Bidang-bidang model khusus PostgreSQLLink to this heading

Semua dari bidang ini tersedia dari modul django.contrib.postgres.fields.

`ArrayField`Link to this heading

class ArrayField(base_field, size=None, **options)Link to this definition

Sebuah bidang untuk menyimpan daftar data. Kebanyakan jenis bidang dapat digunakan, anda cukup melewatkan instance bidang lain sebagai base_field. Anda mungkin juga menentukan sebuah size. ArrayField dapat disarangkan untuk menyimpan larik dimensi-banyak.

If you give the field a default, ensure it's a callable such as list (for an empty default) or a callable that returns a list (such as a function). Incorrectly using default=[] creates a mutable default that is shared between all instances of ArrayField.

base_fieldLink to this definition

Ini adalah sebuah argumen diwajibkan.

Specifies the underlying data type and behavior for the array. It should be an instance of a subclass of Field. For example, it could be an IntegerField or a CharField. Most field types are permitted, with the exception of those handling relational data (ForeignKey, OneToOneField and ManyToManyField).

Itu memungkinkan menyarang bidang-bidang larik - anda dapat menentukan sebuah instance dari ArrayField sebagai base_field. Sebagai contoh:

Code

from django.db import models
from django.contrib.postgres.fields import ArrayField

class ChessBoard(models.Model):
    board = ArrayField(
        ArrayField(
            models.CharField(max_length=10, blank=True),
            size=8,
        ),
        size=8,
    )

Transformation of values between the database and the model, validation of data and configuration, and serialization are all delegated to the underlying base field.

sizeLink to this definition

Ini adalah sebuah argumen pilihan.

If passed, the array will have a maximum size as specified. This will be passed to the database, although PostgreSQL at present does not enforce the restriction.

Catatan

When nesting ArrayField, whether you use the size parameter or not, PostgreSQL requires that the arrays are rectangular:

Code

from django.contrib.postgres.fields import ArrayField
from django.db import models

class Board(models.Model):
    pieces = ArrayField(ArrayField(models.IntegerField()))

# Valid
Board(pieces=[
    [2, 3],
    [2, 1],
])

# Not valid
Board(pieces=[
    [2, 3],
    [2],
])

If irregular shapes are required, then the underlying field should be made nullable and the values padded with None.

Meminta `ArrayField`Link to this heading

There are a number of custom lookups and transforms for ArrayField. We will use the following example model:

Code

from django.db import models
from django.contrib.postgres.fields import ArrayField

class Post(models.Model):
    name = models.CharField(max_length=200)
    tags = ArrayField(models.CharField(max_length=200), blank=True)

    def __str__(self):  # __unicode__ on Python 2
        return self.name

`contains`Link to this heading

The contains lookup is overridden on ArrayField. The returned objects will be those where the values passed are a subset of the data. It uses the SQL operator @>. For example:

Code

>>> Post.objects.create(name='First post', tags=['thoughts', 'django'])
>>> Post.objects.create(name='Second post', tags=['thoughts'])
>>> Post.objects.create(name='Third post', tags=['tutorial', 'django'])

>>> Post.objects.filter(tags__contains=['thoughts'])
<QuerySet [<Post: First post>, <Post: Second post>]>

>>> Post.objects.filter(tags__contains=['django'])
<QuerySet [<Post: First post>, <Post: Third post>]>

>>> Post.objects.filter(tags__contains=['django', 'thoughts'])
<QuerySet [<Post: First post>]>

`contained_by`Link to this heading

This is the inverse of the contains lookup - the objects returned will be those where the data is a subset of the values passed. It uses the SQL operator <@. For example:

Code

>>> Post.objects.create(name='First post', tags=['thoughts', 'django'])
>>> Post.objects.create(name='Second post', tags=['thoughts'])
>>> Post.objects.create(name='Third post', tags=['tutorial', 'django'])

>>> Post.objects.filter(tags__contained_by=['thoughts', 'django'])
<QuerySet [<Post: First post>, <Post: Second post>]>

>>> Post.objects.filter(tags__contained_by=['thoughts', 'django', 'tutorial'])
<QuerySet [<Post: First post>, <Post: Second post>, <Post: Third post>]>

