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.

Forcing an INSERT or UPDATE

New in Django development version

In some rare circumstances, it’s necesary to be able to force the save() method to perform an SQL INSERT and not fall back to doing an UPDATE. Or vice-versa: update, if possible, but not insert a new row. In these cases you can pass the force_insert=True or force_update=True parameters to the save() method. Passing both parameters is an error, since you cannot both insert and update at the same time.

It should be very rare that you’ll need to use these parameters. Django will almost always do the right thing and trying to override that will lead to errors that are difficult to track down. This feature is for advanced use only.

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.

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. As explained in Limiting QuerySets below, a QuerySet can be sliced, using Python’s array-slicing syntax. Usually slicing a QuerySet returns another (unevaluated )``QuerySet``, but Django will execute the database query if you use the “step” parameter of slice syntax.

• repr(). A QuerySet is evaluated when you call repr() on it. This is for convenience in the Python interactive interpreter, so you can immediately see your results when using the API interactively.

• len(). A QuerySet is evaluated when you call len() on it. This, as you might expect, returns the length of the result list.

  Note: Don’t use len() on QuerySets 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.

Pickling QuerySets

If you pickle a QuerySet, this will also force all the results to be loaded into memory prior to pickling. This is because pickling is usually used as a precursor to caching and when the cached QuerySet is reloaded, you want the results to already be present. This means that when you unpickle a QuerySet, it contains the results at the moment it was pickled, rather than the results that are currently in the database.

If you only want to pickle the necessary information to recreate the Queryset from the database at a later time, pickle the query attribute of the QuerySet. You can then recreate the original QuerySet (without any results loaded) using some code like this:

>>> import pickle
>>> query = pickle.loads(s)     # Assuming 's' is the pickled string.
>>> qs = MyModel.objects.all()
>>> qs.query = query            # Restore the original 'query'.

filter(**kwargs)

Returns a new QuerySet containing objects that match the given lookup parameters.

The lookup parameters (**kwargs) should be in the format described in Field lookups below. Multiple parameters are joined via AND in the underlying SQL statement.

exclude(**kwargs)

Returns a new QuerySet containing objects that do not match the given lookup parameters.

The lookup parameters (**kwargs) should be in the format described in Field lookups below. Multiple parameters are joined via AND in the underlying SQL statement, and the whole thing is enclosed in a NOT().

This example excludes all entries whose pub_date is later than 2005-1-3 AND whose headline is “Hello”:

Entry.objects.exclude(pub_date__gt=datetime.date(2005, 1, 3), headline='Hello')

In SQL terms, that evaluates to:

SELECT ...
WHERE NOT (pub_date > '2005-1-3' AND headline = 'Hello')

This example excludes all entries whose pub_date is later than 2005-1-3 OR whose headline is “Hello”:

Entry.objects.exclude(pub_date__gt=datetime.date(2005, 1, 3)).exclude(headline='Hello')

In SQL terms, that evaluates to:

SELECT ...
WHERE NOT pub_date > '2005-1-3'
AND NOT headline = 'Hello'

Note the second example is more restrictive.

order_by(*fields)

By default, results returned by a QuerySet are ordered by the ordering tuple given by the ordering option in the model’s Meta. You can override this on a per-QuerySet basis by using the order_by method.

Example:

Entry.objects.filter(pub_date__year=2005).order_by('-pub_date', 'headline')

The result above will be ordered by pub_date descending, then by headline ascending. The negative sign in front of "-pub_date" indicates descending order. Ascending order is implied. To order randomly, use "?", like so:

Entry.objects.order_by('?')

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

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

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

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

Entry.objects.order_by('blog')

…is identical to:

Entry.objects.order_by('blog__id')

…since the Blog model has no default ordering specified.

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

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

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

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

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.

reverse()

New in Django development version

Use the reverse() method to reverse the order in which a queryset’s elements are returned. Calling reverse() a second time restores the ordering back to the normal direction.

