====================== Database API reference ====================== Once you've created your `data models`_, Django automatically gives you a database-abstraction API that lets you create, retrieve, update and delete objects. This document explains that API. .. _`data models`: http://www.djangoproject.com/documentation/model_api/ Throughout this reference, we'll refer to the following models, which comprise a weblog application:: class Blog(models.Model): name = models.CharField(maxlength=100) tagline = models.TextField() def __str__(self): return self.name class Author(models.Model): name = models.CharField(maxlength=50) email = models.URLField() class __str__(self): return self.name class Entry(models.Model): blog = models.ForeignKey(Blog) headline = models.CharField(maxlength=255) body_text = models.TextField() pub_date = models.DateTimeField() authors = models.ManyToManyField(Author) def __str__(self): return self.headline Creating objects ================ To represent database-table data in Python objects, Django uses an intuitive system: A model class represents a database table, and an instance of that class represents a particular record in the database table. To create an object, instantiate it using keyword arguments to the model class, then call ``save()`` to save it to the database. You import the model class from wherever it lives on the Python path, as you may expect. (We point this out here because previous Django versions required funky model importing.) Assuming models live in a file ``mysite/blog/models.py``, here's an example:: from mysite.blog.models import Blog b = Blog(name='Beatles Blog', tagline='All the latest Beatles news.') b.save() This performs an ``INSERT`` SQL statement behind the scenes. Django doesn't hit the database until you explicitly call ``save()``. The ``save()`` method has no return value. Auto-incrementing primary keys ------------------------------ If a model has an ``AutoField`` -- an auto-incrementing primary key -- then that auto-incremented value will be calculated and saved as an attribute on your object the first time you call ``save()``. Example:: b2 = Blog(name='Cheddar Talk', tagline='Thoughts on cheese.') b2.id # Returns None, because b doesn't have an ID yet. b2.save() b2.id # Returns the ID of your new object. There's no way to tell what the value of an ID will be before you call ``save()``, because that value is calculated by your database, not by Django. (For convenience, each model has an ``AutoField`` named ``id`` by default unless you explicitly specify ``primary_key=True`` on a field. See the `AutoField documentation`_.) .. _AutoField documentation: http://www.djangoproject.com/documentation/model_api/#autofield Explicitly specifying auto-primary-key values ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ If a model has an ``AutoField`` but you want to define a new object's ID explicitly when saving, just define it explicitly before saving, rather than relying on the auto-assignment of the ID. Example:: b3 = Blog(id=3, name='Cheddar Talk', tagline='Thoughts on cheese.') b3.id # Returns 3. b3.save() b3.id # Returns 3. If you assign auto-primary-key values manually, make sure not to use an already-existing primary-key value! If you create a new object with an explicit primary-key value that already exists in the database, Django will assume you're changing the existing record rather than creating a new one. Given the above ``'Cheddar Talk'`` blog example, this example would override the previous record in the database:: b4 = Blog(id=3, name='Not Cheddar', tagline='Anything but cheese.') b4.save() # Overrides the previous blog with ID=3! See _`How Django knows to UPDATE vs. INSERT`, below, for the reason this happens. Explicitly specifying auto-primary-key values is mostly useful for bulk-saving objects, when you're confident you won't have primary-key collision. Saving changes to objects ========================= To save changes to an object that's already in the database, use ``save()``. Given a ``Blog`` instance ``b5`` that has already been saved to the database, this example changes its name and updates its record in the database:: b5.name = 'New name' b5.save() This performs an ``UPDATE`` SQL statement behind the scenes. Django doesn't hit the database until you explicitly call ``save()``. The ``save()`` method has no return value. How Django knows to UPDATE vs. INSERT ------------------------------------- You may have noticed Django database objects use the same ``save()`` method for creating and changing objects. Django abstracts the need to use ``INSERT`` or ``UPDATE`` SQL statements. Specifically, when you call ``save()``, Django follows this algorithm: * If the object's primary key attribute is set to a value that evaluates to ``False`` (such as ``None`` or the empty string), Django executes a ``SELECT`` query to determine whether a record with the given primary key already exists. * If the record with the given primary key does already exist, Django executes an ``UPDATE`` query. * If the object's primary key attribute is *not* set, or if it's set but a record doesn't exist, Django executes an ``INSERT``. The one gotcha here is that you should be careful not to specify a primary-key value explicitly when saving new objects, if you cannot guarantee the primary-key value is unused. For more on this nuance, see "Explicitly specifying auto-primary-key values" above. Retrieving objects ================== To retrieve objects from your database, you construct a ``QuerySet`` via a ``Manager`` on your model class. A ``QuerySet`` represents a collection of objects from your database. It can have zero, one or many *filters* -- criteria that narrow down the collection based on given parameters. In SQL terms, a ``QuerySet`` equates to a ``SELECT`` statement, and a filter is a limiting