|
Posted on 2006-12-10 20:44 pts 阅读(1383) 评论(0) 编辑 收藏 所属分类: Django
Database API reference
This covers Django version 0.95 and the development version. Old docs: 0.90, 0.91Once you've created your data models, Django automatically gives you a database-abstraction API that lets you create, retrieve, update and delete objects. This document explains that API. Throughout this reference, we'll refer to the following models, which comprise a weblog application: class Blog(models.Model): name = models.CharField(maxlength=100) tagline = models.TextField()
def __str__(self): return self.name
class Author(models.Model): name = models.CharField(maxlength=50) email = models.URLField()
def __str__(self): return self.name
class Entry(models.Model): blog = models.ForeignKey(Blog) headline = models.CharField(maxlength=255) body_text = models.TextField() pub_date = models.DateTimeField() authors = models.ManyToManyField(Author)
def __str__(self): return self.headline
Creating objects To represent database-table data in Python objects, Django uses an intuitive system: A model class represents a database table, and an instance of that class represents a particular record in the database table. To create an object, instantiate it using keyword arguments to the model class, then call save() to save it to the database. You import the model class from wherever it lives on the Python path, as you may expect. (We point this out here because previous Django versions required funky model importing.) Assuming models live in a file mysite/blog/models.py, here's an example: from mysite.blog.models import Blog b = Blog(name='Beatles Blog', tagline='All the latest Beatles news.') b.save()
This performs an INSERT SQL statement behind the scenes. Django doesn't hit the database until you explicitly call save(). The save() method has no return value. To create an object and save it all in one step see the create method.
Auto-incrementing primary keysIf a model has an AutoField -- an auto-incrementing primary key -- then that auto-incremented value will be calculated and saved as an attribute on your object the first time you call save(). Example: b2 = Blog(name='Cheddar Talk', tagline='Thoughts on cheese.') b2.id # Returns None, because b doesn't have an ID yet. b2.save() b2.id # Returns the ID of your new object.
There's no way to tell what the value of an ID will be before you call save(), because that value is calculated by your database, not by Django. (For convenience, each model has an AutoField named id by default unless you explicitly specify primary_key=True on a field. See the AutoField documentation.)
Explicitly specifying auto-primary-key valuesIf a model has an AutoField but you want to define a new object's ID explicitly when saving, just define it explicitly before saving, rather than relying on the auto-assignment of the ID. Example: b3 = Blog(id=3, name='Cheddar Talk', tagline='Thoughts on cheese.') b3.id # Returns 3. b3.save() b3.id # Returns 3.
If you assign auto-primary-key values manually, make sure not to use an already-existing primary-key value! If you create a new object with an explicit primary-key value that already exists in the database, Django will assume you're changing the existing record rather than creating a new one. Given the above 'Cheddar Talk' blog example, this example would override the previous record in the database: b4 = Blog(id=3, name='Not Cheddar', tagline='Anything but cheese.') b4.save() # Overrides the previous blog with ID=3!
See How Django knows to UPDATE vs. INSERT, below, for the reason this happens. Explicitly specifying auto-primary-key values is mostly useful for bulk-saving objects, when you're confident you won't have primary-key collision.
Saving changes to objectsTo save changes to an object that's already in the database, use save(). Given a Blog instance b5 that has already been saved to the database, this example changes its name and updates its record in the database: b5.name = 'New name' b5.save() This performs an UPDATE SQL statement behind the scenes. Django doesn't hit the database until you explicitly call save(). The save() method has no return value.
How Django knows to UPDATE vs. INSERT django怎么判断是更新或是新增记录?
You may have noticed Django database objects use the same save() method for creating and changing objects. Django abstracts the need to use INSERT or UPDATE SQL statements. Specifically, when you call save(), Django follows this algorithm:
- If the object's primary key attribute is set to a value that evaluates to False (such as None or the empty string), Django executes a SELECT query to determine whether a record with the given primary key already exists.
首先Django会先在数据库中查找对象的主键是否已存在
- If the record with the given primary key does already exist, Django executes an UPDATE query.
如果对象已经在数据库中存在,Django会执行更新操作
- If the object's primary key attribute is not set, or if it's set but a record doesn't exist, Django executes an INSERT.
如果对象的主键在数据库中不存在,Django会执行插入操作
The one gotcha here is that you should be careful not to specify a primary-key value explicitly when saving new objects, if you cannot guarantee the primary-key value is unused. For more on this nuance, see "Explicitly specifying auto-primary-key values" above.
Retrieving objects
To retrieve objects from your database, you construct a QuerySet via a Manager on your model class.