`overlap`Link to this heading

Returns objects where the data shares any results with the values passed. Uses the SQL operator &&. For example:

Code

>>> Post.objects.create(name='First post', tags=['thoughts', 'django'])
>>> Post.objects.create(name='Second post', tags=['thoughts'])
>>> Post.objects.create(name='Third post', tags=['tutorial', 'django'])

>>> Post.objects.filter(tags__overlap=['thoughts'])
<QuerySet [<Post: First post>, <Post: Second post>]>

>>> Post.objects.filter(tags__overlap=['thoughts', 'tutorial'])
<QuerySet [<Post: First post>, <Post: Second post>, <Post: Third post>]>

`len`Link to this heading

Returns the length of the array. The lookups available afterwards are those available for IntegerField. For example:

Code

>>> Post.objects.create(name='First post', tags=['thoughts', 'django'])
>>> Post.objects.create(name='Second post', tags=['thoughts'])

>>> Post.objects.filter(tags__len=1)
<QuerySet [<Post: Second post>]>

Perubahan indeksLink to this heading

This class of transforms allows you to index into the array in queries. Any non-negative integer can be used. There are no errors if it exceeds the size of the array. The lookups available after the transform are those from the base_field. For example:

Code

>>> Post.objects.create(name='First post', tags=['thoughts', 'django'])
>>> Post.objects.create(name='Second post', tags=['thoughts'])

>>> Post.objects.filter(tags__0='thoughts')
<QuerySet [<Post: First post>, <Post: Second post>]>

>>> Post.objects.filter(tags__1__iexact='Django')
<QuerySet [<Post: First post>]>

>>> Post.objects.filter(tags__276='javascript')
<QuerySet []>

Perubahan potonganLink to this heading

This class of transforms allow you to take a slice of the array. Any two non-negative integers can be used, separated by a single underscore. The lookups available after the transform do not change. For example:

Code

>>> Post.objects.create(name='First post', tags=['thoughts', 'django'])
>>> Post.objects.create(name='Second post', tags=['thoughts'])
>>> Post.objects.create(name='Third post', tags=['django', 'python', 'thoughts'])

>>> Post.objects.filter(tags__0_1=['thoughts'])
<QuerySet [<Post: First post>, <Post: Second post>]>

>>> Post.objects.filter(tags__0_2__contains=['thoughts'])
<QuerySet [<Post: First post>, <Post: Second post>]>

Mengindeks `ArrayField`Link to this heading

At present using db_index will create a btree index. This does not offer particularly significant help to querying. A more useful index is a GIN index, which you should create using a RunSQL operation.

`HStoreField`Link to this heading

class HStoreField(**options)Link to this definition

A field for storing mappings of strings to strings. The Python data type used is a dict.

Untuk menggunakan bidang ini, anda akan butuh untuk:

Tambah 'django.contrib.postgres' dalam INSTALLED_APPS anda.
Setup the hstore extension di PostgreSQL.

Anda akan melihat sebuah kesalahan seperti can't adapt type 'dict' jika anda melewati langkah pertama, atau type "hstore" does not exist jika anda melewati kedua.

Meminta `HStoreField`Link to this heading

In addition to the ability to query by key, there are a number of custom lookups available for HStoreField.

Kami akan menggunakan model contoh berikut:

Code

from django.contrib.postgres.fields import HStoreField
from django.db import models

class Dog(models.Model):
    name = models.CharField(max_length=200)
    data = HStoreField()

    def __str__(self):  # __unicode__ on Python 2
        return self.name

Kunci pencarianLink to this heading

To query based on a given key, you simply use that key as the lookup name:

Code

>>> Dog.objects.create(name='Rufus', data={'breed': 'labrador'})
>>> Dog.objects.create(name='Meg', data={'breed': 'collie'})

>>> Dog.objects.filter(data__breed='collie')
<QuerySet [<Dog: Meg>]>

You can chain other lookups after key lookups:

Code

>>> Dog.objects.filter(data__breed__contains='l')
<QuerySet [<Dog: Rufus>, <Dog: Meg>]>

If the key you wish to query by clashes with the name of another lookup, you need to use the hstorefield.contains lookup instead.

