15 KiB
Serializers
Expanding the usefulness of the serializers is something that we would like to address. However, it's not a trivial problem, and it will take some serious design work.
— Russell Keith-Magee, Django users group
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:
class Comment(object):
def __init__(self, email, content, created=None):
self.email = email
self.content = content
self.created = created or datetime.datetime.now()
comment = Comment(email='leila@example.com', content='foo bar')
We'll declare a serializer that we can use to serialize and deserialize Comment objects.
Declaring a serializer looks very similar to declaring a form:
class CommentSerializer(serializers.Serializer):
email = serializers.EmailField()
content = serializers.CharField(max_length=200)
created = serializers.DateTimeField()
def restore_object(self, attrs, instance=None):
if instance is not None:
instance.title = attrs['title']
instance.content = attrs['content']
instance.created = attrs['created']
return instance
return Comment(**attrs)
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.
Serializing objects
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.
serializer = CommentSerializer(comment)
serializer.data
# {'email': u'leila@example.com', 'content': u'foo bar', 'created': datetime.datetime(2012, 8, 22, 16, 20, 9, 822774)}
At this point we've translated the model instance into python native datatypes. To finalise the serialization process we render the data into json.
stream = JSONRenderer().render(data)
stream
# '{"email": "leila@example.com", "content": "foo bar", "created": "2012-08-22T16:20:09.822"}'
Deserializing objects
Deserialization is similar. First we parse a stream into python native datatypes...
data = JSONParser().parse(stream)
...then we restore those native datatypes into a fully populated object instance.
serializer = CommentSerializer(data=data)
serializer.is_valid()
# True
serializer.object
# <Comment object at 0x10633b2d0>
>>> serializer.deserialize('json', stream)
When deserializing data, we can either create a new instance, or update an existing instance.
serializer = CommentSerializer(data=data) # Create new instance
serializer = CommentSerializer(comment, data=data) # Update `instance`
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
Serializing querysets
To serialize a queryset instead of an object instance, you should pass the many=True flag when instantiating the serializer.
queryset = Comment.objects.all()
serializer = CommentSerializer(queryset, many=True)
serializer.data
# [{'email': u'leila@example.com', 'content': u'foo bar', 'created': datetime.datetime(2012, 8, 22, 16, 20, 9, 822774)}, {'email': u'jamie@example.com', 'content': u'baz', 'created': datetime.datetime(2013, 1, 12, 16, 12, 45, 104445)}]
Validation
When deserializing data, you always need to call is_valid() before attempting to access the deserialized object. If any validation errors occur, the .errors and .non_field_errors properties will contain the resulting error messages.
Field-level validation
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:
from rest_framework import serializers
class BlogPostSerializer(serializers.Serializer):
title = serializers.CharField(max_length=100)
content = serializers.CharField()
def validate_title(self, attrs, source):
"""
Check that the blog post is about Django.
"""
value = attrs[source]
if "django" not in value.lower():
raise serializers.ValidationError("Blog post is not about Django")
return attrs
Object-level validation
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:
from rest_framework import serializers
class EventSerializer(serializers.Serializer):
description = serializers.CharField(max_length=100)
start = serializers.DateTimeField()
finish = serializers.DateTimeField()
def validate(self, attrs):
"""
Check that the start is before the stop.
"""
if attrs['start'] < attrs['finish']:
raise serializers.ValidationError("finish must occur after start")
return attrs
Saving object state
Serializers also include a .save() method that you can override if you want to provide a method of persisting the state of a deserialized object. The default behavior of the method is to simply call .save() on the deserialized object instance.
The generic views provided by REST framework call the .save() method when updating or creating entities.
Dealing with nested objects
The previous example is 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.
The Serializer class is itself a type of Field, and can be used to represent relationships where one object type is nested inside another.
class UserSerializer(serializers.Serializer):
email = serializers.Field()
username = serializers.Field()
class CommentSerializer(serializers.Serializer):
user = UserSerializer()
title = serializers.Field()
content = serializers.Field()
created = serializers.Field()
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.
