{"title":"Bidang-bidang model khusus PostgreSQL","version":"6.0","locale":"id","docname":"ref/contrib/postgres/fields","url":"/id/6.0/ref/contrib/postgres/fields/","canonical":"https://djangodocs.dev/id/6.0/ref/contrib/postgres/fields/","summary":"Semua dari bidang ini tersedia dari modul django.contrib.postgres.fields . Mengindeks bidang-bidang ini Link to this heading # Index and Field.db_index both create…","html":"

Bidang-bidang model khusus PostgreSQLLink to this heading#

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

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Mengindeks bidang-bidang iniLink to this heading#

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

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ArrayFieldLink to this heading#

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\nclass ArrayField(base_field, size=None, **options)Link to this definition#
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A field for storing lists of data. Most field types can be used, and you\npass another field instance as the base_field. You may also specify a size. ArrayField can be nested to store multi-dimensional\narrays.

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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.

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\nbase_fieldLink to this definition#
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Ini adalah sebuah argumen diwajibkan.

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Specifies the underlying data type and behavior for the array. It\nshould be an instance of a subclass of\nField. For example, it could be an\nIntegerField or a\nCharField. Most field types are permitted,\nwith the exception of those handling relational data\n(ForeignKey,\nOneToOneField and\nManyToManyField) and file fields\n(FileField and\nImageField).

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

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Code
from django.contrib.postgres.fields import ArrayField\nfrom django.db import models\n\n\nclass ChessBoard(models.Model):\n    board = ArrayField(\n        ArrayField(\n            models.CharField(max_length=10, blank=True),\n            size=8,\n        ),\n        size=8,\n    )\n
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Perubahan dari nilai-nilai diantara basisdata dan model, pengesahan dari data dan konfigurasi, dan serialisasi adalah semua dilimpahkan ke bidang dasar pokok.

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\n\n
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\nsizeLink to this definition#
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Ini adalah sebuah argumen pilihan.

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

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Meminta ArrayFieldLink to this heading#

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

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Code
from django.contrib.postgres.fields import ArrayField\nfrom django.db import models\n\n\nclass Post(models.Model):\n    name = models.CharField(max_length=200)\n    tags = ArrayField(models.CharField(max_length=200), blank=True)\n\n    def __str__(self):\n        return self.name\n
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containsLink to this heading#

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

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Python console
>>> Post.objects.create(name="First post", tags=["thoughts", "django"])\n>>> Post.objects.create(name="Second post", tags=["thoughts"])\n>>> Post.objects.create(name="Third post", tags=["tutorial", "django"])\n\n>>> Post.objects.filter(tags__contains=["thoughts"])\n<QuerySet [<Post: First post>, <Post: Second post>]>\n\n>>> Post.objects.filter(tags__contains=["django"])\n<QuerySet [<Post: First post>, <Post: Third post>]>\n\n>>> Post.objects.filter(tags__contains=["django", "thoughts"])\n<QuerySet [<Post: First post>]>\n
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contained_byLink to this heading#

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

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Python console
>>> Post.objects.create(name="First post", tags=["thoughts", "django"])\n>>> Post.objects.create(name="Second post", tags=["thoughts"])\n>>> Post.objects.create(name="Third post", tags=["tutorial", "django"])\n\n>>> Post.objects.filter(tags__contained_by=["thoughts", "django"])\n<QuerySet [<Post: First post>, <Post: Second post>]>\n\n>>> Post.objects.filter(tags__contained_by=["thoughts", "django", "tutorial"])\n<QuerySet [<Post: First post>, <Post: Second post>, <Post: Third post>]>\n
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overlapLink to this heading#