`contains`Link to this heading

The contains lookup is overridden on HStoreField. The returned objects are those where the given dict of key-value pairs are all contained in the field. It uses the SQL operator @>. For example:

Code

>>> Dog.objects.create(name='Rufus', data={'breed': 'labrador', 'owner': 'Bob'})
>>> Dog.objects.create(name='Meg', data={'breed': 'collie', 'owner': 'Bob'})
>>> Dog.objects.create(name='Fred', data={})

>>> Dog.objects.filter(data__contains={'owner': 'Bob'})
<QuerySet [<Dog: Rufus>, <Dog: Meg>]>

>>> Dog.objects.filter(data__contains={'breed': 'collie'})
<QuerySet [<Dog: Meg>]>

`contained_by`Link to this heading

This is the inverse of the contains lookup - the objects returned will be those where the key-value pairs on the object are a subset of those in the value passed. It uses the SQL operator <@. For example:

Code

>>> Dog.objects.create(name='Rufus', data={'breed': 'labrador', 'owner': 'Bob'})
>>> Dog.objects.create(name='Meg', data={'breed': 'collie', 'owner': 'Bob'})
>>> Dog.objects.create(name='Fred', data={})

>>> Dog.objects.filter(data__contained_by={'breed': 'collie', 'owner': 'Bob'})
<QuerySet [<Dog: Meg>, <Dog: Fred>]>

>>> Dog.objects.filter(data__contained_by={'breed': 'collie'})
<QuerySet [<Dog: Fred>]>

`has_key`Link to this heading

Returns objects where the given key is in the data. Uses the SQL operator ?. For example:

Code

>>> Dog.objects.create(name='Rufus', data={'breed': 'labrador'})
>>> Dog.objects.create(name='Meg', data={'breed': 'collie', 'owner': 'Bob'})

>>> Dog.objects.filter(data__has_key='owner')
<QuerySet [<Dog: Meg>]>

`has_any_keys`Link to this heading

Returns objects where any of the given keys are in the data. Uses the SQL operator ?|. For example:

Code

>>> Dog.objects.create(name='Rufus', data={'breed': 'labrador'})
>>> Dog.objects.create(name='Meg', data={'owner': 'Bob'})
>>> Dog.objects.create(name='Fred', data={})

>>> Dog.objects.filter(data__has_any_keys=['owner', 'breed'])
<QuerySet [<Dog: Rufus>, <Dog: Meg>]>

`has_keys`Link to this heading

Returns objects where all of the given keys are in the data. Uses the SQL operator ?&. For example:

Code

>>> Dog.objects.create(name='Rufus', data={})
>>> Dog.objects.create(name='Meg', data={'breed': 'collie', 'owner': 'Bob'})

>>> Dog.objects.filter(data__has_keys=['breed', 'owner'])
<QuerySet [<Dog: Meg>]>

`keys`Link to this heading

Returns objects where the array of keys is the given value. Note that the order is not guaranteed to be reliable, so this transform is mainly useful for using in conjunction with lookups on ArrayField. Uses the SQL function akeys(). For example:

Code

>>> Dog.objects.create(name='Rufus', data={'toy': 'bone'})
>>> Dog.objects.create(name='Meg', data={'breed': 'collie', 'owner': 'Bob'})

>>> Dog.objects.filter(data__keys__overlap=['breed', 'toy'])
<QuerySet [<Dog: Rufus>, <Dog: Meg>]>

`values`Link to this heading

Returns objects where the array of values is the given value. Note that the order is not guaranteed to be reliable, so this transform is mainly useful for using in conjunction with lookups on ArrayField. Uses the SQL function avalues(). For example:

Code

>>> Dog.objects.create(name='Rufus', data={'breed': 'labrador'})
>>> Dog.objects.create(name='Meg', data={'breed': 'collie', 'owner': 'Bob'})

>>> Dog.objects.filter(data__values__contains=['collie'])
<QuerySet [<Dog: Meg>]>

`JSONField`Link to this heading

class JSONField(**options)Link to this definition

A field for storing JSON encoded data. In Python the data is represented in its Python native format: dictionaries, lists, strings, numbers, booleans and None.

