> — Russell Keith-Magee, [Django users group][cite]
Serializers allow complex data such as querysets and model instances to be converted to native python datatypes that can then be easily rendered into `JSON`, `XML` or other content types. Serializers also provide deserialization, allowing parsed data to be converted back into complex types, after first validating the incoming data.
REST framework's serializers work very similarly to Django's `Form` and `ModelForm` classes. It provides a `Serializer` class which gives you a powerful, generic way to control the output of your responses, as well as a `ModelSerializer` class which provides a useful shortcut for creating serializers that deal with model instances and querysets.
## Declaring Serializers
Let's start by creating a simple object we can use for example purposes:
The first part of serializer class defines the fields that get serialized/deserialized. The `restore_object` method defines how fully fledged instances get created when deserializing data.
The `restore_object` method is optional, and is only required if we want our serializer to support deserialization into fully fledged object instances. If we don't define this method, then deserializing data will simply return a dictionary of items.
We can now use `CommentSerializer` to serialize a comment, or list of comments. Again, using the `Serializer` class looks a lot like using a `Form` class.
By default, serializers must be passed values for all required fields or they will throw validation errors. You can use the `partial` argument in order to allow partial updates.
serializer = CommentSerializer(comment, data={'content': u'foo bar'}, partial=True) # Update `instance` with partial data
When deserializing data, you always need to call `is_valid()` before attempting to access the deserialized object. If any validation errors occur, the `.errors` property will contain a dictionary representing the resulting error messages. For example:
Each key in the dictionary will be the field name, and the values will be lists of strings of any error messages corresponding to that field. The `non_field_errors` key may also be present, and will list any general validation errors.
You can specify custom field-level validation by adding `.validate_<fieldname>` methods to your `Serializer` subclass. These are analagous to `.clean_<fieldname>` methods on Django forms, but accept slightly different arguments.
They take a dictionary of deserialized attributes as a first argument, and the field name in that dictionary as a second argument (which will be either the name of the field or the value of the `source` argument to the field, if one was provided).
Your `validate_<fieldname>` methods should either just return the `attrs` dictionary or raise a `ValidationError`. For example:
To do any other validation that requires access to multiple fields, add a method called `.validate()` to your `Serializer` subclass. This method takes a single argument, which is the `attrs` dictionary. It should raise a `ValidationError` if necessary, or just return `attrs`. For example:
To save the deserialized objects created by a serializer, call the `.save()` method:
if serializer.is_valid():
serializer.save()
The default behavior of the method is to simply call `.save()` on the deserialized object instance. You can override the default save behaviour by overriding the `.save_object(obj)` method on the serializer class.
The previous examples are fine for dealing with objects that only have simple datatypes, but sometimes we also need to be able to represent more complex objects, where some of the attributes of an object might not be simple datatypes such as strings, dates or integers.
**Note**: Nested serializers are only suitable for read-only representations, as there are cases where they would have ambiguous or non-obvious behavior if used when updating instances. For read-write representations you should always use a flat representation, by using one of the `RelatedField` subclasses.
To serialize a queryset or list of objects instead of a single object instance, you should pass the `many=True` flag when instantiating the serializer. You can then pass a queryset or list of objects to be serialized.
To deserialize a list of object data, and create multiple object instances in a single pass, you should also set the `many=True` flag, and pass a list of data to be deserialized.
When performing a bulk update you may want to allow new items to be created, and missing items to be deleted. To do so, pass `allow_add_remove=True` to the serializer.
Passing `allow_add_remove=True` ensures that any update operations will completely overwrite the existing queryset, rather than simply updating existing objects.
Performing a bulk update is slightly more complicated than performing a bulk creation, because the serializer needs a way to determine how the items in the incoming data should be matched against the existing object instances.
By default the serializer class will use the `id` key on the incoming data to determine the canonical identity of an object. If you need to change this behavior you should override the `get_identity` method on the `Serializer` class. For example:
To map the incoming data items to their corresponding object instances, the `.get_identity()` method will be called both against the incoming data, and against the serialized representation of the existing objects.
## Including extra context
There are some cases where you need to provide extra context to the serializer in addition to the object being serialized. One common case is if you're using a serializer that includes hyperlinked relations, which requires the serializer to have access to the current request so that it can properly generate fully qualified URLs.
You can provide arbitrary additional context by passing a `context` argument when instantiating the serializer. For example:
The context dictionary can be used within any serializer field logic, such as a custom `.to_native()` method, by accessing the `self.context` attribute.
By default, all the model fields on the class will be mapped to corresponding serializer fields.
Any foreign keys on the model will be mapped to `PrimaryKeyRelatedField` if you're using a `ModelSerializer`, or `HyperlinkedRelatedField` if you're using a `HyperlinkedModelSerializer`.
You can add extra fields to a `ModelSerializer` or override the default fields by declaring fields on the class, just as you would for a `Serializer` class.
When serializing model instances, there are a number of different ways you might choose to represent relationships. The default representation for `ModelSerializer` is to use the primary keys of the related instances.
Alternative representations include serializing using hyperlinks, serializing complete nested representations, or serializing with a custom representation.
If you only want a subset of the default fields to be used in a model serializer, you can do so using `fields` or `exclude` options, just as you would with a `ModelForm`.
The `depth` option should be set to an integer value that indicates the depth of relationships that should be traversed before reverting to a flat representation.
You may wish to specify multiple fields as read-only. Instead of adding each field explicitely with the `read_only=True` attribute, you may use the `read_only_fields` Meta option, like so:
class AccountSerializer(serializers.ModelSerializer):
You can create customized subclasses of `ModelSerializer` that use a different set of default fields for the representation, by overriding various `get_<field_type>_field` methods.
Returns the field instance that should be used to represent a related field when `depth` is not specified, or when nested representations are being used and the depth reaches zero.
### get_field
**Signature**: `.get_field(self, model_field)`
Returns the field instance that should be used for non-relational, non-pk fields.
### Example:
The following custom model serializer could be used as a base class for model serializers that should always exclude the pk by default.
class NoPKModelSerializer(serializers.ModelSerializer):