clause such as ``WHERE`` or ``LIMIT``. You get a ``QuerySet`` by using your model's ``Manager``. Each model has at least one ``Manager``, and it's called ``objects`` by default. Access it directly via the model class, like so:: Blog.objects # b = Blog(name='Foo', tagline='Bar') b.objects # AttributeError: "Manager isn't accessible via Blog instances." (``Managers`` are accessible only via model classes, rather than from model instances, to enforce a separation between "table-level" operations and "record-level" operations.) The ``Manager`` is the main source of ``QuerySets`` for a model. It acts as a "root" ``QuerySet`` that describes all objects in the model's database table. For example, ``Blog.objects`` is the initial ``QuerySet`` that contains all ``Blog`` objects in the database. Retrieving all objects ---------------------- The simplest way to retrieve objects from a table is to get all of them. To do this, use the ``all()`` method on a ``Manager``. Example:: all_entries = Entry.objects.all() The ``all()`` method returns a ``QuerySet`` of all the objects in the database. (If ``Entry.objects`` is a ``QuerySet``, why can't we just do ``Entry.objects``? That's because ``Entry.objects``, the root ``QuerySet``, is a special case that cannot be evaluated. The ``all()`` method returns a ``QuerySet`` that *can* be evaluated.) Filtering objects ----------------- The root ``QuerySet`` provided by the ``Manager`` describes all objects in the database table. Usually, though, you'll need to select only a subset of the complete set of objects. To create such a subset, you refine the initial ``QuerySet``, adding filter conditions. The two most common ways to refine a ``QuerySet`` are: ``filter(**kwargs)`` Returns a new ``QuerySet`` containing objects that match the given lookup parameters. ``exclude(**kwargs)`` Returns a new ``QuerySet`` containing objects that do *not* match the given lookup parameters. The lookup parameters (``**kwargs`` in the above function definitions) should be in the format described in _`Field lookups` below. For example, to get a ``QuerySet`` of blog entries from the year 2006, use ``filter()`` like so:: Entry.objects.filter(pub_date__year=2006) (Note we don't have to add an ``all()`` -- ``Entry.objects.all().filter(...)``. That would still work, but you only need ``all()`` when you want all objects from the root ``QuerySet``.) Chaining filters ~~~~~~~~~~~~~~~~ The result of refining a ``QuerySet`` is itself a ``QuerySet``, so it's possible to chain refinements together. For example:: Entry.objects.filter( headline__startswith='What').exclude( pub_date__gte=datetime.now()).filter( pub_date__gte=datetime(2005, 1, 1)) ...takes the initial ``QuerySet`` of all entries in the database, adds a filter, then an exclusion, then another filter. The final result is a ``QuerySet`` containing all entries with a headline that starts with "What", that were published between January 1, 2005, and the current day. Filtered QuerySets are unique ----------------------------- Each time you refine a ``QuerySet``, you get a brand-new ``QuerySet`` that is in no way bound to the previous ``QuerySet``. Each refinement creates a separate and distinct ``QuerySet`` that can be stored, used and reused. Example:: q1 = Entry.objects.filter(headline__startswith="What") q2 = q1.exclude(pub_date__gte=datetime.now()) q3 = q1.filter(pub_date__gte=datetime.now()) These three ``QuerySets`` are separate. The first is a base ``QuerySet`` containing all entries that contain a headline starting with "What". The second is a subset of the first, with an additional criteria that excludes records whose ``pub_date`` is greater than now. The third is a subset of the first, with an additional criteria that selects only the records whose ``pub_date`` is greater than now. The initial ``QuerySet`` (``q1``) is unaffected by the refinement process. QuerySets are lazy ------------------ ``QuerySets`` are lazy -- the act of creating a ``QuerySet`` doesn't involve any database activity. You can stack filters together all day long, and Django won't actually run the query until the ``QuerySet`` is *evaluated*. When QuerySets are evaluated ~~~~~~~~~~~~~~~~~~~~~~~~~~~~ You can evaluate a ``QuerySet`` in the following ways: * **Iteration.** A ``QuerySet`` is iterable, and it executes its database query the first time you iterate over it. For example, this will print the headline of all entries in the database:: for e in Entry.objects.all(): print e.headline * **Slicing.** A ``QuerySet`` can be sliced, using Python's array-slicing syntax, and it executes its database query the first time you slice it. Examples:: fifth_entry = Entry.objects.all()[4] all_entries_but_the_first_two = Entry.objects.all()[2:] every_second_entry = Entry.objects.all()[::2] * **repr().** A ``QuerySet`` is evaluated when you call ``repr()`` on it. This is for convenience in the Python interactive interpreter, so you can immediately see your results when using the API interactively. * **len().** A ``QuerySet`` is evaluated when you call ``len()`` on it. This, as you might expect, returns the length of the result list. Note: *Don't* use ``len()`` on ``QuerySet``s if all you want to do is determine the number of records in the set. It's much more efficient to handle a count at the database level, using SQL's ``SELECT COUNT(*)``, and Django provides a ``count()`` method for precisely this reason. See ``count()`` below. * **list().