If you want to store other data types, you'll need to serialize them first. For example, you might cast a datetime to a string. You might also want to convert the string back to a datetime when you retrieve the data from the database. There are some third-party JSONField implementations which do this sort of thing automatically.

If you give the field a default, ensure it's a callable such as dict (for an empty default) or a callable that returns a dict (such as a function). Incorrectly using default={} creates a mutable default that is shared between all instances of JSONField.

Meminta `JSONField`Link to this heading

Kami akan menggunakan model contoh berikut:

Code

from django.contrib.postgres.fields import JSONField
from django.db import models

class Dog(models.Model):
    name = models.CharField(max_length=200)
    data = JSONField()

    def __str__(self):  # __unicode__ on Python 2
        return self.name

Kunci, indeks, dan pencarian kalurLink to this heading

Untuk meminta berdasarkan kunci kamus yang diberikan, cukup gunakan kunci itu sebagai nama pencarian:

Code

>>> Dog.objects.create(name='Rufus', data={
...     'breed': 'labrador',
...     'owner': {
...         'name': 'Bob',
...         'other_pets': [{
...             'name': 'Fishy',
...         }],
...     },
... })
>>> Dog.objects.create(name='Meg', data={'breed': 'collie'})

>>> Dog.objects.filter(data__breed='collie')
<QuerySet [<Dog: Meg>]>

Multiple keys can be chained together to form a path lookup:

Code

>>> Dog.objects.filter(data__owner__name='Bob')
<QuerySet [<Dog: Rufus>]>

Jika kunci adalah sebuah integer, itu akan ditafsirkan sebagai sebuah pencarian indeks dalam sebuah larik:

Code

>>> Dog.objects.filter(data__owner__other_pets__0__name='Fishy')
<QuerySet [<Dog: Rufus>]>

If the key you wish to query by clashes with the name of another lookup, use the jsonfield.contains lookup instead.

If only one key or index is used, the SQL operator -> is used. If multiple operators are used then the #> operator is used.

Containment and key operationsLink to this heading

JSONField berbagi pencarian terkait pada penahanan dan kunci dengan HStoreField.

contains (menerima JSON apapun daripada hanya sebuah kamus dari string)
contained_by (menerima JSON apapun daripada hanya sebuah kamus dari string)
has_key
has_any_keys
:lookup

Bidang JangkauanLink to this heading

There are five range field types, corresponding to the built-in range types in PostgreSQL. These fields are used to store a range of values; for example the start and end timestamps of an event, or the range of ages an activity is suitable for.

All of the range fields translate to psycopg2 Range objects in python, but also accept tuples as input if no bounds information is necessary. The default is lower bound included, upper bound excluded; that is, [).

`IntegerRangeField`Link to this heading

class IntegerRangeField(**options)Link to this definition

Stores a range of integers. Based on an IntegerField. Represented by an int4range in the database and a NumericRange in Python.

Regardless of the bounds specified when saving the data, PostgreSQL always returns a range in a canonical form that includes the lower bound and excludes the upper bound; that is [).

`BigIntegerRangeField`Link to this heading

class BigIntegerRangeField(**options)Link to this definition

Stores a range of large integers. Based on a BigIntegerField. Represented by an int8range in the database and a NumericRange in Python.

Regardless of the bounds specified when saving the data, PostgreSQL always returns a range in a canonical form that includes the lower bound and excludes the upper bound; that is [).

`FloatRangeField`Link to this heading

class FloatRangeField(**options)Link to this definition: Stores a range of floating point values. Based on a FloatField. Represented by a numrange in the database and a NumericRange in Python.

`DateTimeRangeField`Link to this heading

class DateTimeRangeField(**options)Link to this definition: Stores a range of timestamps. Based on a DateTimeField. Represented by a tztsrange in the database and a DateTimeTZRange in Python.

`DateRangeField`Link to this heading

class DateRangeField(**options)Link to this definition

Stores a range of dates. Based on a DateField. Represented by a daterange in the database and a DateRange in Python.

Regardless of the bounds specified when saving the data, PostgreSQL always returns a range in a canonical form that includes the lower bound and excludes the upper bound; that is [).

