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serializers.py

Serializers

我们希望给序列化器扩展一些行之有效的功能。 虽然这是一个小问题，但需要我们认真对待。

— Russell Keith-Magee, Django users group

序列化器的作用是将复杂的数据结构（如，Queryset对象或者模型对象object）转换为Python内置的基本数据类型（如，列表或者字典）,这样转换之后方便将数据序列化为JSON，XML以及其他格式的数据。 序列化器还提供反序列化功能，前端传过来的数据先经过校验，然后可以反序列化成复杂的数据类型交给后端保存。

REST框架中的序列化器的工作方式与Django的Form和ModelForm类非常相似。 我们提供了一个Serializer类，它为您提供了一种强大的通用方法来控制响应的输出，还提供了一个ModelSerializer类，该类为创建序列化程序提供了有用的快捷方式，处理模型实例和查询集。

Declaring Serializers

让我们开始创建一个简单的对象，我们可以将其用于示例目的：

from datetime import datetime

class Comment(object):
    def __init__(self, email, content, created=None):
        self.email = email
        self.content = content
        self.created = created or datetime.now()

comment = Comment(email='leila@example.com', content='foo bar')

我们将声明一个序列化程序，可用于序列化和反序列化与Comment对象相对应的数据。

声明序列化器看起来与声明表单非常相似：

from rest_framework import serializers

class CommentSerializer(serializers.Serializer):
    email = serializers.EmailField()
    content = serializers.CharField(max_length=200)
    created = serializers.DateTimeField()

序列化对象

我们现在可以使用CommentSerializer来序列化注释或注释列表。 同样，使用Serializer类看起来很像使用Form类。

serializer = CommentSerializer(comment)
serializer.data
# {'email': 'leila@example.com', 'content': 'foo bar', 'created': '2016-01-27T15:17:10.375877'}

此时我们已将模型实例转换为Python内置的基本数据类型。 为了完成序列化过程，我们将数据转化为为json。

from rest_framework.renderers import JSONRenderer

json = JSONRenderer().render(serializer.data)
json
# b'{"email":"leila@example.com","content":"foo bar","created":"2016-01-27T15:17:10.375877"}'

Deserializing objects

反序列化是流程是类似的。 首先，我们将数据流解析为Python内置基本数据类型。

from django.utils.six import BytesIO
from rest_framework.parsers import JSONParser

stream = BytesIO(json)
data = JSONParser().parse(stream)

...然后我们将这些基本数据（验证之后是有效的数据）保存在字典中。

serializer = CommentSerializer(data=data)
serializer.is_valid()
# True
serializer.validated_data
# {'content': 'foo bar', 'email': 'leila@example.com', 'created': datetime.datetime(2012, 08, 22, 16, 20, 09, 822243)}

保存实例

如果我们希望能够根据验证数据返回完整的对象实例，我们需要重写.create()和.update()方法中的一个或两个。 For example:

class CommentSerializer(serializers.Serializer):
    email = serializers.EmailField()
    content = serializers.CharField(max_length=200)
    created = serializers.DateTimeField()

    def create(self, validated_data):
        return Comment(**validated_data)

    def update(self, instance, validated_data):
        instance.email = validated_data.get('email', instance.email)
        instance.content = validated_data.get('content', instance.content)
        instance.created = validated_data.get('created', instance.created)
        return instance

如果您的对象实例对应于Django的ORM模型，您还需要确保这些方法将对象保存到数据库。 例如，如果Comment是Django模型，则方法可能如下所示：

    def create(self, validated_data):
        return Comment.objects.create(**validated_data)

    def update(self, instance, validated_data):
        instance.email = validated_data.get('email', instance.email)
        instance.content = validated_data.get('content', instance.content)
        instance.created = validated_data.get('created', instance.created)
        instance.save()
        return instance

现在，在反序列化数据时，我们可以调用.save()，根据验证的数据返回一个对象实例。

comment = serializer.save()

调用.save()将创建一个新实例，或者更新一个现有实例，这主要取决于在实例化序列化类时是否传递了一个实例对象：

# .save() will create a new instance.
serializer = CommentSerializer(data=data)

# .save() will update the existing `comment` instance.
serializer = CommentSerializer(comment, data=data)

.create()和.update()方法都是可选的。 根据序列化类的用例，您既可以实现它们之一，也可以两者都不实现。

将其他属性传递给.save()

有时，您希望视图代码能够在保存实例时注入其他数据。 这些附加数据可能包括诸如当前用户，当前时间或不属于请求数据一部分的任何其他信息。

在调用.save()方法时可以通过关键字参数传进来一些其他参数。 For example:

serializer.save(owner=request.user)

调用.create()或.update()时，validated_data参数中包含那些通过关键字参数传进来的其他参数。

直接重写.save()方法.

