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Bidang-bidang model khusus PostgreSQL

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

Mengindeks bidang-bidang ini

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.

ArrayField

class ArrayField(base_field, size=None, **options)

A field for storing lists of data. Most field types can be used, and you pass another field instance as the base_field. You may also specify a size. ArrayField can be nested to store multi-dimensional arrays.

Jika anda memberikan bidang default, pastikan itu adalah callable seperti list (untuk sebuah nilai kosong) atau sebuah callable yang mengembalikan list (seperti sebuah fungsi). Salah menggunakan default=[] membuat awalan yang berubah-ubah yaitu dibagi diantara semua contoh dari 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) and file fields (FileField and ImageField).

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

Code
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,
    )

Perubahan dari nilai-nilai diantara basisdata dan model, pengesahan dari data dan konfigurasi, dan serialisasi adalah semua dilimpahkan ke bidang dasar pokok.

size

Ini adalah sebuah argumen pilihan.

Jika dilewatkan, larik akan memiliki ukuran maksimal seperti ditentukan. Ini akan dilewatkan ke basisdata meskipun PostgreSQL saat sekarang tidak melaksanakan batasan.

Meminta ArrayField

Ada sejumlah pencarian penyesuaian dan merubah untuk ArrayField. Kami akan menggunakan model contoh berikut:

Code
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:

Python console
>>> 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:

Python console
>>> 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:

Python console
>>> Post.objects.create(name="First post", tags=["thoughts", "django"])
>>> Post.objects.create(name="Second post", tags=["thoughts", "tutorial"])
>>> 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>]>

>>> Post.objects.filter(tags__overlap=Post.objects.values_list("tags"))
<QuerySet [<Post: First post>, <Post: Second post>, <Post: Third post>]>

len

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

Python console
>>> 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:

Python console
>>> 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 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:

Python console
>>> 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>]>

HStoreField

class HStoreField(**options)

Sebuah bidang untuk menyimpan pasangan nilai-kunci. Jenis data Python adalah sebuah dict. Kunci-kunci harus berupa string, dan nilai-nilai mungkin salah satu string atau null (None dalam Python).

Untuk menggunakan bidang ini, anda akan butuh untuk:

  1. Tambah 'django.contrib.postgres' dalam INSTALLED_APPS anda.

  2. Set up the hstore extension in 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

Sebagai tambahan pada kemampuan untuk pencarian berdasarkan kunci, ada angka dari pencarian penyesuaian tersedia untuk 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):
        return self.name

Kunci pencarian

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

Python console
>>> 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:

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

or use F() expressions to annotate a key value. For example:

Python console
>>> from django.db.models import F
>>> rufus = Dog.objects.annotate(breed=F("data__breed"))[0]
>>> rufus.breed
'labrador'

Jika kunci yang anda ahrapkan untuk meminta berdasarkan ketidakcocokan dengan nama dari pencarian lain, anda butuh menggunakan pencarian hstorefield.contains lookup sebagai gantinya.

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:

Python console
>>> 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:

Python console
>>> 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:

Python console
>>> 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:

Python console
>>> 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:

Python console
>>> 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:

Python console
>>> 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 avals(). For example:

Python console
>>> 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>]>

Bidang Jangkauan

Ada lima jenis jangkauan bidang, berhubungan ke jenis jangkauan siap-pakai dalam PostgreSQL. Bidang-bidang ini digunakan untuk menyimpan jangkauan dari nilai; sebagai contoh stempel waktu awal dan akhir dari sebuah acara, atau jangkauan dari umur sebuah aktivitas yang cocok.

All of the range fields translate to psycopg 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 [) (see the PostgreSQL documentation for details about different bounds). The default bounds can be changed for non-discrete range fields (DateTimeRangeField and DecimalRangeField) by using the default_bounds argument.

IntegerRangeField

class IntegerRangeField(**options)

Stores a range of integers. Based on an IntegerField. Represented by an int4range in the database and a django.db.backends.postgresql.psycopg_any.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)

Stores a range of large integers. Based on a BigIntegerField. Represented by an int8range in the database and a django.db.backends.postgresql.psycopg_any.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 [).

DecimalRangeField

class DecimalRangeField(default_bounds='[)', **options)

Stores a range of floating point values. Based on a DecimalField. Represented by a numrange in the database and a django.db.backends.postgresql.psycopg_any.NumericRange in Python.

default_bounds

Optional. The value of bounds for list and tuple inputs. The default is lower bound included, upper bound excluded, that is [) (see the PostgreSQL documentation for details about different bounds). default_bounds is not used for django.db.backends.postgresql.psycopg_any.NumericRange inputs.

DateTimeRangeField

class DateTimeRangeField(default_bounds='[)', **options)

Stores a range of timestamps. Based on a DateTimeField. Represented by a tstzrange in the database and a django.db.backends.postgresql.psycopg_any.DateTimeTZRange in Python.

default_bounds

Optional. The value of bounds for list and tuple inputs. The default is lower bound included, upper bound excluded, that is [) (see the PostgreSQL documentation for details about different bounds). default_bounds is not used for django.db.backends.postgresql.psycopg_any.DateTimeTZRange inputs.

DateRangeField

class DateRangeField(**options)

Stores a range of dates. Based on a DateField. Represented by a daterange in the database and a django.db.backends.postgresql.psycopg_any.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 [).

