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magic-removal: Fixed section titles in docs/db-api.txt to uncapitalize words, to match our style

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git-svn-id: http://code.djangoproject.com/svn/django/branches/magic-removal@2741 bcc190cf-cafb-0310-a4f2-bffc1f526a37
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Adrian Holovaty 2006-04-23 23:22:42 +00:00
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docs/db-api.txt
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@ -15,7 +15,7 @@ Throughout this reference, we'll refer to the following Poll application::
question = models.CharField(maxlength=255)
pub_date = models.DateTimeField()
expire_date = models.DateTimeField()
def __repr__(self):
return self.question
@ -43,65 +43,65 @@ and the following Django sample session::
>>> Poll.objects.all()
[What's up?, What's your name?]
How Queries Work
How queries work
================
Querying in Django is based upon the construction and evaluation of Query
Sets.
Querying in Django is based upon the construction and evaluation of Query
Sets.
A Query Set is a database-independent representation of a group of objects
that all meet a given set of criteria. However, the determination of which
A Query Set is a database-independent representation of a group of objects
that all meet a given set of criteria. However, the determination of which
objects are actually members of the Query Set is not made until you formally
evaluate the Query Set.
To construct a Query Set that meets your requirements, you start by obtaining
an initial Query Set that describes all objects of a given type. This initial
Query Set can then be refined using a range of operations. Once you have
refined your Query Set to the point where it describes the group of objects
you require, it can be evaluated (using iterators, slicing, or one of a range
of other techniques), yielding an object or list of objects that meet the
an initial Query Set that describes all objects of a given type. This initial
Query Set can then be refined using a range of operations. Once you have
refined your Query Set to the point where it describes the group of objects
you require, it can be evaluated (using iterators, slicing, or one of a range
of other techniques), yielding an object or list of objects that meet the
specifications of the Query Set.
Obtaining an Initial Query Set
==============================
Obtaining an initial QuerySet
=============================
Every model has at least one Manager; by default, the Manager is called
``objects``. One of the most important roles of the Manager is as a source
of initial Query Sets. The Manager acts as a Query Set that describes all
objects of the type being managed; ``Polls.objects`` is the initial Query Set
Every model has at least one Manager; by default, the Manager is called
``objects``. One of the most important roles of the Manager is as a source
of initial Query Sets. The Manager acts as a Query Set that describes all
objects of the type being managed; ``Polls.objects`` is the initial Query Set
that contains all Polls in the database.
The initial Query Set on the Manager behaves in the same way as every other
Query Set in every respect except one - it cannot be evaluated. To overcome
The initial Query Set on the Manager behaves in the same way as every other
Query Set in every respect except one - it cannot be evaluated. To overcome
this limitation, the Manager Query Set has an ``all()`` method. The ``all()``
method produces a copy of the initial Query Set - a copy that *can* be
method produces a copy of the initial Query Set - a copy that *can* be
evaluated::
all_polls = Poll.objects.all()
See the `Managers`_ section of the Model API for more details on the role
See the `Managers`_ section of the Model API for more details on the role
and construction of Managers.
.. _Managers: http://www.djangoproject.com/documentation/model_api/#managers
Query Set Refinement
====================
QuerySet refinement
===================
The initial Query Set provided by the Manager describes all objects of a
given type. However, you will usually need to describe a subset of the
complete set of objects.
The initial Query Set provided by the Manager describes all objects of a
given type. However, you will usually need to describe a subset of the
complete set of objects.
To create such a subset, you refine the initial Query Set, adding conditions
until you have described a set that meets your needs. The two most common
until you have described a set that meets your needs. The two most common
mechanisms for refining a Query Set are:
``filter(**kwargs)``
Returns a new Query Set containing objects that match the given lookup parameters.
Returns a new Query Set containing objects that match the given lookup parameters.
``exclude(**kwargs)``
Return a new Query Set containing objects that do not match the given lookup parameters.
Lookup parameters should be in the format described in "Field lookups" below.