在某些情况下，.create()和.update()方法名称可能没有意义。 例如，在联系表格中，我们可能没有创建新实例，而是发送了电子邮件或其他消息。

在这些情况下，您可能会选择直接重写.save()，因为它更具可读性和意义。

For example:

class ContactForm(serializers.Serializer):
    email = serializers.EmailField()
    message = serializers.CharField()

    def save(self):
        email = self.validated_data['email']
        message = self.validated_data['message']
        send_email(from=email, message=message)

请注意，在上述情况下，我们必须直接操作修改序列化器的.validated_data属性。

Validation

在反序列化数据时，在尝试访问经过验证的数据或保存对象实例之前，始终需要调用is_valid()。 如果发生任何验证错误，.errors属性将包含表示结果错误消息的字典。 For example:

serializer = CommentSerializer(data={'email': 'foobar', 'content': 'baz'})
serializer.is_valid()
# False
serializer.errors
# {'email': [u'Enter a valid e-mail address.'], 'created': [u'This field is required.']}

词典中的每个键将是字段名称，值是一个列表，存放该字段的校验失败错误信息。 non_field_errors键也可能存在，并将列出所有常规验证错误。 可以使用NON_FIELD_ERRORS_KEY REST框架设置来自定义non_field_errors项的名称。

对一个列表做反序列化时，错误信息为被放置在一个列表中，列表中每个元素是一个字典，字典的键是原列表的元素，字典的值是该元素的错误信息。

Raising an exception on invalid data

.is_valid()方法采用可选的raise_exception标志，如果存在验证错误，它将导致引发serializers.ValidationError异常。

These exceptions are automatically dealt with by the default exception handler that REST framework provides, and will return HTTP 400 Bad Request responses by default.

# Return a 400 response if the data was invalid.
serializer.is_valid(raise_exception=True)

Field-level validation

You can specify custom field-level validation by adding .validate_<field_name> methods to your Serializer subclass. These are similar to the .clean_<field_name> methods on Django forms.

These methods take a single argument, which is the field value that requires validation.

Your validate_<field_name> methods should return the validated value or raise a serializers.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, value):
        """
        Check that the blog post is about Django.
        """
        if 'django' not in value.lower():
            raise serializers.ValidationError("Blog post is not about Django")
        return value

Note: If your <field_name> is declared on your serializer with the parameter required=False then this validation step will not take place if the field is not included.

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 a dictionary of field values. It should raise a serializers.ValidationError if necessary, or just return the validated values. 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, data):
        """
        Check that the start is before the stop.
        """
        if data['start'] > data['finish']:
            raise serializers.ValidationError("finish must occur after start")
        return data

Validators

Individual fields on a serializer can include validators, by declaring them on the field instance, for example:

def multiple_of_ten(value):
    if value % 10 != 0:
        raise serializers.ValidationError('Not a multiple of ten')

class GameRecord(serializers.Serializer):
    score = IntegerField(validators=[multiple_of_ten])
    ...

Serializer classes can also include reusable validators that are applied to the complete set of field data. These validators are included by declaring them on an inner Meta class, like so:

class EventSerializer(serializers.Serializer):
    name = serializers.CharField()
    room_number = serializers.IntegerField(choices=[101, 102, 103, 201])
    date = serializers.DateField()

    class Meta:
        # Each room only has one event per day.
        validators = UniqueTogetherValidator(
            queryset=Event.objects.all(),
            fields=['room_number', 'date']
        )

For more information see the validators documentation.

访问初始数据和实例

When passing an initial object or queryset to a serializer instance, the object will be made available as .instance. If no initial object is passed then the .instance attribute will be None.

When passing data to a serializer instance, the unmodified data will be made available as .initial_data. If the data keyword argument is not passed then the .initial_data attribute will not exist.

部分更新

默认情况下，序列化程序必须传递所有必填字段的值，否则会引发验证错误。 You can use the partial argument in order to allow partial updates.

# Update `comment` with partial data
serializer = CommentSerializer(comment, data={'content': u'foo bar'}, partial=True)

Dealing with nested objects

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.

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.EmailField()
    username = serializers.CharField(max_length=100)

class CommentSerializer(serializers.Serializer):
    user = UserSerializer()
    content = serializers.CharField(max_length=200)
    created = serializers.DateTimeField()

如果嵌套表示可以选择接受None值，则应将required = False标志传递给嵌套序列化器。

class CommentSerializer(serializers.Serializer):
    user = UserSerializer(required=False)  # May be an anonymous user.
    content = serializers.CharField(max_length=200)
    created = serializers.DateTimeField()

同样，如果嵌套表示形式应为项目列表，则应将many = True标志传递给嵌套的序列化序列。

class CommentSerializer(serializers.Serializer):
    user = UserSerializer(required=False)
    edits = EditItemSerializer(many=True)  # A nested list of 'edit' items.
    content = serializers.CharField(max_length=200)
    created = serializers.DateTimeField()

Writable nested representations

When dealing with nested representations that support deserializing the data, any errors with nested objects will be nested under the field name of the nested object.

serializer = CommentSerializer(data={'user': {'email': 'foobar', 'username': 'doe'}, 'content': 'baz'})
serializer.is_valid()
# False
serializer.errors
# {'user': {'email': [u'Enter a valid e-mail address.']}, 'created': [u'This field is required.']}

同样，.validated_data属性将包含嵌套的数据结构。

Writing .create() methods for nested representations

If you're supporting writable nested representations you'll need to write .create() or .update() methods that handle saving multiple objects.