** Force evaluation of a ``QuerySet`` by calling ``list()`` on it. For example:: entry_list = list(Entry.objects.all()) Be warned, though, that this could have a large memory overhead, because Django will load each element of the list into memory. In contrast, iterating over a ``QuerySet`` will take advantage of your database to load data and instantiate objects only as you need them. QuerySet methods that return new QuerySets ------------------------------------------ Django provides a range of ``QuerySet`` refinement methods that modify either the types of results returned by the ``QuerySet`` or the way its SQL query is executed. ``filter(**kwargs)`` ~~~~~~~~~~~~~~~~~~~~ Returns a new ``QuerySet`` containing objects that match the given lookup parameters. The lookup parameters (``**kwargs``) should be in the format described in _`Field lookups` below. Multiple parameters are joined via ``AND`` in the underlying SQL statement. ``exclude(**kwargs)`` ~~~~~~~~~~~~~~~~~~~~~ Returns a new ``QuerySet`` containing objects that do *not* match the given lookup parameters. The lookup parameters (``**kwargs``) should be in the format described in _`Field lookups` below. Multiple parameters are joined via ``AND`` in the underlying SQL statement, and the whole thing is enclosed in a ``NOT()``. This example excludes all entries whose ``pub_date`` is the current date/time AND whose ``headline`` is "Hello":: Entry.objects.exclude(pub_date__gt=datetime.date(2005, 1, 3), headline='Hello') In SQL terms, that evaluates to:: SELECT ... WHERE NOT (pub_date > '2005-1-3' AND headline = 'Hello') This example excludes all entries whose ``pub_date`` is the current date/time OR whose ``headline`` is "Hello":: Entry.objects.exclude(pub_date__gt=datetime.date(2005, 1, 3)).exclude(headline='Hello') In SQL terms, that evaluates to:: SELECT ... WHERE NOT pub_date > '2005-1-3' AND NOT headline = 'Hello' Note the second example is more restrictive. ``order_by(*fields)`` ~~~~~~~~~~~~~~~~~~~~~ By default, results returned by a ``QuerySet`` are ordered by the ordering tuple given by the ``ordering`` option in the model's ``Meta``. You can override this on a per-``QuerySet`` basis by using the ``order_by`` method. Example:: Entry.objects.filter(pub_date__year=2005).order_by('-pub_date', 'headline') The result above will be ordered by ``pub_date`` descending, then by ``headline`` ascending. The negative sign in front of ``"-pub_date"`` indicates *descending* order. Ascending order is implied. To order randomly, use ``"?"``, like so:: Entry.objects.order_by('?') To order by a field in a different table, add the other table's name and a dot, like so:: Entry.objects.order_by('blogs_blog.name', 'headline') There's no way to specify whether ordering should be case sensitive. With respect to case-sensitivity, Django will order results however your database backend normally orders them. ``distinct()`` ~~~~~~~~~~~~~~ Returns a new ``QuerySet`` that uses ``SELECT DISTINCT`` in its SQL query. This eliminates duplicate rows from the query results. By default, a ``QuerySet`` will not eliminate duplicate rows. In practice, this is rarely a problem, because simple queries such as ``Blog.objects.all()`` don't introduce the possibility of duplicate result rows. However, if your query spans multiple tables, it's possible to get duplicate results when a ``QuerySet`` is evaluated. That's when you'd use ``distinct()``. ``values(*fields)`` ~~~~~~~~~~~~~~~~~~~ Returns a ``ValuesQuerySet`` -- a ``QuerySet`` that evaluates to a list of dictionaries instead of model-instance objects. Each of those dictionaries represents an object, with the keys corresponding to the attribute names of model objects. This example compares the dictionaries of ``values()`` with the normal model objects:: # This list contains a Blog object. >>> Blog.objects.filter(name__startswith='Beatles') [Beatles Blog] # This list contains a dictionary. >>> Blog.objects.filter(name__startswith='Beatles').values() [{'id': 1, 'name': 'Beatles Blog', 'tagline': 'All the latest Beatles news.'}] ``values()`` takes optional positional arguments, ``*fields``, which specify field names to which the ``SELECT`` should be limited. If you specify the fields, each dictionary will contain only the field keys/values for the fields you specify. If you don't specify the fields, each dictionary will contain a key and value for every field in the database table. Example:: >>> Blog.objects.values() [{'id': 1, 'name': 'Beatles Blog', 'tagline': 'All the latest Beatles news.'}], >>> Blog.objects.values('id', 'name') [{'id': 1, 'name': 'Beatles Blog'}] A ``ValuesQuerySet`` is useful when you know you're only going to need values from a small number of the available fields and you won't need the functionality of a model instance object. It's more efficient to select only the fields you need to use. Finally, note a ``ValuesQuerySet`` is a subclass of ``QuerySet``, so it has all methods of ``QuerySet``. You can call ``filter()`` on it, or ``order_by()``, or whatever. Yes, that means these two calls are identical:: Blog.objects.values().order_by('id') Blog.objects.order_by('id').values() The people who made Django prefer to put all the SQL-affecting methods first, followed (optionally) by any output-affecting methods (such as ``values()``), but it doesn't really matter. This is your chance to really flaunt your individualism. ``dates(field, kind, order='ASC')`` ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Returns a ``DateQuerySet`` -- a ``QuerySet`` that evaluates to a list of ``datetime.datetime`` objects representing all available dates of a particular kind within the contents of the ``QuerySet``. ``field`` should be the name of a ``DateField`` or ``DateTimeField`` of your model. ``kind`` should be either ``"year"``, ``"month"`` or ``"day"``. Each ``datetime.datetime`` object in the result list is "truncated" to the given ``type``. * ``"year"`` returns a list of all distinct year values for the field. * ``"month"`` returns a list of all distinct year/month values for the field. * ``"day"`` returns a list of all distinct year/month/day values for the field. ``order``, which defaults to ``'ASC'``, should be either ``'ASC'`` or ``'DESC'``. This