Lookup parameters should be in the format described in "Field lookups" below.
The result of refining a Query Set is itself a Query Set; so it is possible to
chain refinements together. For example::
@ -111,27 +111,27 @@ chain refinements together. For example::
pub_date__gte=datetime.now()).filter(
pub_date__gte=datetime(2005,1,1))
...takes the initial Query Set, and adds a filter, then an exclusion, then
another filter to remove elements present in the initial Query Set. The
final result is a Query Set containing all Polls with a question that
...takes the initial Query Set, and adds a filter, then an exclusion, then
another filter to remove elements present in the initial Query Set. The
final result is a Query Set containing all Polls with a question that
starts with "What", that were published between 1 Jan 2005 and today.
Each Query Set is a unique object. The process of refinement is not one
of adding a condition to the initial Query Set. Rather, each refinement
creates a separate and distinct Query Set that can be stored, used. and
of adding a condition to the initial Query Set. Rather, each refinement
creates a separate and distinct Query Set that can be stored, used. and
reused. For example::
q1 = Poll.objects.filter(question__startswith="What")
q2 = q1.exclude(pub_date__gte=datetime.now())
q3 = q1.filter(pub_date__gte=datetime.now())
will construct 3 Query Sets; a base query set containing all Polls with a
will construct 3 Query Sets; a base query set containing all Polls with a
question that starts with "What", and two subsets of the base Query Set (one
with an exlusion, one with a filter). The initial Query Set is unaffected by
with an exlusion, one with a filter). The initial Query Set is unaffected by
the refinement process.
It should be noted that the construction of a Query Set does not involve any
activity on the database. The database is not consulted until a Query Set is
activity on the database. The database is not consulted until a Query Set is
evaluated.
Field lookups
@ -200,7 +200,7 @@ two statements are equivalent::
Poll.objects.get(id=14)
Poll.objects.get(id__exact=14)
Multiple lookup parameters are allowed. When separated by commans, the list of
Multiple lookup parameters are allowed. When separated by commans, the list of
lookup parameters will be "AND"ed together::
Poll.objects.filter(
@ -209,7 +209,7 @@ lookup parameters will be "AND"ed together::
question__startswith="Would",
)
...retrieves all polls published in January 2005 that have a question starting
...retrieves all polls published in January 2005 that have a question starting
with "Would."
For convenience, there's a ``pk`` lookup type, which translates into
@ -232,33 +232,33 @@ If you pass an invalid keyword argument, the function will raise ``TypeError``.
OR lookups
==========
Keyword argument queries are "AND"ed together. If you have more
complex query requirements (for example, you need to include an ``OR``
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()
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
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
... 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
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
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(
@ -271,10 +271,10 @@ function, they will be "AND"ed together. For example::
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
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(
@ -303,10 +303,10 @@ See the `OR lookups examples page`_ for more examples.
.. _OR lookups examples page: http://www.djangoproject.com/documentation/models/or_lookups/
Query Set evaluation
====================
QuerySet evaluation
===================
A Query Set must be evaluated to return the objects that are contained in the
A Query Set must be evaluated to return the objects that are contained in the
set. This can be achieved by iteration, slicing, or by specialist function.
A Query Set is an iterable object. Therefore, it can be used in loop
@ -314,16 +314,16 @@ constructs. For example::
for p in Poll.objects.all():
print p
will print all the Poll objects, using the ``__repr__()`` method of Poll.
A Query Set can also be sliced, using array notation::
fifth_poll = Poll.objects.all()[4]
all_polls_but_the_first_two = Poll.objects.all()[2:]
every_second_poll = Poll.objects.all()[::2]
Query Sets are lazy objects - that is, they are not *actually* sets (or
Query Sets are lazy objects - that is, they are not *actually* sets (or
lists) that contain all the objects that they represent. Python protocol
magic is used to make the Query Set *look* like an iterable, sliceable
object, but behind the scenes, Django is using caching to only instantiate
@ -337,16 +337,16 @@ lazy object::
However - be warned; this could have a large memory overhead, as Django will
create an in-memory representation of every element of the list.
