class JSONField ( encoder = None , ** options )

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 .


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 datetime s.

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 .


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 .

Querying JSONField

We will use the following example model:

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

Key, index, and path lookups

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

>>> Dog.objects.create(name='Rufus', data={
...     'breed': 'labrador',
...     'owner': {
...         'name': 'Bob',
...         'other_pets': [{
...             'name': 'Fishy',
...         }],
...     },
... })
>>> Dog.objects.create(name='Meg', data={'breed': 'collie', 'owner': None})

>>> 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>]>

If the key is an integer, it will be interpreted as an index lookup in an array:

>>> 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.

To query for null in JSON data, use None as a value:

>>> Dog.objects.filter(data__owner=None)
<QuerySet [<Dog: Meg>]>

To query for missing keys, use the isnull lookup:

>>> Dog.objects.create(name='Shep', data={'breed': 'collie'})
>>> Dog.objects.filter(data__owner__isnull=True)
<QuerySet [<Dog: Shep>]>


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.