transaction handling
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</topics/db/transactions>`.
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If you're not familiar with the Python DB-API, note that the SQL statement in
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``cursor.execute()`` uses placeholders, ``"%s"``, rather than adding
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parameters directly within the SQL. If you use this technique, the underlying
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database library will automatically escape your parameters as necessary.
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Also note that Django expects the ``"%s"`` placeholder, *not* the ``"?"``
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placeholder, which is used by the SQLite Python bindings. This is for the sake
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of consistency and sanity.
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Using a cursor as a context manager::
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with connection.cursor() as c:
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c.execute(...)
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is equivalent to::
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c = connection.cursor()
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try:
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c.execute(...)
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finally:
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c.close()
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Calling stored procedures
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~~~~~~~~~~~~~~~~~~~~~~~~~
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.. method:: CursorWrapper.callproc(procname, params=None, kparams=None)
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Calls a database stored procedure with the given name. A sequence
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(``params``) or dictionary (``kparams``) of input parameters may be
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provided. Most databases don't support ``kparams``. Of Django's built-in
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backends, only Oracle supports it.
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For example, given this stored procedure in an Oracle database:
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.. code-block:: sql
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CREATE PROCEDURE "TEST_PROCEDURE"(v_i INTEGER, v_text NVARCHAR2(10)) AS
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p_i INTEGER;
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p_text NVARCHAR2(10);
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BEGIN
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p_i := v_i;
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p_text := v_text;
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...
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END;
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This will call it::
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with connection.cursor() as cursor:
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cursor.callproc("test_procedure", [1, "test"])
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