The following example demonstrates how you might handle creating a user with a nested profile object.

class UserSerializer(serializers.ModelSerializer):
    profile = ProfileSerializer()

    class Meta:
        model = User
        fields = ('username', 'email', 'profile')

    def create(self, validated_data):
        profile_data = validated_data.pop('profile')
        user = User.objects.create(**validated_data)
        Profile.objects.create(user=user, **profile_data)
        return user

Writing .update() methods for nested representations

For updates you'll want to think carefully about how to handle updates to relationships. For example if the data for the relationship is None, or not provided, which of the following should occur?

  • Set the relationship to NULL in the database.
  • Delete the associated instance.
  • Ignore the data and leave the instance as it is.
  • Raise a validation error.

Here's an example for an .update() method on our previous UserSerializer class.

    def update(self, instance, validated_data):
        profile_data = validated_data.pop('profile')
        # Unless the application properly enforces that this field is
        # always set, the follow could raise a `DoesNotExist`, which
        # would need to be handled.
        profile = instance.profile

        instance.username = validated_data.get('username', instance.username)
        instance.email = validated_data.get('email', instance.email)
        instance.save()

        profile.is_premium_member = profile_data.get(
            'is_premium_member',
            profile.is_premium_member
        )
        profile.has_support_contract = profile_data.get(
            'has_support_contract',
            profile.has_support_contract
         )
        profile.save()

        return instance

Because the behavior of nested creates and updates can be ambiguous, and may require complex dependencies between related models, REST framework 3 requires you to always write these methods explicitly. The default ModelSerializer .create() and .update() methods do not include support for writable nested representations.

There are however, third-party packages available such as DRF Writable Nested that support automatic writable nested representations.

An alternative to saving multiple related instances in the serializer is to write custom model manager classes that handle creating the correct instances.

For example, suppose we wanted to ensure that User instances and Profile instances are always created together as a pair. We might write a custom manager class that looks something like this:

class UserManager(models.Manager):
    ...

    def create(self, username, email, is_premium_member=False, has_support_contract=False):
        user = User(username=username, email=email)
        user.save()
        profile = Profile(
            user=user,
            is_premium_member=is_premium_member,
            has_support_contract=has_support_contract
        )
        profile.save()
        return user

This manager class now more nicely encapsulates that user instances and profile instances are always created at the same time. Our .create() method on the serializer class can now be re-written to use the new manager method.

def create(self, validated_data):
    return User.objects.create(
        username=validated_data['username'],
        email=validated_data['email']
        is_premium_member=validated_data['profile']['is_premium_member']
        has_support_contract=validated_data['profile']['has_support_contract']
    )

For more details on this approach see the Django documentation on model managers, and this blogpost on using model and manager classes.

Dealing with multiple objects

Serializer类还可以处理序列化或反序列化对象列表。

序列化多个对象

要序列化查询集或对象列表而不是单个对象实例，应在实例化序列化程序时传递many = True标志。 然后，您可以传递要序列化的查询集或对象列表。

queryset = Book.objects.all()
serializer = BookSerializer(queryset, many=True)
serializer.data
# [
#     {'id': 0, 'title': 'The electric kool-aid acid test', 'author': 'Tom Wolfe'},
#     {'id': 1, 'title': 'If this is a man', 'author': 'Primo Levi'},
#     {'id': 2, 'title': 'The wind-up bird chronicle', 'author': 'Haruki Murakami'}
# ]

Deserializing multiple objects

反序列化多个对象的默认行为是支持多个对象创建，但不支持多个对象更新。 For more information on how to support or customize either of these cases, see the ListSerializer documentation below.

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_representation() method, by accessing the self.context attribute.

ModelSerializer

通常，您需要与Django模型定义紧密相关的序列化程序类。

ModelSerializer类提供了一个快捷方式，允许您使用与“模型”字段对应的字段自动创建Serializer类。

The ModelSerializer class is the same as a regular Serializer class, except that:

  • 它将根据模型自动为您生成一组字段。
  • 它将自动为序列化器生成验证器，例如unique_together验证器。
  • 它包括.create()和.update()的简单默认实现。

Declaring a ModelSerializer looks like this:

class AccountSerializer(serializers.ModelSerializer):
    class Meta:
        model = Account
        fields = ('id', 'account_name', 'users', 'created')

默认情况下，类上的所有模型字段都将映射到相应的序列化程序字段。

模型上的任何关系（如外键）都将映射到PrimaryKeyRelatedField。 默认情况下不包括反向关系，除非明确包含在serializer relations文档中指定的内容。

Inspecting a ModelSerializer

Serializer类生成有用的详细表示字符串，允许您完全检查其字段的状态。 This is particularly useful when working with ModelSerializers where you want to determine what set of fields and validators are being automatically created for you.