A QuerySet represents a collection of objects from your database. It can have zero, one or many filters -- criteria that narrow down the collection based on given parameters. In SQL terms, a QuerySet equates to a SELECT statement, and a filter is a limiting clause such as WHERE or LIMIT.
You get a QuerySet by using your model's Manager. Each model has at least one Manager, and it's called objects by default. Access it directly via the model class, like so:
Blog.objects # b = Blog(name='Foo', tagline='Bar') b.objects # AttributeError: "Manager isn't accessible via Blog instances."
(Managers are accessible only via model classes, rather than from model instances, to enforce a separation between "table-level" operations and "record-level" operations.)
The Manager is the main source of QuerySets for a model. It acts as a "root" QuerySet that describes all objects in the model's database table. For example, Blog.objects is the initial QuerySet that contains all Blog objects in the database.
Retrieving all objects
The simplest way to retrieve objects from a table is to get all of them. To do this, use the all() method on a Manager.
Example:
all_entries = Entry.objects.all()
The all() method returns a QuerySet of all the objects in the database.
(If Entry.objects is a QuerySet, why can't we just do Entry.objects? That's because Entry.objects, the root QuerySet, is a special case that cannot be evaluated. The all() method returns a QuerySet that can be evaluated.)
Filtering objects
The root QuerySet provided by the Manager describes all objects in the database table. Usually, though, you'll need to select only a subset of the complete set of objects.
To create such a subset, you refine the initial QuerySet, adding filter conditions. The two most common ways to refine a QuerySet are:
- filter(**kwargs)
- 过滤操作
- Returns a new QuerySet containing objects that match the given lookup parameters.
- exclude(**kwargs)
- 排除操作
- Returns a new QuerySet containing objects that do not match the given lookup parameters.
The lookup parameters (**kwargs in the above function definitions) should be in the format described in Field lookups below.
For example, to get a QuerySet of blog entries from the year 2006, use filter() like so:
Entry.objects.filter(pub_date__year=2006)
(Note we don't have to add an all() -- Entry.objects.all().filter(...). That would still work, but you only need all() when you want all objects from the root QuerySet.)
Chaining filters
The result of refining a QuerySet is itself a QuerySet, so it's possible to chain refinements together. For example:
Entry.objects.filter( headline__startswith='What').exclude( pub_date__gte=datetime.now()).filter( pub_date__gte=datetime(2005, 1, 1))
...takes the initial QuerySet of all entries in the database, adds a filter, then an exclusion, then another filter. The final result is a QuerySet containing all entries with a headline that starts with "What", that were published between January 1, 2005, and the current day.
Filtered QuerySets are unique
Each time you refine a QuerySet, you get a brand-new QuerySet that is in no way bound to the previous QuerySet. Each refinement creates a separate and distinct QuerySet that can be stored, used and reused. Example:
q1 = Entry.objects.filter(headline__startswith="What") q2 = q1.exclude(pub_date__gte=datetime.now()) q3 = q1.filter(pub_date__gte=datetime.now())
These three QuerySets are separate. The first is a base QuerySet containing all entries that contain a headline starting with "What". The second is a subset of the first, with an additional criteria that excludes records whose pub_date is greater than now. The third is a subset of the first, with an additional criteria that selects only the records whose pub_date is greater than now. The initial QuerySet (q1) is unaffected by the refinement process.
QuerySets are lazy
QuerySets are lazy -- the act of creating a QuerySet doesn't involve any database activity. You can stack filters together all day long, and Django won't actually run the query until the QuerySet is evaluated.
When QuerySets are evaluated
You can evaluate a QuerySet in the following ways:
- Iteration. A QuerySet is iterable, and it executes its database query the first time you iterate over it. For example, this will print the headline of all entries in the database:
for e in Entry.objects.all(): print e.headline
- Slicing. 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.
Limiting QuerySets
Use Python's array-slicing syntax to limit your QuerySet to a certain number of results. This is the equivalent of SQL's LIMIT and OFFSET clauses.
For example, this returns the first 5 objects (LIMIT 5):
Entry.objects.all()[:5]
This returns the fifth through tenth objects (OFFSET 5 LIMIT 5):
Entry.objects.all()[5:10]
Generally, slicing a QuerySet returns a new QuerySet -- it doesn't evaluate the query. An exception is if you use the "step" parameter of Python slice syntax. For example, this would actually execute the query in order to return a list of every second object of the first 10:
Entry.objects.all()[:10:2]
To retrieve a single object rather than a list (e.g. SELECT foo FROM bar LIMIT 1), use a simple index instead of a slice. For example, this returns the first Entry in the database, after ordering entries alphabetically by headline:
Entry.objects.order_by('headline')[0]
This is roughly equivalent to:
Entry.objects.order_by('headline')[0:1].get()
Note, however, that the first of these will raise IndexError while the second will raise DoesNotExist if no objects match the given criteria.