To retrieve the ‘’last’’ five items in a queryset, you could do this:

my_queryset.reverse()[:5]

Note that this is not quite the same as slicing from the end of a sequence in Python. The above example will return the last item first, then the penultimate item and so on. If we had a Python sequence and looked at seq[:-5], we would see the fifth-last item first. Django doesn’t support that mode of access (slicing from the end), because it’s not possible to do it efficiently in SQL.

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

distinct()

Returns a new QuerySet that uses SELECT DISTINCT in its SQL query. This eliminates duplicate rows from the query results.

By default, a QuerySet will not eliminate duplicate rows. In practice, this is rarely a problem, because simple queries such as Blog.objects.all() don’t introduce the possibility of duplicate result rows. However, if your query spans multiple tables, it’s possible to get duplicate results when a QuerySet is evaluated. That’s when you’d use distinct().

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'}]

You can also retrieve values from across ForeignKey relations by using double underscores to separate the field names, just as when calling the filter() command. For example:

>>> Entry.objects.values('blog__name').distinct()
[{'name': 'Beatles Blog'}]

A couple of subtleties that are worth mentioning:

• The values() method does not return anything for ManyToManyField attributes and will raise an error if you try to pass in this type of field to it.

• If you have a field called foo that is a ForeignKey, the default values() call will return a dictionary key called foo_id, since this is the name of the hidden model attribute that stores the actual value (the foo attribute refers to the related model). When you are calling values() and passing in field names, you can pass in either foo or foo_id and you will get back the same thing (the dictionary key will match the field name you passed in).

  For example:

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

• When using values() together with distinct(), be aware that ordering can affect the results. See the note in the distinct() section, above, for details.

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

A ValuesQuerySet is useful when you know you’re only going to need values from a small number of the available fields and you won’t need the functionality of a model instance object. It’s more efficient to select only the fields you need to use.

Finally, note a ValuesQuerySet is a subclass of QuerySet, so it has all methods of QuerySet. You can call filter() on it, or order_by(), or whatever. Yes, that means these two calls are identical:

Blog.objects.values().order_by('id')
Blog.objects.order_by('id').values()

The people who made Django prefer to put all the SQL-affecting methods first, followed (optionally) by any output-affecting methods (such as values()), but it doesn’t really matter. This is your chance to really flaunt your individualism.

values_list(*fields)

New in Django development version

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

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

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

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

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

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

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

dates(field, kind, order='ASC')

Returns a DateQuerySet — a QuerySet that evaluates to a list of datetime.datetime objects representing all available dates of a particular kind within the contents of the QuerySet.

field should be the name of a DateField or DateTimeField of your model.

kind should be either "year", "month" or "day". Each datetime.datetime object in the result list is “truncated” to the given type.

• "year" returns a list of all distinct year values for the field.
• "month" returns a list of all distinct year/month values for the field.
• "day" returns a list of all distinct year/month/day values for the field.

order, which defaults to 'ASC', should be either 'ASC' or 'DESC'. This specifies how to order the results.

Examples:

>>> Entry.objects.dates('pub_date', 'year')
[datetime.datetime(2005, 1, 1)]
>>> Entry.objects.dates('pub_date', 'month')
[datetime.datetime(2005, 2, 1), datetime.datetime(2005, 3, 1)]
>>> Entry.objects.dates('pub_date', 'day')
[datetime.datetime(2005, 2, 20), datetime.datetime(2005, 3, 20)]
>>> Entry.objects.dates('pub_date', 'day', order='DESC')
[datetime.datetime(2005, 3, 20), datetime.datetime(2005, 2, 20)]
>>> Entry.objects.filter(headline__contains='Lennon').dates('pub_date', 'day')
[datetime.datetime(2005, 3, 20)]

none()

New in Django development version

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

Examples:

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

all()

New in Django development version

Returns a ‘’copy’’ of the current QuerySet (or QuerySet subclass you pass in). This can be useful in some situations where you might want to pass in either a model manager or a QuerySet and do further filtering on the result. You can safely call all() on either object and then you’ll definitely have a QuerySet to work with.

select_related()

Returns a QuerySet that will automatically “follow” foreign-key relationships, selecting that additional related-object data when it executes its query. This is a performance booster which results in (sometimes much) larger queries but means later use of foreign-key relationships won’t require database queries.