Querying Range FieldsLink to this heading

There are a number of custom lookups and transforms for range fields. They are available on all the above fields, but we will use the following example model:

Code

from django.contrib.postgres.fields import IntegerRangeField
from django.db import models

class Event(models.Model):
    name = models.CharField(max_length=200)
    ages = IntegerRangeField()
    start = models.DateTimeField()

    def __str__(self):  # __unicode__ on Python 2
        return self.name

We will also use the following example objects:

Code

>>> import datetime
>>> from django.utils import timezone
>>> now = timezone.now()
>>> Event.objects.create(name='Soft play', ages=(0, 10), start=now)
>>> Event.objects.create(name='Pub trip', ages=(21, None), start=now - datetime.timedelta(days=1))

and NumericRange:

Code

>>> from psycopg2.extras import NumericRange

Containment functionsLink to this heading

As with other PostgreSQL fields, there are three standard containment operators: contains, contained_by and overlap, using the SQL operators @>, <@, and && respectively.

`contains`Link to this heading

Code

>>> Event.objects.filter(ages__contains=NumericRange(4, 5))
<QuerySet [<Event: Soft play>]>

`contained_by`Link to this heading

Code

>>> Event.objects.filter(ages__contained_by=NumericRange(0, 15))
<QuerySet [<Event: Soft play>]>

The contained_by lookup is also available on the non-range field types: IntegerField, BigIntegerField, FloatField, DateField, and DateTimeField. For example:

Code

>>> from psycopg2.extras import DateTimeTZRange
>>> Event.objects.filter(start__contained_by=DateTimeTZRange(
...     timezone.now() - datetime.timedelta(hours=1),
...     timezone.now() + datetime.timedelta(hours=1),
... )
<QuerySet [<Event: Soft play>]>

`overlap`Link to this heading

Code

>>> Event.objects.filter(ages__overlap=NumericRange(8, 12))
<QuerySet [<Event: Soft play>]>

Fungsi perbandinganLink to this heading

Range fields support the standard lookups: lt, gt, lte and gte. These are not particularly helpful - they compare the lower bounds first and then the upper bounds only if necessary. This is also the strategy used to order by a range field. It is better to use the specific range comparison operators.

`fully_lt`Link to this heading

The returned ranges are strictly less than the passed range. In other words, all the points in the returned range are less than all those in the passed range.

Code

>>> Event.objects.filter(ages__fully_lt=NumericRange(11, 15))
<QuerySet [<Event: Soft play>]>

`fully_gt`Link to this heading

The returned ranges are strictly greater than the passed range. In other words, the all the points in the returned range are greater than all those in the passed range.

Code

>>> Event.objects.filter(ages__fully_gt=NumericRange(11, 15))
<QuerySet [<Event: Pub trip>]>

`not_lt`Link to this heading

The returned ranges do not contain any points less than the passed range, that is the lower bound of the returned range is at least the lower bound of the passed range.

Code

>>> Event.objects.filter(ages__not_lt=NumericRange(0, 15))
<QuerySet [<Event: Soft play>, <Event: Pub trip>]>

`not_gt`Link to this heading

The returned ranges do not contain any points greater than the passed range, that is the upper bound of the returned range is at most the upper bound of the passed range.

Code

>>> Event.objects.filter(ages__not_gt=NumericRange(3, 10))
<QuerySet [<Event: Soft play>]>

`adjacent_to`Link to this heading

The returned ranges share a bound with the passed range.

Code

>>> Event.objects.filter(ages__adjacent_to=NumericRange(10, 21))
<QuerySet [<Event: Soft play>, <Event: Pub trip>]>

Querying using the boundsLink to this heading

There are three transforms available for use in queries. You can extract the lower or upper bound, or query based on emptiness.

`startswith`Link to this heading

Returned objects have the given lower bound. Can be chained to valid lookups for the base field.

Code

>>> Event.objects.filter(ages__startswith=21)
<QuerySet [<Event: Pub trip>]>

`endswith`Link to this heading

Returned objects have the given upper bound. Can be chained to valid lookups for the base field.

Code

>>> Event.objects.filter(ages__endswith=10)
<QuerySet [<Event: Soft play>]>

`isempty`Link to this heading

Returned objects are empty ranges. Can be chained to valid lookups for a BooleanField.