To do so, open the Django shell, using python manage.py shell, then import the serializer class, instantiate it, and print the object representation…

>>> from myapp.serializers import AccountSerializer
>>> serializer = AccountSerializer()
>>> print(repr(serializer))
AccountSerializer():
    id = IntegerField(label='ID', read_only=True)
    name = CharField(allow_blank=True, max_length=100, required=False)
    owner = PrimaryKeyRelatedField(queryset=User.objects.all())

指定要包含的字段

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. It is strongly recommended that you explicitly set all fields that should be serialized using the fields attribute. This will make it less likely to result in unintentionally exposing data when your models change.

For example:

class AccountSerializer(serializers.ModelSerializer):
    class Meta:
        model = Account
        fields = ('id', 'account_name', 'users', 'created')

You can also set the fields attribute to the special value '__all__' to indicate that all fields in the model should be used.

For example:

class AccountSerializer(serializers.ModelSerializer):
    class Meta:
        model = Account
        fields = '__all__'

You can set the exclude attribute to a list of fields to be excluded from the serializer.

For example:

class AccountSerializer(serializers.ModelSerializer):
    class Meta:
        model = Account
        exclude = ('users',)

In the example above, if the Account model had 3 fields account_name, users, and created, this will result in the fields account_name and created to be serialized.

The names in the fields and exclude attributes will normally map to model fields on the model class.

Alternatively names in the fields options can map to properties or methods which take no arguments that exist on the model class.

Since version 3.3.0, it is mandatory to provide one of the attributes fields or exclude.

Specifying nested serialization

默认ModelSerializer使用主键进行关系，但您也可以使用depth选项轻松生成嵌套表示：

class AccountSerializer(serializers.ModelSerializer):
    class Meta:
        model = Account
        fields = ('id', 'account_name', 'users', 'created')
        depth = 1

depth选项应设置为一个整数值，该值指示在还原为平面表示之前应该遍历的关系深度。

如果要自定义序列化的方式，则需要自己定义字段。

Specifying fields explicitly

您可以向ModelSerializer添加额外的字段，也可以通过在类上声明字段来覆盖默认字段，就像对Serializer类一样。

class AccountSerializer(serializers.ModelSerializer):
    url = serializers.CharField(source='get_absolute_url', read_only=True)
    groups = serializers.PrimaryKeyRelatedField(many=True)

    class Meta:
        model = Account

多余的字段可以对应于模型中的任何属性或可调用的字段。

Specifying read only fields

You may wish to specify multiple fields as read-only. Instead of adding each field explicitly with the read_only=True attribute, you may use the shortcut Meta option, read_only_fields.

This option should be a list or tuple of field names, and is declared as follows:

class AccountSerializer(serializers.ModelSerializer):
    class Meta:
        model = Account
        fields = ('id', 'account_name', 'users', 'created')
        read_only_fields = ('account_name',)

Model fields which have editable=False set, and AutoField fields will be set to read-only by default, and do not need to be added to the read_only_fields option.

Note: There is a special-case where a read-only field is part of a unique_together constraint at the model level. In this case the field is required by the serializer class in order to validate the constraint, but should also not be editable by the user.

The right way to deal with this is to specify the field explicitly on the serializer, providing both the read_only=True and default=… keyword arguments.

One example of this is a read-only relation to the currently authenticated User which is unique_together with another identifier. In this case you would declare the user field like so:

user = serializers.PrimaryKeyRelatedField(read_only=True, default=serializers.CurrentUserDefault())

Please review the Validators Documentation for details on the UniqueTogetherValidator and CurrentUserDefault classes.

Additional keyword arguments

还有一个快捷方式允许您使用extra_kwargs选项在字段上指定任意其他关键字参数。 与read_only_fields的情况一样，这意味着您不需要在序列化器上显式声明该字段。

此选项是一个字典，将字段名称映射到关键字参数字典。 For example:

class CreateUserSerializer(serializers.ModelSerializer):
    class Meta:
        model = User
        fields = ('email', 'username', 'password')
        extra_kwargs = {'password': {'write_only': True}}

    def create(self, validated_data):
        user = User(
            email=validated_data['email'],
            username=validated_data['username']
        )
        user.set_password(validated_data['password'])
        user.save()
        return user

Relational fields

序列化模型实例时，可以选择多种方式来表示关系。 ModelSerializer的默认表示是使用相关实例的主键。

其他表示形式包括使用超链接进行序列化，序列化完整的嵌套表示形式或使用自定义表示形式进行序列化。

有关完整的详细信息，请参见序列化器关系文档。

自定义字段映射

The ModelSerializer class also exposes an API that you can override in order to alter how serializer fields are automatically determined when instantiating the serializer.

Normally if a ModelSerializer does not generate the fields you need by default then you should either add them to the class explicitly, or simply use a regular Serializer class instead. However in some cases you may want to create a new base class that defines how the serializer fields are created for any given model.

.serializer_field_mapping

A mapping of Django model classes to REST framework serializer classes. You can override this mapping to alter the default serializer classes that should be used for each model class.

This property should be the serializer field class, that is used for relational fields by default.

For ModelSerializer this defaults to PrimaryKeyRelatedField.