The following examples illustrate the difference between plain lookups and select_related() lookups. Here’s standard lookup:

# Hits the database.
e = Entry.objects.get(id=5)

# Hits the database again to get the related Blog object.
b = e.blog

And here’s select_related lookup:

# Hits the database.
e = Entry.objects.select_related().get(id=5)

# Doesn't hit the database, because e.blog has been prepopulated
# in the previous query.
b = e.blog

select_related() follows foreign keys as far as possible. If you have the following models:

class City(models.Model):
    # ...

class Person(models.Model):
    # ...
    hometown = models.ForeignKey(City)

class Book(models.Model):
    # ...
    author = models.ForeignKey(Person)

…then a call to Book.objects.select_related().get(id=4) will cache the related Person and the related City:

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

b = Book.objects.get(id=4) # No select_related() in this example.
p = b.author         # Hits the database.
c = p.hometown       # Hits the database.

Note that, by default, select_related() does not follow foreign keys that have null=True.

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

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

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

The depth argument is new in the Django development version.

New in Django development version: Sometimes you only need to access specific models that are related to your root model, not all of the related models. In these cases, you can pass the related field names to select_related() and it will only follow those relations. You can even do this for models that are more than one relation away by separating the field names with double underscores, just as for filters. For example, if we have this model:

class Room(models.Model):
    # ...
    building = models.ForeignKey(...)

class Group(models.Model):
    # ...
    teacher = models.ForeignKey(...)
    room = models.ForeignKey(Room)
    subject = models.ForeignKey(...)

…and we only needed to work with the room and subject attributes, we could write this:

g = Group.objects.select_related('room', 'subject')

This is also valid:

g = Group.objects.select_related('room__building', 'subject')

…and would also pull in the building relation.

You can only refer to ForeignKey relations in the list of fields passed to select_related. You can refer to foreign keys that have null=True (unlike the default select_related() call). It’s an error to use both a list of fields and the depth parameter in the same select_related() call, since they are conflicting options.

extra(select=None, where=None, params=None, tables=None, order_by=None, select_params=None)

Sometimes, the Django query syntax by itself can’t easily express a complex WHERE clause. For these edge cases, Django provides the extra() QuerySet modifier — a hook for injecting specific clauses into the SQL generated by a QuerySet.

By definition, these extra lookups may not be portable to different database engines (because you’re explicitly writing SQL code) and violate the DRY principle, so you should avoid them if possible.

Specify one or more of params, select, where or tables. None of the arguments is required, but you should use at least one of them.

select

The select argument lets you put extra fields in the SELECT clause. It should be a dictionary mapping attribute names to SQL clauses to use to calculate that attribute.

Example:

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

As a result, each Entry object will have an extra attribute, is_recent, a boolean representing whether the entry’s pub_date is greater than Jan. 1, 2006.

Django inserts the given SQL snippet directly into the SELECT statement, so the resulting SQL of the above example would be:

SELECT blog_entry.*, (pub_date > '2006-01-01')
FROM blog_entry;

The next example is more advanced; it does a subquery to give each resulting Blog object an entry_count attribute, an integer count of associated Entry objects:

Blog.objects.extra(
    select={
        'entry_count': 'SELECT COUNT(*) FROM blog_entry WHERE blog_entry.blog_id = blog_blog.id'
    },
)

(In this particular case, we’re exploiting the fact that the query will already contain the blog_blog table in its FROM clause.)