!不能使用objects.all()[4:]
QuerySet methods that return new QuerySets
Django provides a range of QuerySet refinement methods that modify either the types of results returned by the QuerySet or the way its SQL query is executed.
filter(**kwargs)
Returns a new QuerySet containing objects that match the given lookup parameters.
The lookup parameters (**kwargs) should be in the format described in Field lookups below. Multiple parameters are joined via AND in the underlying SQL statement.
exclude(**kwargs)
Returns a new QuerySet containing objects that do not match the given lookup parameters.
The lookup parameters (**kwargs) should be in the format described in Field lookups below. Multiple parameters are joined via AND in the underlying SQL statement, and the whole thing is enclosed in a NOT().
This example excludes all entries whose pub_date is the current date/time AND whose headline is "Hello":
Entry.objects.exclude(pub_date__gt=datetime.date(2005, 1, 3), headline='Hello')
In SQL terms, that evaluates to:
SELECT ... WHERE NOT (pub_date > '2005-1-3' AND headline = 'Hello')
This example excludes all entries whose pub_date is the current date/time OR whose headline is "Hello":
Entry.objects.exclude(pub_date__gt=datetime.date(2005, 1, 3)).exclude(headline='Hello')
In SQL terms, that evaluates to:
SELECT ... WHERE NOT pub_date > '2005-1-3' AND NOT headline = 'Hello'
Note the second example is more restrictive.
order_by(*fields)
By default, results returned by a QuerySet are ordered by the ordering tuple given by the ordering option in the model's Meta. You can override this on a per-QuerySet basis by using the order_by method.
Example:
Entry.objects.filter(pub_date__year=2005).order_by('-pub_date', 'headline')
The result above will be ordered by pub_date descending, then by headline ascending. The negative sign in front of "-pub_date" indicates descending order. Ascending order is implied. 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)]
QuerySet methods that do not return QuerySets
The following QuerySet methods evaluate the QuerySet and return something other than a QuerySet.
These methods do not use a cache (see Caching and QuerySets below). Rather, they query the database each time they're called.
get(**kwargs)
Returns the object matching the given lookup parameters, which should be in the format described in Field lookups. get() raises AssertionError if more than one object was found. get() raises a DoesNotExist exception if an object wasn't found for the given parameters. The DoesNotExist exception is an attribute of the model class. Example: Entry.objects.get(id='foo') # raises Entry.DoesNotExist The DoesNotExist exception inherits from django.core.exceptions.ObjectDoesNotExist, so you can target multiple DoesNotExist exceptions. Example: from django.core.exceptions import ObjectDoesNotExist try: e = Entry.objects.get(id=3) b = Blog.objects.get(id=1) except ObjectDoesNotExist: print "Either the entry or blog doesn't exist."
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. latest(field_name=None)Returns the latest object in the table, by date, using the field_name provided as the date field. This example returns the latest Entry in the table, according to the pub_date field:
Entry.objects.latest('pub_date')
If your model's Meta specifies get_latest_by, you can leave off the field_name argument to latest(). Django will use the field specified in get_latest_by by default.
Like get(), latest() raises DoesNotExist if an object doesn't exist with the given parameters.
Note latest() exists purely for convenience and readability.
Field lookups
Field lookups are how you specify the meat of an SQL WHERE clause. They're specified as keyword arguments to the QuerySet methods filter(), exclude() and get().
Basic lookups keyword arguments take the form field__lookuptype=value. (That's a double-underscore). For example: Entry.objects.filter(pub_date__lte='2006-01-01') translates (roughly) into the following SQL:
SELECT * FROM blog_entry WHERE pub_date <= '2006-01-01';
How this is possible
Python has the ability to define functions that accept arbitrary name-value arguments whose names and values are evaluated at runtime. For more information, see Keyword Arguments in the official Python tutorial.
If you pass an invalid keyword argument, a lookup function will raise TypeError.
The database API supports the following lookup types:
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.