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

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Python console
>>> Post.objects.create(name="First post", tags=["thoughts", "django"])\n>>> Post.objects.create(name="Second post", tags=["thoughts", "tutorial"])\n>>> Post.objects.create(name="Third post", tags=["tutorial", "django"])\n\n>>> Post.objects.filter(tags__overlap=["thoughts"])\n<QuerySet [<Post: First post>, <Post: Second post>]>\n\n>>> Post.objects.filter(tags__overlap=["thoughts", "tutorial"])\n<QuerySet [<Post: First post>, <Post: Second post>, <Post: Third post>]>\n\n>>> Post.objects.filter(tags__overlap=Post.objects.values_list("tags"))\n<QuerySet [<Post: First post>, <Post: Second post>, <Post: Third post>]>\n
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lenLink to this heading#

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

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Python console
>>> Post.objects.create(name="First post", tags=["thoughts", "django"])\n>>> Post.objects.create(name="Second post", tags=["thoughts"])\n\n>>> Post.objects.filter(tags__len=1)\n<QuerySet [<Post: Second post>]>\n
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Perubahan indeksLink to this heading#

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Index transforms index into the array. Any non-negative integer can be used.\nThere are no errors if it exceeds the size of the\narray. The lookups available after the transform are those from the\nbase_field. For example:

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Python console
>>> Post.objects.create(name="First post", tags=["thoughts", "django"])\n>>> Post.objects.create(name="Second post", tags=["thoughts"])\n\n>>> Post.objects.filter(tags__0="thoughts")\n<QuerySet [<Post: First post>, <Post: Second post>]>\n\n>>> Post.objects.filter(tags__1__iexact="Django")\n<QuerySet [<Post: First post>]>\n\n>>> Post.objects.filter(tags__276="javascript")\n<QuerySet []>\n
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Perubahan potonganLink to this heading#

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Slice transforms take a slice of the array. Any two non-negative integers can\nbe used, separated by a single underscore. The lookups available after the\ntransform do not change. For example:

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Python console
>>> Post.objects.create(name="First post", tags=["thoughts", "django"])\n>>> Post.objects.create(name="Second post", tags=["thoughts"])\n>>> Post.objects.create(name="Third post", tags=["django", "python", "thoughts"])\n\n>>> Post.objects.filter(tags__0_1=["thoughts"])\n<QuerySet [<Post: First post>, <Post: Second post>]>\n\n>>> Post.objects.filter(tags__0_2__contains=["thoughts"])\n<QuerySet [<Post: First post>, <Post: Second post>]>\n
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HStoreFieldLink to this heading#

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\nclass HStoreField(**options)Link to this definition#
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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).

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Untuk menggunakan bidang ini, anda akan butuh untuk:

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    \n

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

    2. \n

  2. Set up the hstore extension in\nPostgreSQL.

    3. \n
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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.

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Meminta HStoreFieldLink to this heading#

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Sebagai tambahan pada kemampuan untuk pencarian berdasarkan kunci, ada angka dari pencarian penyesuaian tersedia untuk HStoreField.

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Kami akan menggunakan model contoh berikut:

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Code
from django.contrib.postgres.fields import HStoreField\nfrom django.db import models\n\n\nclass Dog(models.Model):\n    name = models.CharField(max_length=200)\n    data = HStoreField()\n\n    def __str__(self):\n        return self.name\n
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Kunci pencarianLink to this heading#

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

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Python console
>>> Dog.objects.create(name="Rufus", data={"breed": "labrador"})\n>>> Dog.objects.create(name="Meg", data={"breed": "collie"})\n\n>>> Dog.objects.filter(data__breed="collie")\n<QuerySet [<Dog: Meg>]>\n
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You can chain other lookups after key lookups:

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Python console
>>> Dog.objects.filter(data__breed__contains="l")\n<QuerySet [<Dog: Rufus>, <Dog: Meg>]>\n
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or use F() expressions to annotate a key value. For example:

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Python console
>>> from django.db.models import F\n>>> rufus = Dog.objects.annotate(breed=F("data__breed"))[0]\n>>> rufus.breed\n'labrador'\n
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Jika kunci yang anda ahrapkan untuk meminta berdasarkan ketidakcocokan dengan nama dari pencarian lain, anda butuh menggunakan pencarian hstorefield.contains lookup sebagai gantinya.

