Bidang-bidang model khusus PostgreSQL¶

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

Indexing these fields¶

Index and Field.db_index both create a B-tree index, which isn't particularly helpful when querying complex data types. Indexes such as GinIndex and GistIndex are better suited, though the index choice is dependent on the queries that you're using. Generally, GiST may be a good choice for the range fields and HStoreField, and GIN may be helpful for ArrayField and JSONField.

`ArrayField`¶

class ArrayField(base_field, size=None, **options)[sumber]¶

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_field¶

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:

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

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.

size¶

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:

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`¶

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

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

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

    def __str__(self):
        return self.name

`contains`¶

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:

>>> 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`¶

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:

>>> 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`¶

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

>>> 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`¶

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

>>> 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 indeks¶

Index transforms index into the array. 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:

>>> 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 []>

Catatan

PostgreSQL uses 1-based indexing for array fields when writing raw SQL. However these indexes and those used in slices use 0-based indexing to be consistent with Python.

Perubahan potongan¶

Slice transforms 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:

>>> 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>]>

Catatan

PostgreSQL uses 1-based indexing for array fields when writing raw SQL. However these slices and those used in indexes use 0-based indexing to be consistent with Python.

Larik dimensi banyak dengan indeks dan potongan

PostgreSQL has some rather esoteric behavior when using indexes and slices on multidimensional arrays. It will always work to use indexes to reach down to the final underlying data, but most other slices behave strangely at the database level and cannot be supported in a logical, consistent fashion by Django.

`CIText` fields¶

class CIText(**options)[sumber]¶

New in Django 1.11.

A mixin to create case-insensitive text fields backed by the citext type. Read about the performance considerations prior to using it.

To use citext, use the CITextExtension operation to setup the citext extension in PostgreSQL before the first CreateModel migration operation.

Several fields that use the mixin are provided:

class CICharField(**options)[sumber]¶

class CIEmailField(**options)[sumber]¶

class CITextField(**options)[sumber]¶

These fields subclass CharField, EmailField, and TextField, respectively.

max_length won't be enforced in the database since citext behaves similar to PostgreSQL's text type.

`HStoreField`¶

class HStoreField(**options)[sumber]¶

A field for storing key-value pairs. The Python data type used is a dict. Keys must be strings, and values may be either strings or nulls (None in Python).

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.

Changed in Django 1.11:

Added the ability to store nulls. Previously, they were cast to strings.

Catatan

On occasions it may be useful to require or restrict the keys which are valid for a given field. This can be done using the KeysValidator.

Meminta `HStoreField`¶

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:

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):
        return self.name

Kunci pencarian¶

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

>>> 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:

>>> 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.

Peringatan

Since any string could be a key in a hstore value, any lookup other than those listed below will be interpreted as a key lookup. No errors are raised. Be extra careful for typing mistakes, and always check your queries work as you intend.

`contains`¶

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:

>>> 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`¶

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:

>>> 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`¶

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

>>> 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`¶

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

>>> 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`¶

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

>>> 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`¶

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:

>>> 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`¶

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:

>>> 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`¶

class JSONField(encoder=None, **options)[sumber]¶

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.

encoder¶

New in Django 1.11.

An optional JSON-encoding class to serialize data types not supported by the standard JSON serializer (datetime, uuid, etc.). For example, you can use the DjangoJSONEncoder class or any other json.JSONEncoder subclass.

When the value is retrieved from the database, it will be in the format chosen by the custom encoder (most often a string), so you'll need to take extra steps to convert the value back to the initial data type (Model.from_db() and Field.from_db_value() are two possible hooks for that purpose). Your deserialization may need to account for the fact that you can't be certain of the input type. For example, you run the risk of returning a datetime that was actually a string that just happened to be in the same format chosen for datetimes.

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.

Catatan

PostgreSQL has two native JSON based data types: json and jsonb. The main difference between them is how they are stored and how they can be queried. PostgreSQL's json field is stored as the original string representation of the JSON and must be decoded on the fly when queried based on keys. The jsonb field is stored based on the actual structure of the JSON which allows indexing. The trade-off is a small additional cost on writing to the jsonb field. JSONField uses jsonb.