For HyperlinkedModelSerializer this defaults to serializers.HyperlinkedRelatedField.

serializer_url_field

The serializer field class that should be used for any url field on the serializer.

Defaults to serializers.HyperlinkedIdentityField

serializer_choice_field

The serializer field class that should be used for any choice fields on the serializer.

Defaults to serializers.ChoiceField

The field_class and field_kwargs API

The following methods are called to determine the class and keyword arguments for each field that should be automatically included on the serializer. Each of these methods should return a two tuple of (field_class, field_kwargs).

.build_standard_field(self, field_name, model_field)

Called to generate a serializer field that maps to a standard model field.

The default implementation returns a serializer class based on the serializer_field_mapping attribute.

.build_relational_field(self, field_name, relation_info)

Called to generate a serializer field that maps to a relational model field.

The default implementation returns a serializer class based on the serializer_relational_field attribute.

The relation_info argument is a named tuple, that contains model_field, related_model, to_many and has_through_model properties.

.build_nested_field(self, field_name, relation_info, nested_depth)

Called to generate a serializer field that maps to a relational model field, when the depth option has been set.

The default implementation dynamically creates a nested serializer class based on either ModelSerializer or HyperlinkedModelSerializer.

The nested_depth will be the value of the depth option, minus one.

The relation_info argument is a named tuple, that contains model_field, related_model, to_many and has_through_model properties.

.build_property_field(self, field_name, model_class)

Called to generate a serializer field that maps to a property or zero-argument method on the model class.

The default implementation returns a ReadOnlyField class.

.build_url_field(self, field_name, model_class)

Called to generate a serializer field for the serializer's own url field. The default implementation returns a HyperlinkedIdentityField class.

.build_unknown_field(self, field_name, model_class)

Called when the field name did not map to any model field or model property. The default implementation raises an error, although subclasses may customize this behavior.

HyperlinkedModelSerializer

The HyperlinkedModelSerializer class is similar to the ModelSerializer class except that it uses hyperlinks to represent relationships, rather than primary keys.

By default the serializer will include a url field instead of a primary key field.

The url field will be represented using a HyperlinkedIdentityField serializer field, and any relationships on the model will be represented using a HyperlinkedRelatedField serializer field.

You can explicitly include the primary key by adding it to the fields option, for example:

class AccountSerializer(serializers.HyperlinkedModelSerializer):
    class Meta:
        model = Account
        fields = ('url', 'id', 'account_name', 'users', 'created')

Absolute and relative URLs

When instantiating a HyperlinkedModelSerializer you must include the current request in the serializer context, for example:

serializer = AccountSerializer(queryset, context={'request': request})

Doing so will ensure that the hyperlinks can include an appropriate hostname, so that the resulting representation uses fully qualified URLs, such as:

http://api.example.com/accounts/1/

Rather than relative URLs, such as:

/accounts/1/

If you do want to use relative URLs, you should explicitly pass {'request': None} in the serializer context.

How hyperlinked views are determined

There needs to be a way of determining which views should be used for hyperlinking to model instances.

By default hyperlinks are expected to correspond to a view name that matches the style '{model_name}-detail', and looks up the instance by a pk keyword argument.

You can override a URL field view name and lookup field by using either, or both of, the view_name and lookup_field options in the extra_kwargs setting, like so:

class AccountSerializer(serializers.HyperlinkedModelSerializer):
    class Meta:
        model = Account
        fields = ('account_url', 'account_name', 'users', 'created')
        extra_kwargs = {
            'url': {'view_name': 'accounts', 'lookup_field': 'account_name'},
            'users': {'lookup_field': 'username'}
        }

Alternatively you can set the fields on the serializer explicitly. For example:

class AccountSerializer(serializers.HyperlinkedModelSerializer):
    url = serializers.HyperlinkedIdentityField(
        view_name='accounts',
        lookup_field='slug'
    )
    users = serializers.HyperlinkedRelatedField(
        view_name='user-detail',
        lookup_field='username',
        many=True,
        read_only=True
    )

    class Meta:
        model = Account
        fields = ('url', 'account_name', 'users', 'created')

Tip: Properly matching together hyperlinked representations and your URL conf can sometimes be a bit fiddly. Printing the repr of a HyperlinkedModelSerializer instance is a particularly useful way to inspect exactly which view names and lookup fields the relationships are expected to map too.

Changing the URL field name

The name of the URL field defaults to 'url'. You can override this globally, by using the URL_FIELD_NAME setting.

ListSerializer

The ListSerializer class provides the behavior for serializing and validating multiple objects at once. You won't typically need to use ListSerializer directly, but should instead simply pass many=True when instantiating a serializer.

When a serializer is instantiated and many=True is passed, a ListSerializer instance will be created. The serializer class then becomes a child of the parent ListSerializer

The following argument can also be passed to a ListSerializer field or a serializer that is passed many=True:

allow_empty

This is True by default, but can be set to False if you want to disallow empty lists as valid input.