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:
serializer = AccountSerializer(account, context={'request': request})
serializer.data
# {'id': 6, 'owner': u'denvercoder9', 'created': datetime.datetime(2013, 2, 12, 09, 44, 56, 678870), 'details': 'http://example.com/accounts/6/details'}
The context dictionary can be used within any serializer field logic, such as a custom .to_native() method, by accessing the self.context attribute.
Creating custom fields
If you want to create a custom field, you'll probably want to override either one or both of the .to_native() and .from_native() methods. These two methods are used to convert between the intial datatype, and a primative, serializable datatype. Primative datatypes may be any of a number, string, date/time/datetime or None. They may also be any list or dictionary like object that only contains other primative objects.
The .to_native() method is called to convert the initial datatype into a primative, serializable datatype. The from_native() method is called to restore a primative datatype into it's initial representation.
Let's look at an example of serializing a class that represents an RGB color value:
class Color(object):
"""
A color represented in the RGB colorspace.
"""
def __init__(self, red, green, blue):
assert(red >= 0 and green >= 0 and blue >= 0)
assert(red < 256 and green < 256 and blue < 256)
self.red, self.green, self.blue = red, green, blue
class ColourField(serializers.WritableField):
"""
Color objects are serialized into "rgb(#, #, #)" notation.
"""
def to_native(self, obj):
return "rgb(%d, %d, %d)" % (obj.red, obj.green, obj.blue)
def from_native(self, data):
data = data.strip('rgb(').rstrip(')')
red, green, blue = [int(col) for col in data.split(',')]
return Color(red, green, blue)
By default field values are treated as mapping to an attribute on the object. If you need to customize how the field value is accessed and set you need to override .field_to_native() and/or .field_from_native().
As an example, let's create a field that can be used represent the class name of the object being serialized:
class ClassNameField(serializers.Field):
def field_to_native(self, obj, field_name):
"""
Serialize the object's class name.
"""
return obj.__class__
ModelSerializers
Often you'll want serializer classes that map closely to model definitions.
The ModelSerializer class lets you automatically create a Serializer class with fields that correspond to the Model fields.
class AccountSerializer(serializers.ModelSerializer):
class Meta:
model = Account
[TODO: Explain model field to serializer field mapping in more detail]
Specifying fields explicitly
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.
class AccountSerializer(serializers.ModelSerializer):
url = CharField(source='get_absolute_url', read_only=True)
group = NaturalKeyField()
class Meta:
model = Account
Extra fields can correspond to any property or callable on the model.
Relational fields
When serializing model instances, there are a number of different ways you might choose to represent relationships. The default representation is to use the primary keys of the related instances.
Alternative representations include serializing using natural keys, serializing complete nested representations, or serializing using a custom representation, such as a URL that uniquely identifies the model instances.
The PrimaryKeyRelatedField and HyperlinkedRelatedField fields provide alternative flat representations.
The ModelSerializer class can itself be used as a field, in order to serialize relationships using nested representations.
The RelatedField class may be subclassed to create a custom representation of a relationship. The subclass should override .to_native(), and optionally .from_native() if deserialization is supported.
All the relational fields may be used for any relationship or reverse relationship on a model.
Specifying which fields should be included
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.
For example:
class AccountSerializer(serializers.ModelSerializer):
class Meta:
model = Account
exclude = ('id',)
Specifiying nested serialization
The default ModelSerializer uses primary keys for relationships, but you can also easily generate nested representations using the depth option:
class AccountSerializer(serializers.ModelSerializer):
class Meta:
model = Account
exclude = ('id',)
depth = 1
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.
Specifying which fields should be read-only
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):
class Meta:
model = Account
read_only_fields = ('created', 'modified')
Customising the default fields
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.
Each of these methods may either return a field or serializer instance, or None.
get_pk_field
Signature: .get_pk_field(self, model_field)
Returns the field instance that should be used to represent the pk field.
get_nested_field
Signature: .get_nested_field(self, model_field)
Returns the field instance that should be used to represent a related field when depth is specified as being non-zero.
get_related_field
Signature: .get_related_field(self, model_field, to_many=False)
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):
def get_pk_field(self, model_field):
return None