Caching and Query Sets
======================
Caching and QuerySets
=====================
Each Query Set contains a cache. In a newly created Query Set, this cache
is unpopulated. When a Query Set is evaluated for the first time, Django
makes a database query to populate the cache, and then returns the results
that have been explicitly requested (e.g., the next element if iteration
Each Query Set contains a cache. In a newly created Query Set, this cache
is unpopulated. When a Query Set is evaluated for the first time, Django
makes a database query to populate the cache, and then returns the results
that have been explicitly requested (e.g., the next element if iteration
is in use). Subsequent evaluations of the Query Set reuse the cached results.
This caching behavior must be kept in mind when using Query Sets. For
This caching behavior must be kept in mind when using Query Sets. For
example, the following will cause two temporary Query Sets to be created,
evaluated, and thrown away::
@ -354,10 +354,10 @@ evaluated, and thrown away::
print [p for p in Poll.objects.all()] # Evaluate the Query Set again
On a small, low-traffic website, this may not pose a serious problem. However,
on a high traffic website, it effectively doubles your database load. In
addition, there is a possibility that the two lists may not be identical,
since a poll may be added or deleted by another user between making the two
requests.
on a high traffic website, it effectively doubles your database load. In
addition, there is a possibility that the two lists may not be identical,
since a poll may be added or deleted by another user between making the two
requests.
To avoid this problem, simply save the Query Set and reuse it::
@ -365,12 +365,12 @@ To avoid this problem, simply save the Query Set and reuse it::
print [p for p in queryset] # Evaluate the query set
print [p for p in queryset] # Re-use the cache from the evaluation
Specialist Query Set Evaluation
===============================
Specialist QuerySet evaluation
==============================
The following specialist functions can also be used to evaluate a Query Set.
Unlike iteration or slicing, these methods do not populate the cache; each
time one of these evaluation functions is used, the database will be queried.
The following specialist functions can also be used to evaluate a Query Set.
Unlike iteration or slicing, these methods do not populate the cache; each
time one of these evaluation functions is used, the database will be queried.
``get(**kwargs)``
-----------------
@ -409,48 +409,48 @@ Returns the latest object, according to the model's 'get_latest_by'
Meta option, or using the field_name provided. For example::
>>> Poll.objects.latest()
What's up?
What's up?
>>> Poll.objects.latest('expire_date')
What's your name?
Relationships (joins)
=====================
When you define a relationship in a model (i.e., a ForeignKey,
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
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,
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
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
Single object descriptor
------------------------
If the related object is a single object, the descriptor acts
@ -463,16 +463,16 @@ just as if the related object were an attribute::
# Save the change
mychoice.save()
Whenever a change is made to a Single Object Descriptor, 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
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
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
@ -480,54 +480,54 @@ a field::
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
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
queried, and the result stored. Subsequent attempts to access
the descriptor on the same instance will use the cached value.
Object Set Descriptor
Object set descriptor
---------------------
An Object Set Descriptor acts just like the Manager - as an initial Query
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
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``
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
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.
Add the specified objects to the related object set.
``create(\**kwargs)``
Create a new object, and put it in the related object set. See
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.
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``
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.
from one relation without adding it to another.
The members of a related object set can be assigned from any iterable object.
For example::
@ -535,49 +535,49 @@ 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.
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.
automatically saved to the database.
Relationships and Queries
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
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
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
... 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.
Specialist Query Sets Refinement
================================
Specialist QuerySets refinement
===============================
In addition to ``filter`` and ``exclude()``, Django provides a range of
Query Set refinement methods that modify the types of results returned by
In addition to ``filter`` and ``exclude()``, Django provides a range of
Query Set refinement methods that modify the types of results returned by
the Query Set, or modify the way the SQL query is executed on the database.