specifies how to order the results. Examples:: >>> Entry.objects.dates('pub_date', 'year') [datetime.datetime(2005, 1, 1)] >>> Entry.objects.dates('pub_date', 'month') [datetime.datetime(2005, 2, 1), datetime.datetime(2005, 3, 1)] >>> Entry.objects.dates('pub_date', 'day') [datetime.datetime(2005, 2, 20), datetime.datetime(2005, 3, 20)] >>> Entry.objects.dates('pub_date', 'day', order='DESC') [datetime.datetime(2005, 3, 20), datetime.datetime(2005, 2, 20)] >>> Entry.objects.filter(headline__contains='Lennon').dates('pub_date', 'day') [datetime.datetime(2005, 3, 20)] ``select_related()`` ~~~~~~~~~~~~~~~~~~~~ Returns a ``QuerySet`` that will automatically "follow" foreign-key relationships, selecting that additional related-object data when it executes its query. This is a performance booster which results in (sometimes much) larger queries but means later use of foreign-key relationships won't require database queries. The following examples illustrate the difference between plain lookups and ``select_related()`` lookups. Here's standard lookup:: # Hits the database. e = Entry.objects.get(id=5) # Hits the database again to get the related Blog object. b = e.blog And here's ``select_related`` lookup:: # Hits the database. e = Entry.objects.select_related().get(id=5) # Doesn't hit the database, because e.blog has been prepopulated # in the previous query. b = e.blog ``select_related()`` follows foreign keys as far as possible. If you have the following models:: class City(models.Model): # ... class Person(models.Model): # ... hometown = models.ForeignKey(City) class Book(meta.Model): # ... author = models.ForeignKey(Person) ...then a call to ``Book.objects.select_related().get(id=4)`` will cache the related ``Person`` *and* the related ``City``:: b = Book.objects.select_related().get(id=4) p = b.author # Doesn't hit the database. c = p.hometown # Doesn't hit the database. sv = Book.objects.get(id=4) # No select_related() in this example. p = b.author # Hits the database. c = p.hometown # Hits the database. ``extra(select=None, where=None, params=None, tables=None)`` ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Sometimes, the Django query syntax by itself can't easily express a complex ``WHERE`` clause. For these edge cases, Django provides the ``extra()`` ``QuerySet`` modifier -- a hook for injecting specific clauses into the SQL generated by a ``QuerySet``. By definition, these extra lookups may not be portable to different database engines (because you're explicitly writing SQL code) and violate the DRY principle, so you should avoid them if possible. Specify one or more of ``params``, ``select``, ``where`` or ``tables``. None of the arguments is required, but you should use at least one of them. ``select`` The ``select`` argument lets you put extra fields in the ``SELECT`` clause. It should be a dictionary mapping attribute names to SQL clauses to use to calculate that attribute. Example:: Entry.objects.extra(select={'is_recent': "pub_date > '2006-01-01'"}) As a result, each ``Entry`` object will have an extra attribute, ``is_recent``, a boolean representing whether the entry's ``pub_date`` is greater than Jan. 1, 2006. Django inserts the given SQL snippet directly into the ``SELECT`` statement, so the resulting SQL of the above example would be:: SELECT blog_entry.*, (pub_date > '2006-01-01') FROM blog_entry; The next example is more advanced; it does a subquery to give each resulting ``Blog`` object an ``entry_count`` attribute, an integer count of associated ``Entry`` objects:: Blog.objects.extra( select={ 'entry_count': 'SELECT COUNT(*) FROM blog_entry WHERE blog_entry.blog_id = blog_blog.id' }, ) (In this particular case, we're exploiting the fact that the query will already contain the ``blog_blog`` table in its ``FROM`` clause.) The resulting SQL of the above example would be:: SELECT blog_blog.*, (SELECT COUNT(*) FROM blog_entry WHERE blog_entry.blog_id = blog_blog.id) FROM blog_blog; Note that the parenthesis required by most database engines around subqueries are not required in Django's ``select`` clauses. Also note that some database backends, such as some MySQL versions, don't support subqueries. ``where`` / ``tables`` You can define explicit SQL ``WHERE`` clauses -- perhaps to perform non-explicit joins -- by using ``where``. You can manually add tables to the SQL ``FROM`` clause by using ``tables``. ``where`` and ``tables`` both take a list of strings. All ``where`` parameters are "AND"ed to any other search criteria. Example:: Entry.objects.extra(where=['id IN (3, 4, 5, 20)']) ...translates (roughly) into the following SQL:: SELECT * FROM blog_entry WHERE id IN (3, 4, 5, 20); ``params`` The ``select`` and ``where`` parameters described above may use standard Python database string placeholders -- ``'%s'`` to indicate parameters the database engine should automatically quote. The ``params`` argument is a list of any extra parameters to be substituted. Example:: Entry.objects.extra(where=['headline=%s'], params=['Lennon']) Always use ``params`` instead of embedding values directly into ``select`` or ``where`` because ``params`` will ensure values are quoted correctly according to your particular backend. (For example, quotes will be escaped correctly.) Bad:: Entry.objects.extra(where=["headline='Lennon'"]) Good:: Entry.objects.extra(where=['headline=%s'], params=['Lennon']) QuerySet methods that do not return QuerySets --------------------------------------------- The following ``QuerySet`` methods evaluate the ``QuerySet`` and return something *other than* a ``QuerySet``. These methods do not use a cache (see _`Caching and QuerySets` below). Rather, they query the database each time they're called. ``get(**kwargs)`` ~~~~~~~~~~~~~~~~~ Returns the object matching the given lookup parameters, which should be in the