The resulting SQL of the above example would be:

SELECT blog_blog.*, (SELECT COUNT(*) FROM blog_entry WHERE blog_entry.blog_id = blog_blog.id)
FROM blog_blog;

Note that the parenthesis required by most database engines around subqueries are not required in Django’s select clauses. Also note that some database backends, such as some MySQL versions, don’t support subqueries.

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

This will work, for example:

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

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

where / tables

You can define explicit SQL WHERE clauses — perhaps to perform non-explicit joins — by using where. You can manually add tables to the SQL FROM clause by using tables.

where and tables both take a list of strings. All where parameters are “AND”ed to any other search criteria.

Example:

Entry.objects.extra(where=['id IN (3, 4, 5, 20)'])

…translates (roughly) into the following SQL:

SELECT * FROM blog_entry WHERE id IN (3, 4, 5, 20);

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

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

order_by

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

For example:

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

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

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

params

The where parameter described above may use standard Python database string placeholders — '%s' to indicate parameters the database engine should automatically quote. The params argument is a list of any extra parameters to be substituted.

Example:

Entry.objects.extra(where=['headline=%s'], params=['Lennon'])

Always use params instead of embedding values directly into where because params will ensure values are quoted correctly according to your particular backend. (For example, quotes will be escaped correctly.)

Bad:

Entry.objects.extra(where=["headline='Lennon'"])

Good:

Entry.objects.extra(where=['headline=%s'], params=['Lennon'])

New in Django development version The select_params argument to extra() is new. Previously, you could attempt to pass parameters for select in the params argument, but it worked very unreliably.

get(**kwargs)

Returns the object matching the given lookup parameters, which should be in the format described in Field lookups.

get() raises MultipleObjectsReturned if more than one object was found. The MultipleObjectsReturned exception is an attribute of the model class. For example, the following will raise MultipleObjectsReturned if there are more than one authors with the name of ‘John’:

Author.objects.get(name='John') # raises Author.MultipleObjectsReturned

get() raises a DoesNotExist exception if an object wasn’t found for the given parameters. The DoesNotExist exception is an attribute of the model class. Example:

Entry.objects.get(id='foo') # raises Entry.DoesNotExist

The DoesNotExist exception inherits from django.core.exceptions.ObjectDoesNotExist, so you can target multiple DoesNotExist exceptions. Example:

from django.core.exceptions import ObjectDoesNotExist
try:
    e = Entry.objects.get(id=3)
    b = Blog.objects.get(id=1)
except ObjectDoesNotExist:
    print "Either the entry or blog doesn't exist."

create(**kwargs)

A convenience method for creating an object and saving it all in one step. Thus:

p = Person.objects.create(first_name="Bruce", last_name="Springsteen")

and:

p = Person(first_name="Bruce", last_name="Springsteen")
p.save()

are equivalent.

get_or_create(**kwargs)

A convenience method for looking up an object with the given kwargs, creating one if necessary.

Returns a tuple of (object, created), where object is the retrieved or created object and created is a boolean specifying whether a new object was created.

This is meant as a shortcut to boilerplatish code and is mostly useful for data-import scripts. For example:

try:
    obj = Person.objects.get(first_name='John', last_name='Lennon')
except Person.DoesNotExist:
    obj = Person(first_name='John', last_name='Lennon', birthday=date(1940, 10, 9))
    obj.save()

This pattern gets quite unwieldy as the number of fields in a model goes up. The above example can be rewritten using get_or_create() like so:

obj, created = Person.objects.get_or_create(first_name='John', last_name='Lennon',
                  defaults={'birthday': date(1940, 10, 9)})

Any keyword arguments passed to get_or_create() — except an optional one called defaults — will be used in a get() call. If an object is found, get_or_create() returns a tuple of that object and False. If an object is not found, get_or_create() will instantiate and save a new object, returning a tuple of the new object and True. The new object will be created according to this algorithm:

defaults = kwargs.pop('defaults', {})
params = dict([(k, v) for k, v in kwargs.items() if '__' not in k])
params.update(defaults)
obj = self.model(**params)
obj.save()

In English, that means start with any non-'defaults' keyword argument that doesn’t contain a double underscore (which would indicate a non-exact lookup). Then add the contents of defaults, overriding any keys if necessary, and use the result as the keyword arguments to the model class.