Meminta Jangkauan Bidang

Ada sejumlah pencarian penyesuaian dan perubahan untuk bidang jangkauan. Mereka tersedia pada semua bidang-bidang diatas, tetapi kami akan menggunakan model contoh berikut:

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):
        return self.name

We will also use the following example objects:

Python console
>>> 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)
... )

dan NumericRange:

Code
>>> from django.db.backends.postgresql.psycopg_any import NumericRange

Fungsi-fungsi penahanan

Seperti bidang-bidang PostgreSQL lainnya, ada tiga standar penahanan penghubung: contains, contained_by dan overlap, menggunakan penghubung SQL @>, <@, dan && masing-masing.

contains
Code
>>> Event.objects.filter(ages__contains=NumericRange(4, 5))
<QuerySet [<Event: Soft play>]>
contained_by
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: SmallAutoField, AutoField, BigAutoField, SmallIntegerField, IntegerField, BigIntegerField, DecimalField, FloatField, DateField, and DateTimeField. For example:

Python console
>>> from django.db.backends.postgresql.psycopg_any 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
Code
>>> Event.objects.filter(ages__overlap=NumericRange(8, 12))
<QuerySet [<Event: Soft play>]>

Fungsi perbandingan

Bidang jangkauan mendukung pencarian standar: lt, gt, lte dan gte. Ini tidak terlalu membantu - mereka membandingkan batasan terendah dahulu dan batasan tertinggi hanya jika dibutuhkan. Ini juga strategi digunakan untuk mengurutkan berdasarkan bidang jangkauan. Itu lebih baik menggunakan penghubung perbandingan jangkauan khusus.

fully_lt

Jangkauan dikembalikan adalah sangat kurang dari jangkauan dilewatkan. Dengan kata lain, semua titik dalam jangkauan dikembalikan kurang dari semua dalam jangkauan dilewatkan.

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

Jangkauan dikembalikan adalah lebih besar dari jangkauan dilewatkan. Dengan kata lain, semua titik dalam jangkauan dikembalikan lebih besar dari semua dalam jangkauan dilewatkan.

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

Jangkauan dikembalikan tidak mengandung titik apapun kurang dari jangkauan dilewatkan, yaitu batasan terendah dari jangkauan dikembalikan adalah setidaknya batasan terendah dari jangkauan dilewatkan.

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

Jangkauan dikembalikan tidak mengandung titik apapun lebih besar dari jangkauan dilewatkan, yaitu batasan tertinggi dari jangkauan dikembalikan adalah batasan paling tertinggi dari jangkauan dilewatkan.

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

Jangkauan dikembalikan berbagi sebuah batasan dengan jangkauan dilewatkan.

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

Meminta menggunakan batasan

Range fields support several extra lookups.

startswith

Obyek-obyek dikembalikan memiliki batasan terendah diberikan. Dapat diikat untuk pencarian sah untuk bidang dasar.

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

Obyek-obyek dikembalikan memiliki batasan tertinggi diberikan. Dapat diikat untuk pencarian sah untuk bidang dasar.

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

Obyek-obyek dikembalikan adalah jangkauan kosong. Dapat diikat untuk pencarian sah untuk BooleanField.

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

Returns objects that have inclusive or exclusive lower bounds, depending on the boolean value passed. Can be chained to valid lookups for a BooleanField.

Code
>>> Event.objects.filter(ages__lower_inc=True)
<QuerySet [<Event: Soft play>, <Event: Pub trip>]>
lower_inf

Returns objects that have unbounded (infinite) or bounded lower bound, depending on the boolean value passed. Can be chained to valid lookups for a BooleanField.

Code
>>> Event.objects.filter(ages__lower_inf=True)
<QuerySet []>
upper_inc

Returns objects that have inclusive or exclusive upper bounds, depending on the boolean value passed. Can be chained to valid lookups for a BooleanField.

Code
>>> Event.objects.filter(ages__upper_inc=True)
<QuerySet []>
upper_inf

Returns objects that have unbounded (infinite) or bounded upper bound, depending on the boolean value passed. Can be chained to valid lookups for a BooleanField.

Code
>>> Event.objects.filter(ages__upper_inf=True)
<QuerySet [<Event: Pub trip>]>

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 psycopg provides a register_range() to allow use of custom range types.

class RangeField(**options)

Kelas dasar untuk bidang jangkauan model.

base_field

Kelas bidang model digunakan.

range_type

The range type to use.

form_field

Kelas bidang formulir digunakan. Harus berupa subkelas dari django.contrib.postgres.forms.BaseRangeField.

class django.contrib.postgres.forms.BaseRangeField

Kelas dasar untuk formulir bidang jangkauan.

base_field

Bidang formulir digunakan.

range_type

The range type to use.

Range operators

class RangeOperators

PostgreSQL provides a set of SQL operators that can be used together with the range data types (see the PostgreSQL documentation for the full details of range operators). This class is meant as a convenient method to avoid typos. The operator names overlap with the names of corresponding lookups.

Python
class RangeOperators:
    EQUAL = "="
    NOT_EQUAL = "<>"
    CONTAINS = "@>"
    CONTAINED_BY = "<@"
    OVERLAPS = "&&"
    FULLY_LT = "<<"
    FULLY_GT = ">>"
    NOT_LT = "&>"
    NOT_GT = "&<"
    ADJACENT_TO = "-|-"

Pernyataan RangeBoundary()

class RangeBoundary(inclusive_lower=True, inclusive_upper=False)
inclusive_lower

If True (default), the lower bound is inclusive '[', otherwise it's exclusive '('.

inclusive_upper

If False (default), the upper bound is exclusive ')', otherwise it's inclusive ']'.

A RangeBoundary() expression represents the range boundaries. It can be used with a custom range functions that expected boundaries, for example to define ExclusionConstraint. See the PostgreSQL documentation for the full details.

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