Customizing ListSerializer behavior

There are a few use cases when you might want to customize the ListSerializer behavior. For example:

  • You want to provide particular validation of the lists, such as checking that one element does not conflict with another element in a list.
  • You want to customize the create or update behavior of multiple objects.

For these cases you can modify the class that is used when many=True is passed, by using the list_serializer_class option on the serializer Meta class.

For example:

class CustomListSerializer(serializers.ListSerializer):
    ...

class CustomSerializer(serializers.Serializer):
    ...
    class Meta:
        list_serializer_class = CustomListSerializer

Customizing multiple create

The default implementation for multiple object creation is to simply call .create() for each item in the list. If you want to customize this behavior, you'll need to customize the .create() method on ListSerializer class that is used when many=True is passed.

For example:

class BookListSerializer(serializers.ListSerializer):
    def create(self, validated_data):
        books = [Book(**item) for item in validated_data]
        return Book.objects.bulk_create(books)

class BookSerializer(serializers.Serializer):
    ...
    class Meta:
        list_serializer_class = BookListSerializer

Customizing multiple update

By default the ListSerializer class does not support multiple updates. This is because the behavior that should be expected for insertions and deletions is ambiguous.

To support multiple updates you'll need to do so explicitly. When writing your multiple update code make sure to keep the following in mind:

  • How do you determine which instance should be updated for each item in the list of data?
  • How should insertions be handled? Are they invalid, or do they create new objects?
  • How should removals be handled? Do they imply object deletion, or removing a relationship? Should they be silently ignored, or are they invalid?
  • How should ordering be handled? Does changing the position of two items imply any state change or is it ignored?

You will need to add an explicit id field to the instance serializer. The default implicitly-generated id field is marked as read_only. This causes it to be removed on updates. Once you declare it explicitly, it will be available in the list serializer's update method.

Here's an example of how you might choose to implement multiple updates:

class BookListSerializer(serializers.ListSerializer):
    def update(self, instance, validated_data):
        # Maps for id->instance and id->data item.
        book_mapping = {book.id: book for book in instance}
        data_mapping = {item['id']: item for item in validated_data}

        # Perform creations and updates.
        ret = []
        for book_id, data in data_mapping.items():
            book = book_mapping.get(book_id, None)
            if book is None:
                ret.append(self.child.create(data))
            else:
                ret.append(self.child.update(book, data))

        # Perform deletions.
        for book_id, book in book_mapping.items():
            if book_id not in data_mapping:
                book.delete()

        return ret

class BookSerializer(serializers.Serializer):
    # We need to identify elements in the list using their primary key,
    # so use a writable field here, rather than the default which would be read-only.
    id = serializers.IntegerField()
    ...

    class Meta:
        list_serializer_class = BookListSerializer

It is possible that a third party package may be included alongside the 3.1 release that provides some automatic support for multiple update operations, similar to the allow_add_remove behavior that was present in REST framework 2.

Customizing ListSerializer initialization

When a serializer with many=True is instantiated, we need to determine which arguments and keyword arguments should be passed to the .__init__() method for both the child Serializer class, and for the parent ListSerializer class.

The default implementation is to pass all arguments to both classes, except for validators, and any custom keyword arguments, both of which are assumed to be intended for the child serializer class.

Occasionally you might need to explicitly specify how the child and parent classes should be instantiated when many=True is passed. You can do so by using the many_init class method.

    @classmethod
    def many_init(cls, *args, **kwargs):
        # Instantiate the child serializer.
        kwargs['child'] = cls()
        # Instantiate the parent list serializer.
        return CustomListSerializer(*args, **kwargs)

BaseSerializer

BaseSerializer类，可用于轻松支持替代的序列化和反序列化样式。

此类实现与Serializer类相同的基本API：

  • .data-返回传出的原始表示形式。
  • .is_valid()-反序列化并验证传入的数据。
  • .validated_data-返回经过验证的传入数据。
  • .errors-返回验证期间的所有错误。
  • .save()-将经过验证的数据保留到对象实例中。

可以覆盖四种方法，具体取决于您希望序列化程序类支持什么功能：

  • .to_representation()-对其进行重写以支持序列化（用于读取操作）。
  • .to_internal_value()-重写此属性以支持反序列化，以进行写操作。
  • .create()和.update()-覆盖这两个或其中之一以支持保存实例。

因为此类提供与Serializer类相同的接口，所以您可以将其与基于常规类的现有视图一起使用，就像对常规Serializer或一样。 ModelSerializer。

这样做的唯一区别是BaseSerializer类不会在可浏览的API中生成HTML表单。 这是因为它们返回的数据不包括所有字段信息，该信息将允许将每个字段呈现为合适的HTML输入。

Read-only BaseSerializer classes

要使用BaseSerializer类实现只读的序列化程序，我们只需要重写.to_representation()方法即可。 让我们来看一个使用简单Django模型的示例：

class HighScore(models.Model):
    created = models.DateTimeField(auto_now_add=True)
    player_name = models.CharField(max_length=10)
    score = models.IntegerField()

It's simple to create a read-only serializer for converting HighScore instances into primitive data types.