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containsLink to this heading#

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

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Python console
>>> Dog.objects.create(name="Rufus", data={"breed": "labrador", "owner": "Bob"})\n>>> Dog.objects.create(name="Meg", data={"breed": "collie", "owner": "Bob"})\n>>> Dog.objects.create(name="Fred", data={})\n\n>>> Dog.objects.filter(data__contains={"owner": "Bob"})\n<QuerySet [<Dog: Rufus>, <Dog: Meg>]>\n\n>>> Dog.objects.filter(data__contains={"breed": "collie"})\n<QuerySet [<Dog: Meg>]>\n
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\n

contained_byLink to this heading#

\n

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

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Python console
>>> Dog.objects.create(name="Rufus", data={"breed": "labrador", "owner": "Bob"})\n>>> Dog.objects.create(name="Meg", data={"breed": "collie", "owner": "Bob"})\n>>> Dog.objects.create(name="Fred", data={})\n\n>>> Dog.objects.filter(data__contained_by={"breed": "collie", "owner": "Bob"})\n<QuerySet [<Dog: Meg>, <Dog: Fred>]>\n\n>>> Dog.objects.filter(data__contained_by={"breed": "collie"})\n<QuerySet [<Dog: Fred>]>\n
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has_keyLink to this heading#

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

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Python console
>>> Dog.objects.create(name="Rufus", data={"breed": "labrador"})\n>>> Dog.objects.create(name="Meg", data={"breed": "collie", "owner": "Bob"})\n\n>>> Dog.objects.filter(data__has_key="owner")\n<QuerySet [<Dog: Meg>]>\n
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has_any_keysLink to this heading#

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

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Python console
>>> Dog.objects.create(name="Rufus", data={"breed": "labrador"})\n>>> Dog.objects.create(name="Meg", data={"owner": "Bob"})\n>>> Dog.objects.create(name="Fred", data={})\n\n>>> Dog.objects.filter(data__has_any_keys=["owner", "breed"])\n<QuerySet [<Dog: Rufus>, <Dog: Meg>]>\n
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has_keysLink to this heading#

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

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Python console
>>> Dog.objects.create(name="Rufus", data={})\n>>> Dog.objects.create(name="Meg", data={"breed": "collie", "owner": "Bob"})\n\n>>> Dog.objects.filter(data__has_keys=["breed", "owner"])\n<QuerySet [<Dog: Meg>]>\n
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keysLink to this heading#

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

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Python console
>>> Dog.objects.create(name="Rufus", data={"toy": "bone"})\n>>> Dog.objects.create(name="Meg", data={"breed": "collie", "owner": "Bob"})\n\n>>> Dog.objects.filter(data__keys__overlap=["breed", "toy"])\n<QuerySet [<Dog: Rufus>, <Dog: Meg>]>\n
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valuesLink to this heading#

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

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Python console
>>> Dog.objects.create(name="Rufus", data={"breed": "labrador"})\n>>> Dog.objects.create(name="Meg", data={"breed": "collie", "owner": "Bob"})\n\n>>> Dog.objects.filter(data__values__contains=["collie"])\n<QuerySet [<Dog: Meg>]>\n
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Bidang JangkauanLink to this heading#

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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.

\n

All of the range fields translate to psycopg Range objects in Python, but also accept tuples as input if no bounds\ninformation is necessary. The default is lower bound included, upper bound\nexcluded, that is [) (see the PostgreSQL documentation for details about\ndifferent bounds). The default bounds can be changed for non-discrete range\nfields (DateTimeRangeField and DecimalRangeField) by using\nthe default_bounds argument.