``order_by(*fields)``
----------------------
The results returned by a Query Set are automatically ordered by the ordering
tuple given by the ``ordering`` meta key in the model. However, ordering may be
The results returned by a Query Set are automatically ordered by the ordering
tuple given by the ``ordering`` meta key in the model. However, ordering may be
explicitly provided by using the ``order_by`` method::
Poll.objects.filter(pub_date__year=2005,
Poll.objects.filter(pub_date__year=2005,
pub_date__month=1).order_by('-pub_date', 'question')
The result set above will be ordered by ``pub_date`` descending, then
@ -599,21 +599,21 @@ backend normally orders them.
``distinct()``
--------------
By default, a Query Set will not eliminate duplicate rows. This will not
By default, a Query Set will not eliminate duplicate rows. This will not
happen during simple queries; however, if your query spans relations,
or you are using a Values Query Set with a ``fields`` clause, it is possible
to get duplicated results when a Query Set is evaluated.
to get duplicated results when a Query Set is evaluated.
``distinct()`` returns a new Query Set that eliminates duplicate rows from the
results returned by the Query Set. This is equivalent to a ``SELECT DISTINCT``
SQL clause.
results returned by the Query Set. This is equivalent to a ``SELECT DISTINCT``
SQL clause.
``values(*fields)``
--------------------
Returns a Values Query Set - a Query Set that evaluates to a list of
dictionaries instead of model-instance objects. Each dictionary in the
list will represent an object matching the query, with the keys matching
Returns a Values Query Set - a Query Set that evaluates to a list of
dictionaries instead of model-instance objects. Each dictionary in the
list will represent an object matching the query, with the keys matching
the attribute names of the object.
It accepts an optional parameter, ``fields``, which should be a list or tuple
@ -623,25 +623,25 @@ database table. If you specify ``fields``, each dictionary will have only the
field keys/values for the fields you specify. For example::
>>> Poll.objects.values()
[{'id': 1, 'slug': 'whatsup', 'question': "What's up?",
'pub_date': datetime.datetime(2005, 2, 20),
[{'id': 1, 'slug': 'whatsup', 'question': "What's up?",
'pub_date': datetime.datetime(2005, 2, 20),
'expire_date': datetime.datetime(2005, 3, 20)},
{'id': 2, 'slug': 'name', 'question': "What's your name?",
'pub_date': datetime.datetime(2005, 3, 20),
{'id': 2, 'slug': 'name', 'question': "What's your name?",
'pub_date': datetime.datetime(2005, 3, 20),
'expire_date': datetime.datetime(2005, 4, 20)}]
>>> Poll.objects.values('id', 'slug')
[{'id': 1, 'slug': 'whatsup'}, {'id': 2, 'slug': 'name'}]
A Values Query Set 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
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.
``dates(field, kind, order='ASC')``
-----------------------------------
Returns a Date Query Set - a Query Set that evaluates to a list of
``datetime.datetime`` objects representing all available dates of a
Returns a Date Query Set - a Query Set that evaluates to a list of
``datetime.datetime`` objects representing all available dates of a
particular kind within the contents of the Query Set.
``field`` should be the name of a ``DateField`` or ``DateTimeField`` of your
@ -719,8 +719,8 @@ Sometimes, the Django query syntax by itself isn't quite enough. To cater for th
edge cases, Django provides the ``extra()`` Query Set modifier - a mechanism
for injecting specific clauses into the SQL generated by a Query Set.
Note that by definition these extra lookups may not be portable to different
database engines (because you're explicitly writing SQL code) and should be
Note that by definition these extra lookups may not be portable to different
database engines (because you're explicitly writing SQL code) and should be
avoided if possible.:
``params``
@ -827,7 +827,7 @@ 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.
``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::
@ -856,7 +856,7 @@ key field is called ``name``, these two statements are equivalent::
Extra instance methods
======================
In addition to ``save()``, ``delete()``, a model object might get any or all
In addition to ``save()``, ``delete()``, a model object might get any or all
of the following methods:
get_FOO_display()
@ -942,4 +942,3 @@ 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.