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. iendswithCase-insensitive ends-with. Example: Entry.objects.filter(headline__iendswith='will')
SQL equivalent: SELECT ... WHERE headline ILIKE '%will'
rangeRange 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. yearFor 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.) monthFor 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.) dayFor 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. isnullTakes 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;
__isnull=True vs __exact=None There is an important difference between __isnull=True and __exact=None. __exact=None will always return an empty result set, because SQL requires that no value is equal to NULL. __isnull determines if the field is currently holding the value of NULL without performing a comparison. searchA 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. Default lookups are exactIf you don't provide a lookup type -- that is, if your keyword argument doesn't contain a double underscore -- the lookup type is assumed to be exact. For example, the following two statements are equivalent: Blog.objects.get(id__exact=14) # Explicit form Blog.objects.get(id=14) # __exact is implied
This is for convenience, because exact lookups are the common case. The pk lookup shortcutFor convenience, Django provides a pk lookup type, which stands for "primary_key". In the example Blog model, the primary key is the id field, so these three statements are equivalent: Blog.objects.get(id__exact=14) # Explicit form Blog.objects.get(id=14) # __exact is implied Blog.objects.get(pk=14) # pk implies id__exact
The use of pk isn't limited to __exact queries -- any query term can be combined with pk to perform a query on the primary key of a model: # Get blogs entries with id 1, 4 and 7 Blog.objects.filter(pk__in=[1,4,7]) # Get all blog entries with id > 14 Blog.objects.filter(pk__gt=14)
pk lookups also work across joins. For example, these three statements are equivalent: Entry.objects.filter(blog__id__exact=3) # Explicit form Entry.objects.filter(blog__id=3) # __exact is implied Entry.objects.filter(blog__pk=3) # __pk implies __id__exact
Lookups that span relationshipsDjango 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 statementsThe field lookups that equate to LIKE SQL statements (iexact, contains, icontains, startswith, istartswith, endswith and iendswith) will automatically escape the two special characters used in LIKE statements -- the percent sign and the underscore. (In a LIKE statement, the percent sign signifies a multiple-character wildcard and the underscore signifies a single-character wildcard.) This means things should work intuitively, so the abstraction doesn't leak. For example, to retrieve all the entries that contain a percent sign, just use the percent sign as any other character: Entry.objects.filter(headline__contains='%')
Django takes care of the quoting for you; the resulting SQL will look something like this: SELECT ... WHERE headline LIKE '%\%%';
Same goes for underscores. Both percentage signs and underscores are handled for you transparently. Caching and QuerySetsEach QuerySet contains a cache, to minimize database access. It's important to understand how it works, in order to write the most efficient code. In a newly created QuerySet, the cache is empty. The first time a QuerySet is evaluated -- and, hence, a database query happens -- Django saves the query results in the QuerySet's cache and returns the results that have been explicitly requested (e.g., the next element, if the QuerySet is being iterated over). Subsequent evaluations of the QuerySet reuse the cached results. Keep this caching behavior in mind, because it may bite you if you don't use your QuerySets correctly. For example, the following will create two QuerySets, evaluate them, and throw them away: print [e.headline for e in Entry.objects.all()] print [e.pub_date for e in Entry.objects.all()]
That means the same database query will be executed twice, effectively doubling your database load. Also, there's a possibility the two lists may not include the same database records, because an Entry may have been added or deleted in the split second between the two requests. To avoid this problem, simply save the QuerySet and reuse it: queryset = Poll.objects.all() print [p.headline for p in queryset] # Evaluate the query set. print [p.pub_date for p in queryset] # Re-use the cache from the evaluation.