format described in _`Field lookups`. ``get()`` raises ``AssertionError`` if more than one object was found. ``get()`` raises a ``DoesNotExist`` exception if an object wasn't found for the given parameters. The ``DoesNotExist`` exception is an attribute of the model class. Example:: Entry.objects.get(id='foo') # raises Entry.DoesNotExist The ``DoesNotExist`` exception inherits from ``django.core.exceptions.ObjectDoesNotExist``, so you can target multiple ``DoesNotExist`` exceptions. Example:: from django.core.exceptions import ObjectDoesNotExist try: e = Entry.objects.get(id=3) b = Blog.objects.get(id=1) except ObjectDoesNotExist: print "Either the entry or blog doesn't exist." ``count()`` ~~~~~~~~~~~ Returns an integer representing the number of objects in the database matching the ``QuerySet``. ``count()`` never raises exceptions. Example:: # Returns the total number of entries in the database. Entry.objects.count() # Returns the number of entries whose headline contains 'Lennon' Entry.objects.filter(headline__contains='Lennon').count() ``count()`` performs a ``SELECT COUNT(*)`` behind the scenes, so you should always use ``count()`` rather than loading all of the record into Python objects and calling ``len()`` on the result. Depending on which database you're using (e.g. PostgreSQL vs. MySQL), ``count()`` may return a long integer instead of a normal Python integer. This is an underlying implementation quirk that shouldn't pose any real-world problems. ``in_bulk(id_list)`` ~~~~~~~~~~~~~~~~~~~~ Takes a list of primary-key values and returns a dictionary mapping each primary-key value to an instance of the object with the given ID. Example:: >>> Blog.objects.in_bulk([1]) {1: Beatles Blog} >>> Blog.objects.in_bulk([1, 2]) {1: Beatles Blog, 2: Cheddar Talk} >>> Blog.objects.in_bulk([]) {} If you pass ``in_bulk()`` an empty list, you'll get an empty dictionary. ``latest(field_name=None)`` ~~~~~~~~~~~~~~~~~~~~~~~~~~~ Returns the latest object in the table, by date, using the ``field_name`` provided as the date field. This example returns the latest ``Entry`` in the table, according to the ``pub_date`` field:: Entry.objects.latest('pub_date') If your model's ``Meta`` specifies ``get_latest_by``, you can leave off the ``field_name`` argument to ``latest()``. Django will use the field specified in ``get_latest_by`` by default. Like ``get()``, ``latest()`` raises ``DoesNotExist`` if an object doesn't exist with the given parameters. Note ``latest()`` exists purely for convenience and readability. Field lookups ------------- Field lookups are how you specify the meat of an SQL ``WHERE`` clause. They're specified as keyword arguments to the ``QuerySet`` methods ``filter()``, ``exclude()`` and ``get()``. Basic lookups keyword arguments take the form ``field__lookuptype=value``. (That's a double-underscore). For example:: Entry.objects.filter(pub_date__lte='2006-01-01') translates (roughly) into the following SQL:: SELECT * FROM blog_entry WHERE pub_date <= '2006-01-01'; .. admonition:: How this is possible Python has the ability to define functions that accept arbitrary name-value arguments whose names and values are evaluated at runtime. For more information, see `Keyword Arguments`_ in the official Python tutorial. .. _`Keyword Arguments`: http://docs.python.org/tut/node6.html#SECTION006720000000000000000 If you pass an invalid keyword argument, a lookup function will raise ``TypeError``. The database API supports the following lookup types: exact ~~~~~ Exact match. Example:: Entry.objects.get(id__exact=14) SQL equivalent:: SELECT ... WHERE id = 14; iexact ~~~~~~ Case-insensitive exact match. Example:: Blog.objects.get(name__iexact='beatles blog') SQL equivalent:: SELECT ... WHERE name ILIKE 'beatles blog'; Note this will match ``'Beatles Blog'``, ``'beatles blog'``, ``'BeAtLes BLoG'``, etc. contains ~~~~~~~~ Case-sensitive containment test. Example:: Entry.objects.get(headline__contains='Lennon') SQL equivalent:: SELECT ... WHERE headline LIKE '%Lennon%'; Note this will match the headline ``'Today Lennon honored'`` but not ``'today lennon honored'``. SQLite doesn't support case-sensitive ``LIKE`` statements; ``contains`` acts like ``icontains`` for SQLite. icontains ~~~~~~~~~ Case-insensitive containment test. Example:: Entry.objects.get(headline__icontains='Lennon') SQL equivalent:: SELECT ... WHERE headline ILIKE '%Lennon%'; gt ~~ Greater than. Example:: Entry.objects.filter(id__gt=4) SQL equivalent:: SELECT ... WHERE id > 4; gte ~~~ Greater than or equal to. lt ~~ Less than. lte ~~~ Less than or equal to. in ~~ In a given list. Example:: Entry.objects.filter(id__in=[1, 3, 4]) SQL equivalent:: SELECT ... WHERE id IN (1, 3, 4); startswith ~~~~~~~~~~ Case-sensitive starts-with. Example:: Entry.objects.filter(headline__startswith='Will') SQL equivalent:: SELECT ... WHERE headline LIKE 'Will%'; SQLite doesn't support case-sensitive ``LIKE`` statements; ``startswith`` acts like ``istartswith`` for SQLite. istartswith ~~~~~~~~~~~ Case-insensitive starts-with. Example:: Entry.objects.filter(headline__istartswith='will') SQL equivalent:: SELECT ... WHERE headline ILIKE 'Will%'; endswith ~~~~~~~~ Case-sensitive ends-with. Example:: Entry.objects.filter(headline__endswith='cats') SQL equivalent:: SELECT ... WHERE headline LIKE '%cats'; SQLite doesn't support case-sensitive ``LIKE`` statements; ``endswith`` acts like ``iendswith`` for SQLite. iendswith ~~~~~~~~~ Case-insensitive ends-with. Example:: Entry.objects.filter(headline__iendswith='will') SQL equivalent:: SELECT ... WHERE headline ILIKE '%will' range ~~~~~ Range test (inclusive). Example:: start_date = datetime.date(2005, 1, 1) end_date = datetime.date(2005, 3, 31) Entry.objects.filter(pub_date__range=(start_date, end_date)) SQL equivalent:: SELECT ... WHERE pub_date BETWEEN '2005-01-01' and '2005-03-31'; You can use ``range`` anywhere you can use ``BETWEEN`` in SQL -- for dates, numbers and even characters. year ~~~~ For date/datetime fields, exact year match. Takes a four-digit year. Example:: Entry.objects.filter(pub_date__year=2005) SQL equivalent:: SELECT ... WHERE EXTRACT('year' FROM pub_date) = '2005'; (The exact SQL syntax varies for each database engine.) month ~~~~~ For date/datetime fields, exact month match. Takes an integer 1 (January) through 12 (December). Example:: Entry.objects.filter(pub_date__month=12) SQL equivalent:: SELECT ... WHERE EXTRACT('month' FROM pub_date) = '12'; (The exact SQL syntax varies for each database engine.) day ~~~ For date/datetime fields, exact day match. Example:: Entry.objects.filter(pub_date__day=3) SQL equivalent:: SELECT ... WHERE EXTRACT('day' FROM pub_date) = '3'; (The exact SQL syntax varies for each database engine.) Note this will match any record with a pub_date on the third day of the month, such as January 3, July 3, etc. isnull ~~~~~~ ``NULL`` or ``IS NOT NULL`` match. Takes either ``True`` or ``False``, which correspond to ``IS NULL`` and ``IS NOT NULL``, respectively. Example:: Entry.objects.filter(pub_date__isnull=True) SQL equivalent:: SELECT ... WHERE pub_date IS NULL; Default lookups are exact ~~~~~~~~~~~~~~~~~~~~~~~~~ If you don't provide a lookup type -- that is, if your keyword argument doesn't contain a double underscore -- the lookup type is assumed to be ``exact``. For example, the following two statements are equivalent:: Blog.objects.get(id=14) Blog.objects.get(id__exact=14) This is for convenience, because ``exact`` lookups are the common case. The pk lookup shortcut ~~~~~~~~~~~~~~~~~~~~~~ For convenience, Django provides a ``pk`` lookup type, which stands for "primary_key". This is shorthand for "an exact lookup on the primary-key." In the example ``Blog`` model, the primary key is the ``id`` field, so these two statements are equivalent:: Blog.objects.get(id__exact=14) Blog.objects.get(pk=14) ``pk`` lookups also work across joins. For example, these two statements are equivalent:: Entry.objects.filter(blog__id__exact=3) Entry.objects.filter(blog__pk=3) Escaping parenthesis and underscores in LIKE statements ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ The field lookups that equate to ``LIKE`` SQL statements (``iexact``, ``contains``, ``icontains``, ``startswith``, ``istartswith``, ``endswith`` and ``iendswith``) will automatically escape the two special characters used in ``LIKE`` statements -- the percent sign and the underscore. (In a ``LIKE`` statement, the percent sign signifies a multiple-character wildcard and the underscore signifies a single-character wildcard.) This means things should work intuitively, so the abstraction doesn't leak. For example, to retrieve all the entries that contain a percent sign, just use the percent sign as any other character:: Entry.objects.filter(headline__contains='%') Django takes care of the quoting for you; the resulting SQL will look something like this:: SELECT ... WHERE headline LIKE '%\%%'; Same goes for underscores. Both percentage signs and underscores are handled for you transparently. Caching and QuerySets --------------------- Each ``QuerySet`` contains a cache, to minimize database access. It's important to understand how it works, in order to write the most efficient code. In a newly created ``QuerySet``, the cache is empty. The first time a ``QuerySet`` is evaluated -- and, hence, a database query happens -- Django saves the query results in the ``QuerySet``'s cache and returns the results that have been explicitly requested (e.g., the next element, if the ``QuerySet`` is being iterated over). Subsequent evaluations of the ``QuerySet`` reuse the cached results. Keep this caching behavior in mind, because it may bite you if you don't use your ``QuerySet``s correctly. For example, the following will create two ``QuerySet``s, evaluate them, and throw them away:: print [e.headline for e in Entry.objects.all()] print [e.pub_date for e in Entry.objects.all()] That means the same database query will be executed twice, effectively doubling your database load. Also, there's a possibility the two lists may not include the same database records, because an ``Entry`` may have been added or deleted in the split second between the two requests. To avoid this problem, simply save the ``QuerySet`` and reuse it:: queryset = Poll.objects.all() print [p.headline for p in queryset] # Evaluate the query set. print [p.pub_date for p in queryset] # Re-use the cache from the evaluation. Comparing objects ================= To compare two model instances, just use the standard Python comparison operator, the double equals sign: ``==``. Behind the scenes, that compares the primary key values of two models. Using the ``Entry`` example above, the following two statements are equivalent:: some_entry == other_entry some_entry.id == other_entry.id If a model's primary key isn't called ``id``, no problem. Comparisons will always use the primary key, whatever it's called. For example, if a model's primary key field is called ``name``, these two statements are equivalent:: some_obj == other_obj some_obj.name == other_obj.name OR lookups ========== Keyword argument queries are "AND"ed together. If you have more complex query requirements (for example, you need to include an ``OR`` statement in your query), you need to 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 in the same way as keyword arguments to the basic lookup functions like get() and filter(). For example:: Q(question__startswith='What') is a ``Q`` object encapsulating a single ``LIKE`` query. ``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 the statement:: Q(question__startswith='Who') | Q(question__startswith='What') ... yields a single ``Q`` object that