If you have a field named defaults and want to use it as an exact lookup in get_or_create(), just use 'defaults__exact', like so:

Foo.objects.get_or_create(defaults__exact='bar', defaults={'defaults': 'baz'})

Finally, a word on using get_or_create() in Django views. As mentioned earlier, get_or_create() is mostly useful in scripts that need to parse data and create new records if existing ones aren’t available. But if you need to use get_or_create() in a view, please make sure to use it only in POST requests unless you have a good reason not to. GET requests shouldn’t have any effect on data; use POST whenever a request to a page has a side effect on your data. For more, see Safe methods in the HTTP spec.

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.

iterator()

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

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

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.

exact

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

Examples:

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

SQL equivalents:

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

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

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);

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

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

This queryset will be evaluated as subselect statement:

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

startswith

Case-sensitive starts-with.

Example:

Entry.objects.filter(headline__startswith='Will')

SQL equivalent:

SELECT ... WHERE headline LIKE 'Will%';

SQLite doesn’t support case-sensitive LIKE statements; startswith acts like istartswith for SQLite.

istartswith

Case-insensitive starts-with.

Example:

Entry.objects.filter(headline__istartswith='will')

SQL equivalent:

SELECT ... WHERE headline ILIKE 'Will%';

endswith

Case-sensitive ends-with.

Example:

Entry.objects.filter(headline__endswith='cats')

SQL equivalent:

SELECT ... WHERE headline LIKE '%cats';

SQLite doesn’t support case-sensitive LIKE statements; endswith acts like iendswith for SQLite.

iendswith

Case-insensitive ends-with.

Example:

Entry.objects.filter(headline__iendswith='will')

SQL equivalent:

SELECT ... WHERE headline ILIKE '%will'

range

Range test (inclusive).

Example:

start_date = datetime.date(2005, 1, 1)
end_date = datetime.date(2005, 3, 31)
Entry.objects.filter(pub_date__range=(start_date, end_date))

SQL equivalent:

SELECT ... WHERE pub_date BETWEEN '2005-01-01' and '2005-03-31';

You can use range anywhere you can use BETWEEN in SQL — for dates, numbers and even characters.

year

For date/datetime fields, exact year match. Takes a four-digit year.

Example:

Entry.objects.filter(pub_date__year=2005)

SQL equivalent:

SELECT ... WHERE EXTRACT('year' FROM pub_date) = '2005';

(The exact SQL syntax varies for each database engine.)

month

For date/datetime fields, exact month match. Takes an integer 1 (January) through 12 (December).

Example:

Entry.objects.filter(pub_date__month=12)

SQL equivalent:

SELECT ... WHERE EXTRACT('month' FROM pub_date) = '12';

(The exact SQL syntax varies for each database engine.)

day

For date/datetime fields, exact day match.

Example:

Entry.objects.filter(pub_date__day=3)

SQL equivalent:

SELECT ... WHERE EXTRACT('day' FROM pub_date) = '3';

(The exact SQL syntax varies for each database engine.)

Note this will match any record with a pub_date on the third day of the month, such as January 3, July 3, etc.

isnull

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

Example:

Entry.objects.filter(pub_date__isnull=True)

SQL equivalent:

SELECT ... WHERE pub_date IS NULL;

search

A boolean full-text search, taking advantage of full-text indexing. This is like contains but is significantly faster due to full-text indexing.

Note this is only available in MySQL and requires direct manipulation of the database to add the full-text index.

regex

New in Django development version

Case-sensitive regular expression match.