class HighScoreSerializer(serializers.BaseSerializer):
    def to_representation(self, obj):
        return {
            'score': obj.score,
            'player_name': obj.player_name
        }

We can now use this class to serialize single HighScore instances:

@api_view(['GET'])
def high_score(request, pk):
    instance = HighScore.objects.get(pk=pk)
    serializer = HighScoreSerializer(instance)
    return Response(serializer.data)

Or use it to serialize multiple instances:

@api_view(['GET'])
def all_high_scores(request):
    queryset = HighScore.objects.order_by('-score')
    serializer = HighScoreSerializer(queryset, many=True)
    return Response(serializer.data)
Read-write BaseSerializer classes

To create a read-write serializer we first need to implement a .to_internal_value() method. This method returns the validated values that will be used to construct the object instance, and may raise a serializers.ValidationError if the supplied data is in an incorrect format.

Once you've implemented .to_internal_value(), the basic validation API will be available on the serializer, and you will be able to use .is_valid(), .validated_data and .errors.

If you want to also support .save() you'll need to also implement either or both of the .create() and .update() methods.

Here's a complete example of our previous HighScoreSerializer, that's been updated to support both read and write operations.

class HighScoreSerializer(serializers.BaseSerializer):
    def to_internal_value(self, data):
        score = data.get('score')
        player_name = data.get('player_name')

        # Perform the data validation.
        if not score:
            raise serializers.ValidationError({
                'score': 'This field is required.'
            })
        if not player_name:
            raise serializers.ValidationError({
                'player_name': 'This field is required.'
            })
        if len(player_name) > 10:
            raise serializers.ValidationError({
                'player_name': 'May not be more than 10 characters.'
            })

        # Return the validated values. This will be available as
        # the `.validated_data` property.
        return {
            'score': int(score),
            'player_name': player_name
        }

    def to_representation(self, obj):
        return {
            'score': obj.score,
            'player_name': obj.player_name
        }

    def create(self, validated_data):
        return HighScore.objects.create(**validated_data)

Creating new base classes

如果要实现新的通用序列化程序类以处理特定的序列化样式或与备用存储后端集成，则BaseSerializer类也很有用。

下列类是通用序列化器的示例，该序列化器可以处理将任意对象强制转换为原始表示形式。

class ObjectSerializer(serializers.BaseSerializer):
    """
    A read-only serializer that coerces arbitrary complex objects
    into primitive representations.
    """
    def to_representation(self, obj):
        for attribute_name in dir(obj):
            attribute = getattr(obj, attribute_name)
            if attribute_name('_'):
                # Ignore private attributes.
                pass
            elif hasattr(attribute, '__call__'):
                # Ignore methods and other callables.
                pass
            elif isinstance(attribute, (str, int, bool, float, type(None))):
                # Primitive types can be passed through unmodified.
                output[attribute_name] = attribute
            elif isinstance(attribute, list):
                # Recursively deal with items in lists.
                output[attribute_name] = [
                    self.to_representation(item) for item in attribute
                ]
            elif isinstance(attribute, dict):
                # Recursively deal with items in dictionaries.
                output[attribute_name] = {
                    str(key): self.to_representation(value)
                    for key, value in attribute.items()
                }
            else:
                # Force anything else to its string representation.
                output[attribute_name] = str(attribute)

先进的序列化器用法

覆盖序列化和反序列化行为

如果需要更改序列化程序类的序列化或反序列化行为，则可以通过覆盖.to_representation()或.to_internal_value()方法来实现。

这可能有用的一些原因包括...

  • 为新的序列化器基类添加新行为。
  • 稍微修改现有类的行为。
  • 提高返回大量数据的频繁访问的API端点的序列化性能。

这些方法的签名如下：

.to_representation(self, obj)

接受需要序列化的对象实例，并应返回原始表示形式。 通常，这意味着返回内置Python数据类型的结构。 可以处理的确切类型取决于您为API配置的渲染类。

可以重写以修改表示样式。 For example:

def to_representation(self, instance):
    """Convert `username` to lowercase."""
    ret = super().to_representation(instance)
    ret['username'] = ret['username'].lower()
    return ret

.to_internal_value(self, data)

Takes the unvalidated incoming data as input and should return the validated data that will be made available as serializer.validated_data. The return value will also be passed to the .create() or .update() methods if .save() is called on the serializer class.

If any of the validation fails, then the method should raise a serializers.ValidationError(errors). The errors argument should be a dictionary mapping field names (or settings.NON_FIELD_ERRORS_KEY) to a list of error messages. If you don't need to alter deserialization behavior and instead want to provide object-level validation, it's recommended that you instead override the .validate() method.

The data argument passed to this method will normally be the value of request.data, so the datatype it provides will depend on the parser classes you have configured for your API.

Serializer Inheritance

Similar to Django forms, you can extend and reuse serializers through inheritance. This allows you to declare a common set of fields or methods on a parent class that can then be used in a number of serializers. For example,

class MyBaseSerializer(Serializer):
    my_field = serializers.CharField()

    def validate_my_field(self):
        ...

class MySerializer(MyBaseSerializer):
    ...