represents the "OR" of two "question__startswith" queries, equivalent to the 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. Parenthetical grouping can also be used. One or more ``Q`` objects can then provided as arguments to the lookup functions. If multiple ``Q`` object arguments are provided to a lookup function, they 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') If necessary, lookup functions can mix the use of ``Q`` objects and keyword arguments. All arguments provided to a lookup function (be they keyword argument or ``Q`` object) 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. A ``Q`` objects can also be provided to the ``complex`` keyword argument. For example:: Poll.objects.get( complex=Q(question__startswith='Who') & (Q(pub_date=date(2005, 5, 2)) | Q(pub_date=date(2005, 5, 6)) ) ) See the `OR lookups examples page`_ for more examples. .. _OR lookups examples page: http://www.djangoproject.com/documentation/models/or_lookups/ Relationships (joins) ===================== When you define a relationship in a model (i.e., a ForeignKey, OneToOneField, or ManyToManyField), Django uses the name of the relationship to add a descriptor_ on every instance of the model. This descriptor behaves just like a normal attribute, providing access to the related object or objects. For example, ``mychoice.poll`` will return the poll object associated with a specific instance of ``Choice``. .. _descriptor: http://users.rcn.com/python/download/Descriptor.htm Django also adds a descriptor for the 'other' side of the relationship - the link from the related model to the model that defines the relationship. Since the related model has no explicit reference to the source model, Django will automatically derive a name for this descriptor. The name that Django chooses depends on the type of relation that is represented. However, if the definition of the relation has a `related_name` parameter, Django will use this name in preference to deriving a name. There are two types of descriptor that can be employed: Single Object Descriptors and Object Set Descriptors. The following table describes when each descriptor type is employed. The local model is the model on which the relation is defined; the related model is the model referred to by the relation. =============== ============= ============= Relation Type Local Model Related Model =============== ============= ============= OneToOneField Single Object Single Object ForeignKey Single Object Object Set ManyToManyField Object Set Object Set =============== ============= ============= Single object descriptor ------------------------ If the related object is a single object, the descriptor acts just as if the related object were an attribute:: # Obtain the existing poll old_poll = mychoice.poll # Set a new poll mychoice.poll = new_poll # Save the change mychoice.save() Whenever a change is made to a Single Object Descriptor, save() must be called to commit the change to the database. If no `related_name` parameter is defined, Django will use the lower case version of the source model name as the name for the related descriptor. For example, if the ``Choice`` model had a field:: coordinator = models.OneToOneField(User) ... instances of the model ``User`` would be able to call: old_choice = myuser.choice myuser.choice = new_choice By default, relations do not allow values of None; if you attempt to assign None to a Single Object Descriptor, an AttributeError will be thrown. However, if the relation has 'null=True' set (i.e., the database will allow NULLs for the relation), None can be assigned and returned by the descriptor to represent empty relations. Access to Single Object Descriptors is cached. The first time a descriptor on an instance is accessed, the database will be queried, and the result stored. Subsequent attempts to access the descriptor on the same instance will use the cached value. Object set descriptor --------------------- An Object Set Descriptor acts just like the Manager - as an initial Query Set describing the set of objects related to an instance. As such, any query refining technique (filter, exclude, etc) can be used on the Object Set descriptor. This also means that Object Set Descriptor cannot be evaluated directly - the ``all()`` method must be used to produce a Query Set that can be evaluated. If no ``related_name`` parameter is defined, Django will use the lower case version of the source model name appended with `_set` as the name for the related descriptor. For example, every ``Poll`` object has a ``choice_set`` descriptor. The Object Set Descriptor has utility methods to add objects to the related object set: ``add(obj1, obj2, ...)`` Add the specified objects to the related object set. ``create(\**kwargs)`` Create a new object, and put it in the related object set. See _`Creating new objects` The Object Set Descriptor may also have utility methods to remove objects from the related object set: ``remove(obj1, obj2, ...)