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

Example:

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

SQL equivalents:

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

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

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

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

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

iregex

New in Django development version

Case-insensitive regular expression match.

Example:

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

SQL equivalents:

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

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

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

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

Spanning multi-valued relationships

New in Django development version

When you are filtering an object based on a ManyToManyField or a reverse ForeignKeyField, there are two different sorts of filter you may be interested in. Consider the Blog/Entry relationship (Blog to Entry is a one-to-many relation). We might be interested in finding blogs that have an entry which has both “Lennon” in the headline and was published in 2008. Or we might want to find blogs that have an entry with “Lennon” in the headline as well as an entry that was published in 2008. Since there are multiple entries associated with a single Blog, both of these queries are possible and make sense in some situations.

The same type of situation arises with a ManyToManyField. For example, if an Entry has a ManyToManyField called tags, we might want to find entries linked to tags called “music” and “bands” or we might want an entry that contains a tag with a name of “music” and a status of “public”.

To handle both of these situations, Django has a consistent way of processing filter() and exclude() calls. Everything inside a single filter() call is applied simultaneously to filter out items matching all those requirements. Successive filter() calls further restrict the set of objects, but for multi-valued relations, they apply to any object linked to the primary model, not necessarily those objects that were selected by an earlier filter() call.

That may sound a bit confusing, so hopefully an example will clarify. To select all blogs that contains entries with “Lennon” in the headline and were published in 2008, 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.

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.

select_related() is documented in the QuerySet methods that return new QuerySets section above.

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. Example:

Blog.entry_set # Raises AttributeError: "Manager must be accessed via instance".

In addition to the QuerySet methods defined in “Retrieving objects” above, the ForeignKey Manager has these additional methods:

• add(obj1, obj2, ...): Adds the specified model objects to the related object set.

  Example:

  b = Blog.objects.get(id=1)
  e = Entry.objects.get(id=234)
  b.entry_set.add(e) # Associates Entry e with Blog b.
  

• create(**kwargs): Creates a new object, saves it and puts it in the related object set. Returns the newly created object.

  Example:

  b = Blog.objects.get(id=1)
  e = b.entry_set.create(headline='Hello', body_text='Hi', pub_date=datetime.date(2005, 1, 1))
  # No need to call e.save() at this point -- it's already been saved.
  

  This is equivalent to (but much simpler than):

  b = Blog.objects.get(id=1)
  e = Entry(blog=b, headline='Hello', body_text='Hi', pub_date=datetime.date(2005, 1, 1))
  e.save()
  

  Note that there’s no need to specify the keyword argument of the model that defines the relationship. In the above example, we don’t pass the parameter blog to create(). Django figures out that the new Entry object’s blog field should be set to b.

• remove(obj1, obj2, ...): Removes the specified model objects from the related object set.

  Example:

  b = Blog.objects.get(id=1)
  e = Entry.objects.get(id=234)
  b.entry_set.remove(e) # Disassociates Entry e from Blog b.
  

  In order to prevent database inconsistency, this method only exists on ForeignKey objects where null=True. If the related field can’t be set to None (NULL), then an object can’t be removed from a relation without being added to another. In the above example, removing e from b.entry_set() is equivalent to doing e.blog = None, and because the blog ForeignKey doesn’t have null=True, this is invalid.

• clear(): Removes all objects from the related object set.

  Example:

  b = Blog.objects.get(id=1)
  b.entry_set.clear()
  

  Note this doesn’t delete the related objects — it just disassociates them.

  Just like remove(), clear() is only available on ForeignKey``s where ``null=True.

To assign the members of a related set in one fell swoop, just assign to it from any iterable object. Example:

b = Blog.objects.get(id=1)
b.entry_set = [e1, e2]

If the clear() method is available, any pre-existing objects will be removed from the entry_set before all objects in the iterable (in this case, a list) are added to the set. If the clear() method is not available, all objects in the iterable will be added without removing any existing elements.

Each “reverse” operation des