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IntegerRangeFieldLink to this heading#

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\n
\nclass IntegerRangeField(**options)Link to this definition#
\n

Stores a range of integers. Based on an\nIntegerField. Represented by an int4range in\nthe database and a\ndjango.db.backends.postgresql.psycopg_any.NumericRange in Python.

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

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BigIntegerRangeFieldLink to this heading#

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\n
\nclass BigIntegerRangeField(**options)Link to this definition#
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Stores a range of large integers. Based on a\nBigIntegerField. Represented by an int8range\nin the database and a\ndjango.db.backends.postgresql.psycopg_any.NumericRange in Python.

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

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DecimalRangeFieldLink to this heading#

\n
\n
\nclass DecimalRangeField(default_bounds='[)', **options)Link to this definition#
\n

Stores a range of floating point values. Based on a\nDecimalField. Represented by a numrange in\nthe database and a\ndjango.db.backends.postgresql.psycopg_any.NumericRange in Python.

\n
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\ndefault_boundsLink to this definition#
\n

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

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DateTimeRangeFieldLink to this heading#

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\n
\nclass DateTimeRangeField(default_bounds='[)', **options)Link to this definition#
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Stores a range of timestamps. Based on a\nDateTimeField. Represented by a tstzrange in\nthe database and a\ndjango.db.backends.postgresql.psycopg_any.DateTimeTZRange in Python.

\n
\n
\ndefault_boundsLink to this definition#
\n

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

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DateRangeFieldLink to this heading#

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\n
\nclass DateRangeField(**options)Link to this definition#
\n

Stores a range of dates. Based on a\nDateField. Represented by a daterange in the\ndatabase and a django.db.backends.postgresql.psycopg_any.DateRange in\nPython.

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

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\n\n
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Meminta Jangkauan BidangLink to this heading#

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

\n
Code
from django.contrib.postgres.fields import IntegerRangeField\nfrom django.db import models\n\n\nclass Event(models.Model):\n    name = models.CharField(max_length=200)\n    ages = IntegerRangeField()\n    start = models.DateTimeField()\n\n    def __str__(self):\n        return self.name\n
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We will also use the following example objects:

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Python console
>>> import datetime\n>>> from django.utils import timezone\n>>> now = timezone.now()\n>>> Event.objects.create(name="Soft play", ages=(0, 10), start=now)\n>>> Event.objects.create(\n...     name="Pub trip", ages=(21, None), start=now - datetime.timedelta(days=1)\n... )\n
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dan NumericRange:

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Code
>>> from django.db.backends.postgresql.psycopg_any import NumericRange\n
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Fungsi-fungsi penahananLink to this heading#

\n

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

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containsLink to this heading#
\n
Code
>>> Event.objects.filter(ages__contains=NumericRange(4, 5))\n<QuerySet [<Event: Soft play>]>\n
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contained_byLink to this heading#
\n
Code
>>> Event.objects.filter(ages__contained_by=NumericRange(0, 15))\n<QuerySet [<Event: Soft play>]>\n
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The contained_by lookup is also available on the non-range field types:\nSmallAutoField,\nAutoField, BigAutoField,\nSmallIntegerField,\nIntegerField,\nBigIntegerField,\nDecimalField, FloatField,\nDateField, and\nDateTimeField. For example:

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Python console
>>> from django.db.backends.postgresql.psycopg_any import DateTimeTZRange\n>>> Event.objects.filter(\n...     start__contained_by=DateTimeTZRange(\n...         timezone.now() - datetime.timedelta(hours=1),\n...         timezone.now() + datetime.timedelta(hours=1),\n...     ),\n... )\n<QuerySet [<Event: Soft play>]>\n
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\n
overlapLink to this heading#
\n
Code
>>> Event.objects.filter(ages__overlap=NumericRange(8, 12))\n<QuerySet [<Event: Soft play>]>\n
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Fungsi perbandinganLink to this heading#

\n

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.