Comparing objectsTo compare two model instances, just use the standard Python comparison operator, the double equals sign: ==. Behind the scenes, that compares the primary key values of two models. Using the Entry example above, the following two statements are equivalent: some_entry == other_entry some_entry.id == other_entry.id
If a model's primary key isn't called id, no problem. Comparisons will always use the primary key, whatever it's called. For example, if a model's primary key field is called name, these two statements are equivalent: some_obj == other_obj some_obj.name == other_obj.name
Complex lookups with Q objectsKeyword argument queries -- in filter(), etc. -- are "AND"ed together. If you need to execute more complex queries (for example, queries with OR statements), you can 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 as in "Field lookups" above. For example, this Q object encapsulates a single LIKE query: Q(question__startswith='What')
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, this statement yields a single Q object that represents the "OR" of two "question__startswith" queries: Q(question__startswith='Who') | Q(question__startswith='What')
This is equivalent to the following SQL WHERE clause: WHERE question LIKE 'Who%' OR question LIKE 'What%'
You can compose statements of arbitrary complexity by combining Q objects with the & and | operators. You can also use parenthetical grouping. Each lookup function that takes keyword-arguments (e.g. filter(), exclude(), get()) can also be passed one or more Q objects as positional (not-named) arguments. If you provide multiple Q object arguments to a lookup function, the arguments will be "AND"ed together. For example: Poll.objects.get( Q(question__startswith='Who'), Q(pub_date=date(2005, 5, 2)) | Q(pub_date=date(2005, 5, 6)) )
... roughly translates into the SQL: SELECT * from polls WHERE question LIKE 'Who%' AND (pub_date = '2005-05-02' OR pub_date = '2005-05-06')
Lookup functions can mix the use of Q objects and keyword arguments. All arguments provided to a lookup function (be they keyword arguments or Q objects) are "AND"ed together. However, if a Q object is provided, it must precede the definition of any keyword arguments. For example: Poll.objects.get( Q(pub_date=date(2005, 5, 2)) | Q(pub_date=date(2005, 5, 6)), question__startswith='Who')
... would be a valid query, equivalent to the previous example; but: # INVALID QUERY Poll.objects.get( question__startswith='Who', Q(pub_date=date(2005, 5, 2)) | Q(pub_date=date(2005, 5, 6)))
... would not be valid. See the OR lookups examples page for more examples. Related objectsWhen you define a relationship in a model (i.e., a ForeignKey, OneToOneField, or ManyToManyField), instances of that model will have a convenient API to access the related object(s). Using the models at the top of this page, for example, an Entry object e can get its associated Blog object by accessing the blog attribute: e.blog. (Behind the scenes, this functionality is implemented by Python descriptors. This shouldn't really matter to you, but we point it out here for the curious.) Django also creates API accessors for the "other" side of the relationship -- the link from the related model to the model that defines the relationship. For example, a Blog object b has access to a list of all related Entry objects via the entry_set attribute: b.entry_set.all(). All examples in this section use the sample Blog, Author and Entry models defined at the top of this page. One-to-many relationshipsForwardIf 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. BackwardIf 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. Many-to-many relationshipsBoth ends of a many-to-many relationship get automatic API access to the other end. The API works just as a "backward" one-to-many relationship. See Backward above. The only difference is in the attribute naming: The model that defines the ManyToManyField uses the attribute name of that field itself, whereas the "reverse" model uses the lowercased model name of the original model, plus '_set' (just like reverse one-to-many relationships). An example makes this easier to understand: e = Entry.objects.get(id=3) e.authors.all() # Returns all Author objects for this Entry. e.authors.count() e.authors.filter(name__contains='John')
a = Author.objects.get(id=5) a.entry_set.all() # Returns all Entry objects for this Author.
Like ForeignKey, ManyToManyField can specify related_name. In the above example, if the ManyToManyField in Entry had specified related_name='entries', then each Author instance would have an entries attribute instead of entry_set. One-to-one relationshipsThe semantics of one-to-one relationships will be changing soon, so we don't recommend you use them. How are the backward relationships possible?Other object-relational mappers require you to define relationships on both sides. The Django developers believe this is a violation of the DRY (Don't Repeat Yourself) principle, so Django only requires you to define the relationship on one end. But how is this possible, given that a model class doesn't know which other model classes are related to it until those other model classes are loaded? The answer lies in the INSTALLED_APPS setting. The first time any model is loaded, Django iterates over every model in INSTALLED_APPS and creates the backward relationships in memory as needed. Essentially, one of the functions of INSTALLED_APPS is to tell Django the entire model domain. Deleting objectsThe delete method, conveniently, is named delete(). This method immediately deletes the object and has no return value. Example: e.delete()
You can also delete objects in bulk. Every QuerySet has a delete() method, which deletes all members of that QuerySet. For example, this deletes all Entry objects with a pub_date year of 2005: Entry.objects.filter(pub_date__year=2005).delete()
Note that delete() is the only QuerySet method that is not exposed on a Manager itself. This is a safety mechanism to prevent you from accidentally requesting Entry.objects.delete(), and deleting all the entries. If you do want to delete all the objects, then you have to explicitly request a complete query set: Entry.objects.all().delete()
Falling back to raw SQLIf you find yourself needing to write an SQL query that is too complex for Django's database-mapper to handle, you can fall back into raw-SQL statement mode. The preferred way to do this is by giving your model custom methods or custom manager methods that execute queries. Although there's nothing in Django that requires database queries to live in the model layer, this approach keeps all your data-access logic in one place, which is smart from an code-organization standpoint. For instructions, see Executing custom SQL. Finally, it's important to note that the Django database layer is merely an interface to your database. You can access your database via other tools, programming languages or database frameworks; there's nothing Django-specific about your database. powered by performancing firefox
|