`` Remove the specified objects from the related object set. ``clear()`` Remove all objects from the related object set. These two removal methods will not exist on ForeignKeys where ``Null=False`` (such as in the Poll example). This is to prevent database inconsistency - if the related field cannot be set to None, then an object cannot be removed from one relation without adding it to another. The members of a related object set can be assigned from any iterable object. For example:: mypoll.choice_set = [choice1, choice2] If the ``clear()`` method is available, any pre-existing objects will be removed from the Object Set before all objects in the iterable (in this case, a list) are added to the choice set. If the ``clear()`` method is not available, all objects in the iterable will be added without removing any existing elements. Each of these operations on the Object Set Descriptor has immediate effect on the database - every add, create and remove is immediately and automatically saved to the database. Relationships and queries ========================= When composing a ``filter`` or ``exclude`` refinement, it may be necessary to include conditions that span relationships. Relations can be followed as deep as required - just add descriptor names, separated by double underscores, to describe the full path to the query attribute. The query:: Foo.objects.filter(name1__name2__name3__attribute__lookup=value) ... is interpreted as 'get every Foo that has a name1 that has a name2 that has a name3 that has an attribute with lookup matching value'. In the Poll example:: Choice.objects.filter(poll__slug__startswith="eggs") ... describes the set of choices for which the related poll has a slug attribute that starts with "eggs". Django automatically composes the joins and conditions required for the SQL query. Creating new related objects ============================ Related objects are created using the ``create()`` convenience function on the descriptor Manager for relation:: >>> p.choice_set.create(choice="Over easy", votes=0) >>> p.choice_set.create(choice="Scrambled", votes=0) >>> p.choice_set.create(choice="Fertilized", votes=0) >>> p.choice_set.create(choice="Poached", votes=0) >>> p.choice_set.count() 4 Each of those ``create()`` methods is equivalent to (but much simpler than):: >>> c = Choice(poll_id=p.id, choice="Over easy", votes=0) >>> c.save() Note that when using the `create()`` method, you do not give any value for the ``id`` field, nor do you give a value for the field that stores the relation (``poll_id`` in this case). The ``create()`` method always returns the newly created object. Deleting objects ================ The delete method, conveniently, is named ``delete()``. This method immediately deletes the object and has no return value. Example:: >>> c.delete() Objects can also be deleted in bulk. Every Query Set has a ``delete()`` method that will delete all members of the query set. For example:: >>> Polls.objects.filter(pub_date__year=2005).delete() would bulk delete all Polls with a year of 2005. Note that ``delete()`` is the only Query Set method that is not exposed on the Manager itself. This is a safety mechanism to prevent you from accidentally requesting ``Polls.objects.delete()``, and deleting *all* the polls. If you *actually* want to delete all the objects, then you have to explicitly request a complete query set:: Polls.objects.all().delete() Extra instance methods ====================== In addition to ``save()``, ``delete()``, a model object might get any or all of the following methods: get_FOO_display() ----------------- For every field that has ``choices`` set, the object will have a ``get_FOO_display()`` method, where ``FOO`` is the name of the field. This method returns the "human-readable" value of the field. For example, in the following model:: GENDER_CHOICES = ( ('M', 'Male'), ('F', 'Female'), ) class Person name = meta.CharField(maxlength=20) gender = meta.CharField(maxlength=1, choices=GENDER_CHOICES) ...each ``Person`` instance will have a ``get_gender_display()`` method. Example:: >>> p = Person(name='John', gender='M') >>> p.save() >>> p.gender 'M' >>> p.get_gender_display() 'Male' get_next_by_FOO(\**kwargs) and get_previous_by_FOO(\**kwargs) ------------------------------------------------------------- For every ``DateField`` and ``DateTimeField`` that does not have ``null=True``, the object will have ``get_next_by_FOO()`` and ``get_previous_by_FOO()`` methods, where ``FOO`` is the name of the field. This returns the next and previous object with respect to the date field, raising the appropriate ``DoesNotExist`` exception when appropriate. Both methods accept optional keyword arguments, which should be in the format described in _`Field lookups` above. Note that in the case of identical date values, these methods will use the ID as a fallback check. This guarantees that no records are skipped or duplicated. For a full example, see the `lookup API sample model_`. .. _lookup API sample model: http://www.djangoproject.com/documentation/models/lookup/ get_FOO_filename() ------------------ For every ``FileField``, the object will have a ``get_FOO_filename()`` method, where ``FOO`` is the name of the field. This returns the full filesystem path to the file, according to your ``MEDIA_ROOT`` setting. Note that ``ImageField`` is technically a subclass of ``FileField``, so every model with an ``ImageField`` will also get this method. get_FOO_url() ------------- For every ``FileField``, the object will have a ``get_FOO_url()`` method, where ``FOO`` is the name of the field. This returns the full URL to the file, according to your ``MEDIA_URL`` setting. If the value is blank, this method returns an empty string. get_FOO_size() -------------- For every ``FileField``, the object will have a ``get_FOO_filename()`` method, where ``FOO`` is the name of the field. This returns the size of the file, in bytes. (Behind the scenes, it uses ``os.path.getsize``.) save_FOO_file(filename, raw_contents) ------------------------------------- For every ``FileField``, the object will have a ``get_FOO_filename()`` method, where ``FOO`` is the name of the field. This saves the given file to the filesystem, using the given filename. If a file with the given filename already exists, Django adds an underscore to the end of the filename (but before the extension) until the filename is available. get_FOO_height() and get_FOO_width() ------------------------------------ For every ``ImageField``, the object will have ``get_FOO_height()`` and ``get_FOO_width()`` methods, where ``FOO`` is the name of the field. This returns the height (or width) of the image, as an integer, in pixels.