Code

>>> Event.objects.filter(ages__isempty=True)
<QuerySet []>

Menentukan jenis jangkauan anda sendiriLink to this heading

PostgreSQL allows the definition of custom range types. Django's model and form field implementations use base classes below, and psycopg2 provides a register_range() to allow use of custom range types.

class RangeField(**options)Link to this definition

Base class for model range fields.

base_fieldLink to this definition: The model field class to use.

range_typeLink to this definition: The psycopg2 range type to use.

form_fieldLink to this definition: The form field class to use. Should be a subclass of django.contrib.postgres.forms.BaseRangeField.

class django.contrib.postgres.forms.BaseRangeFieldLink to this definition

Base class for form range fields.

base_fieldLink to this definition: The form field to use.

range_typeLink to this definition: The psycopg2 range type to use.

Bidang-bidang model khusus PostgreSQLLink to this heading#

ArrayFieldLink to this heading#

Meminta ArrayFieldLink to this heading#

containsLink to this heading#

contained_byLink to this heading#

overlapLink to this heading#

lenLink to this heading#

Perubahan indeksLink to this heading#

Perubahan potonganLink to this heading#

Mengindeks ArrayFieldLink to this heading#

HStoreFieldLink to this heading#

Meminta HStoreFieldLink to this heading#

Kunci pencarianLink to this heading#

containsLink to this heading#

contained_byLink to this heading#

has_keyLink to this heading#

has_any_keysLink to this heading#

has_keysLink to this heading#

keysLink to this heading#

valuesLink to this heading#

JSONFieldLink to this heading#

Meminta JSONFieldLink to this heading#

Kunci, indeks, dan pencarian kalurLink to this heading#

Containment and key operationsLink to this heading#

Bidang JangkauanLink to this heading#

IntegerRangeFieldLink to this heading#

BigIntegerRangeFieldLink to this heading#

FloatRangeFieldLink to this heading#

DateTimeRangeFieldLink to this heading#

DateRangeFieldLink to this heading#

Querying Range FieldsLink to this heading#

Containment functionsLink to this heading#

containsLink to this heading#

contained_byLink to this heading#

overlapLink to this heading#

Fungsi perbandinganLink to this heading#

fully_ltLink to this heading#

fully_gtLink to this heading#

not_ltLink to this heading#

not_gtLink to this heading#

adjacent_toLink to this heading#

Querying using the boundsLink to this heading#

startswithLink to this heading#

endswithLink to this heading#

isemptyLink to this heading#

Menentukan jenis jangkauan anda sendiriLink to this heading#

Bidang-bidang model khusus PostgreSQLLink to this heading

`ArrayField`Link to this heading

Meminta `ArrayField`Link to this heading

`contains`Link to this heading

`contained_by`Link to this heading

`overlap`Link to this heading

`len`Link to this heading

Perubahan indeksLink to this heading

Perubahan potonganLink to this heading

Mengindeks `ArrayField`Link to this heading

`HStoreField`Link to this heading

Meminta `HStoreField`Link to this heading

Kunci pencarianLink to this heading

`contains`Link to this heading

`contained_by`Link to this heading

`has_key`Link to this heading

`has_any_keys`Link to this heading

`has_keys`Link to this heading

`keys`Link to this heading

`values`Link to this heading

`JSONField`Link to this heading

Meminta `JSONField`Link to this heading

Kunci, indeks, dan pencarian kalurLink to this heading

Containment and key operationsLink to this heading

Bidang JangkauanLink to this heading

`IntegerRangeField`Link to this heading

`BigIntegerRangeField`Link to this heading

`FloatRangeField`Link to this heading

`DateTimeRangeField`Link to this heading

`DateRangeField`Link to this heading

Querying Range FieldsLink to this heading

Containment functionsLink to this heading

`contains`Link to this heading

`contained_by`Link to this heading

`overlap`Link to this heading

Fungsi perbandinganLink to this heading

`fully_lt`Link to this heading

`fully_gt`Link to this heading

`not_lt`Link to this heading

`not_gt`Link to this heading

`adjacent_to`Link to this heading

Querying using the boundsLink to this heading

`startswith`Link to this heading

`endswith`Link to this heading

`isempty`Link to this heading

Menentukan jenis jangkauan anda sendiriLink to this heading