As a result, this field requires PostgreSQL ≥ 9.4.

Meminta `JSONField`¶

Kami akan menggunakan model contoh berikut:

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):
        return self.name

Kunci, indeks, dan pencarian kalur¶

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

>>> 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:

>>> 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:

>>> 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.

Peringatan

Since any string could be a key in a JSON object, any lookup other than those listed below will be interpreted as a key lookup. No errors are raised. Be extra careful for typing mistakes, and always check your queries work as you intend.

Containment and key operations¶

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 Jangkauan¶

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`¶

class IntegerRangeField(**options)[sumber]¶

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`¶

class BigIntegerRangeField(**options)[sumber]¶

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`¶

class FloatRangeField(**options)[sumber]¶: Stores a range of floating point values. Based on a FloatField. Represented by a numrange in the database and a NumericRange in Python.

`DateTimeRangeField`¶

class DateTimeRangeField(**options)[sumber]¶: Stores a range of timestamps. Based on a DateTimeField. Represented by a tstzrange in the database and a DateTimeTZRange in Python.

`DateRangeField`¶

class DateRangeField(**options)[sumber]¶

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 Fields¶

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:

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):
        return self.name

We will also use the following example objects:

>>> 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:

>>> from psycopg2.extras import NumericRange

Containment functions¶

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

`contains`¶

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

`contained_by`¶

>>> 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:

>>> 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`¶

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

Fungsi perbandingan¶

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`¶

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.

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

`fully_gt`¶

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.

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

`not_lt`¶

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.

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

`not_gt`¶

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.

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

`adjacent_to`¶

The returned ranges share a bound with the passed range.

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

Querying using the bounds¶

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

`startswith`¶

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

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

`endswith`¶

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

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

`isempty`¶

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

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

Menentukan jenis jangkauan anda sendiri¶

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)[sumber]¶

Base class for model range fields.

base_field¶: The model field class to use.

range_type¶: The psycopg2 range type to use.

form_field¶: The form field class to use. Should be a subclass of django.contrib.postgres.forms.BaseRangeField.

class django.contrib.postgres.forms.BaseRangeField¶

Base class for form range fields.

base_field¶: The form field to use.

range_type¶: The psycopg2 range type to use.

Bidang-bidang model khusus PostgreSQL¶

Indexing these fields¶

ArrayField¶

Meminta ArrayField¶

contains¶

contained_by¶

overlap¶

len¶

Perubahan indeks¶

Perubahan potongan¶

CIText fields¶

HStoreField¶

Meminta HStoreField¶

Kunci pencarian¶

contains¶

contained_by¶

has_key¶

has_any_keys¶

has_keys¶

keys¶

values¶

JSONField¶

Meminta JSONField¶

Kunci, indeks, dan pencarian kalur¶

Containment and key operations¶

Bidang Jangkauan¶

IntegerRangeField¶

BigIntegerRangeField¶

FloatRangeField¶

DateTimeRangeField¶

DateRangeField¶

Querying Range Fields¶

Containment functions¶

contains¶

contained_by¶

overlap¶

Fungsi perbandingan¶

fully_lt¶

fully_gt¶

not_lt¶

not_gt¶

adjacent_to¶

Querying using the bounds¶

startswith¶

endswith¶

isempty¶

Menentukan jenis jangkauan anda sendiri¶

Additional Information

Support Django!

Contents

Getting help

Download:

`ArrayField`¶

Meminta `ArrayField`¶

`contains`¶

`contained_by`¶

`overlap`¶

`len`¶

`CIText` fields¶

`HStoreField`¶

Meminta `HStoreField`¶

`contains`¶

`contained_by`¶

`has_key`¶

`has_any_keys`¶

`has_keys`¶

`keys`¶

`values`¶

`JSONField`¶

Meminta `JSONField`¶

`IntegerRangeField`¶

`BigIntegerRangeField`¶

`FloatRangeField`¶

`DateTimeRangeField`¶

`DateRangeField`¶

`contains`¶

`contained_by`¶

`overlap`¶

`fully_lt`¶

`fully_gt`¶

`not_lt`¶

`not_gt`¶

`adjacent_to`¶

`startswith`¶

`endswith`¶

`isempty`¶