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\n
fully_ltLink to this heading#
\n

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

\n
Code
>>> Event.objects.filter(ages__fully_lt=NumericRange(11, 15))\n<QuerySet [<Event: Soft play>]>\n
\n
\n
\n
fully_gtLink to this heading#
\n

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

\n
Code
>>> Event.objects.filter(ages__fully_gt=NumericRange(11, 15))\n<QuerySet [<Event: Pub trip>]>\n
\n
\n
\n
not_ltLink to this heading#
\n

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

\n
Code
>>> Event.objects.filter(ages__not_lt=NumericRange(0, 15))\n<QuerySet [<Event: Soft play>, <Event: Pub trip>]>\n
\n
\n
\n
not_gtLink to this heading#
\n

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

\n
Code
>>> Event.objects.filter(ages__not_gt=NumericRange(3, 10))\n<QuerySet [<Event: Soft play>]>\n
\n
\n
\n
adjacent_toLink to this heading#
\n

Jangkauan dikembalikan berbagi sebuah batasan dengan jangkauan dilewatkan.

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

Meminta menggunakan batasanLink to this heading#

\n

Range fields support several extra lookups.

\n
\n
startswithLink to this heading#
\n

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

\n
Code
>>> Event.objects.filter(ages__startswith=21)\n<QuerySet [<Event: Pub trip>]>\n
\n
\n
\n
endswithLink to this heading#
\n

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

\n
Code
>>> Event.objects.filter(ages__endswith=10)\n<QuerySet [<Event: Soft play>]>\n
\n
\n
\n
isemptyLink to this heading#
\n

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

\n
Code
>>> Event.objects.filter(ages__isempty=True)\n<QuerySet []>\n
\n
\n
\n
lower_incLink to this heading#
\n

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

\n
Code
>>> Event.objects.filter(ages__lower_inc=True)\n<QuerySet [<Event: Soft play>, <Event: Pub trip>]>\n
\n
\n
\n
lower_infLink to this heading#
\n

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

\n
Code
>>> Event.objects.filter(ages__lower_inf=True)\n<QuerySet []>\n
\n
\n
\n
upper_incLink to this heading#
\n

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

\n
Code
>>> Event.objects.filter(ages__upper_inc=True)\n<QuerySet []>\n
\n
\n
\n
upper_infLink to this heading#
\n

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

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

Menentukan jenis jangkauan anda sendiriLink to this heading#

\n

PostgreSQL allows the definition of custom range types. Django's model and form\nfield implementations use base classes below, and psycopg provides a\nregister_range() to allow use of custom\nrange types.

\n
\n
\nclass RangeField(**options)Link to this definition#
\n

Kelas dasar untuk bidang jangkauan model.

\n
\n
\nbase_fieldLink to this definition#
\n

Kelas bidang model digunakan.

\n
\n\n
\n
\nrange_typeLink to this definition#
\n

The range type to use.

\n
\n\n
\n
\nform_fieldLink to this definition#
\n

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

\n
\n\n
\n\n
\n
\nclass django.contrib.postgres.forms.BaseRangeFieldLink to this definition#
\n

Kelas dasar untuk formulir bidang jangkauan.

\n
\n
\nbase_fieldLink to this definition#
\n

Bidang formulir digunakan.

\n
\n\n
\n
\nrange_typeLink to this definition#
\n

The range type to use.

\n
\n\n
\n\n
\n
\n

Range operatorsLink to this heading#

\n
\n
\nclass RangeOperatorsLink to this definition#
\n
\n\n

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

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

Pernyataan RangeBoundary()Link to this heading#

\n
\n
\nclass RangeBoundary(inclusive_lower=True, inclusive_upper=False)Link to this definition#
\n
\n
\ninclusive_lowerLink to this definition#
\n

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

\n
\n\n
\n
\ninclusive_upperLink to this definition#
\n

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

\n
\n\n
\n\n

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

\n
\n
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