Explicitly specifying auto-primary-key values

Example:

b3.id     # Returns 3.
b3.save()
b3.id     # Returns 3.

Given the above 'Cheddar Talk' blog example, this example would override the previous record in the database:

b4.save()  # Overrides the previous blog with ID=3!

Explicitly specifying auto-primary-key values is mostly useful for bulk-saving objects, when you're confident you won't have primary-key collision.

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.
  需要注意的是：不要在结果集上执行len()，那样比较消耗资源，如果需要，可以使用count()。
  



• 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.
  

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. order_by可以有多个排序字段，要对字段降序排列，在字段前加－。

To order randomly, use "?", like so:
要随即排序，使用问号？

Entry.objects.order_by('?')

To order by a field in a different table, add the other table's name and a dot, like so:
要在排序中使用其他表，可以使用“表名.字段名”形式

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.
不能指定使用大小写字符排序

distinct()
唯一性

Returns a new QuerySet that uses SELECT DISTINCT in its SQL query. This eliminates duplicate rows from the query results.可以返回不重复的记录集结果。

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')
？不太明白该过滤器的效果

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(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.

sv = 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 select_related() does not follow foreign keys that have null=True.

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'])

get(**kwargs)

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

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:

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.

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.

 />>> Blog.objects.in_bulk([1])
{1: Beatles Blog}
 />>> Blog.objects.in_bulk([1, 2])
{1: Beatles Blog, 2: Cheddar Talk}
 />>> Blog.objects.in_bulk([])
{}

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 = NULL;

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

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.

Lookups that span relationships

Django offers a powerful and intuitive way to "follow" relationships in lookups, taking care of the SQL JOINs for you automatically, behind the scenes. To span a relationship, just use the field name of related fields across models, separated by double underscores, until you get to the field you want.

This example retrieves all Entry objects with a Blog whose name is 'Beatles Blog':

Entry.objects.filter(blog__name__exact='Beatles Blog')

This spanning can be as deep as you'd like.

It works backwards, too. To refer to a "reverse" relationship, just use the lowercase name of the model.

This example retrieves all Blog objects which have at least one Entry whose headline contains 'Lennon':

Blog.objects.filter(entry__headline__contains='Lennon')

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.

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 described in this section has an immediate effect on the database. Every addition, creation and deletion is immediately and automatically saved to the database.