Like Django's Model and ModelForm classes, the inner Meta class on serializers does not implicitly inherit from it's parents' inner Meta classes. If you want the Meta class to inherit from a parent class you must do so explicitly. For example:

class AccountSerializer(MyBaseSerializer):
    class Meta(MyBaseSerializer.Meta):
        model = Account

Typically we would recommend not using inheritance on inner Meta classes, but instead declaring all options explicitly.

Additionally, the following caveats apply to serializer inheritance:

  • Normal Python name resolution rules apply. If you have multiple base classes that declare a Meta inner class, only the first one will be used. This means the child’s Meta, if it exists, otherwise the Meta of the first parent, etc.

  • It’s possible to declaratively remove a Field inherited from a parent class by setting the name to be None on the subclass.

    class MyBaseSerializer(ModelSerializer):
    my_field = serializers.CharField()

class MySerializer(MyBaseSerializer):
    my_field = None

    However, you can only use this technique to opt out from a field defined declaratively by a parent class; it won’t prevent the ModelSerializer from generating a default field. To opt-out from default fields, see Specifying which fields to include.

Dynamically modifying fields

Once a serializer has been initialized, the dictionary of fields that are set on the serializer may be accessed using the .fields attribute. Accessing and modifying this attribute allows you to dynamically modify the serializer.

Modifying the fields argument directly allows you to do interesting things such as changing the arguments on serializer fields at runtime, rather than at the point of declaring the serializer.

Example

For example, if you wanted to be able to set which fields should be used by a serializer at the point of initializing it, you could create a serializer class like so:

class DynamicFieldsModelSerializer(serializers.ModelSerializer):
    """
    A ModelSerializer that takes an additional `fields` argument that
    controls which fields should be displayed.
    """

    def __init__(self, *args, **kwargs):
        # Don't pass the 'fields' arg up to the superclass
        fields = kwargs.pop('fields', None)

        # Instantiate the superclass normally
        super(DynamicFieldsModelSerializer, self).__init__(*args, **kwargs)

        if fields is not None:
            # Drop any fields that are not specified in the `fields` argument.
            allowed = set(fields)
            existing = set(self.fields)
            for field_name in existing - allowed:
                self.fields.pop(field_name)

This would then allow you to do the following:

>>> class UserSerializer(DynamicFieldsModelSerializer):
>>>     class Meta:
>>>         model = User
>>>         fields = ('id', 'username', 'email')
>>>
>>> print UserSerializer(user)
{'id': 2, 'username': 'jonwatts', 'email': 'jon@example.com'}
>>>
>>> print UserSerializer(user, fields=('id', 'email'))
{'id': 2, 'email': 'jon@example.com'}

Customizing the default fields

REST framework 2 provided an API to allow developers to override how a ModelSerializer class would automatically generate the default set of fields.

This API included the .get_field(), .get_pk_field() and other methods.

Because the serializers have been fundamentally redesigned with 3.0 this API no longer exists. You can still modify the fields that get created but you'll need to refer to the source code, and be aware that if the changes you make are against private bits of API then they may be subject to change.

Third party packages

The following third party packages are also available.

Django REST marshmallow

The django-rest-marshmallow package provides an alternative implementation for serializers, using the python marshmallow library. It exposes the same API as the REST framework serializers, and can be used as a drop-in replacement in some use-cases.

Serpy

The serpy package is an alternative implementation for serializers that is built for speed. Serpy serializes complex datatypes to simple native types. The native types can be easily converted to JSON or any other format needed.

MongoengineModelSerializer

The django-rest-framework-mongoengine package provides a MongoEngineModelSerializer serializer class that supports using MongoDB as the storage layer for Django REST framework.

GeoFeatureModelSerializer

The django-rest-framework-gis package provides a GeoFeatureModelSerializer serializer class that supports GeoJSON both for read and write operations.

HStoreSerializer

The django-rest-framework-hstore package provides an HStoreSerializer to support django-hstore DictionaryField model field and its schema-mode feature.

Dynamic REST

The dynamic-rest package extends the ModelSerializer and ModelViewSet interfaces, adding API query parameters for filtering, sorting, and including / excluding all fields and relationships defined by your serializers.

Dynamic Fields Mixin

The drf-dynamic-fields package provides a mixin to dynamically limit the fields per serializer to a subset specified by an URL parameter.

DRF FlexFields

The drf-flex-fields package extends the ModelSerializer and ModelViewSet to provide commonly used functionality for dynamically setting fields and expanding primitive fields to nested models, both from URL parameters and your serializer class definitions.

Serializer Extensions

The django-rest-framework-serializer-extensions package provides a collection of tools to DRY up your serializers, by allowing fields to be defined on a per-view/request basis. Fields can be whitelisted, blacklisted and child serializers can be optionally expanded.

HTML JSON Forms

The html-json-forms package provides an algorithm and serializer for processing <form> submissions per the (inactive) HTML JSON Form specification. The serializer facilitates processing of arbitrarily nested JSON structures within HTML. For example, <input name="items[0][id]" value="5"> will be interpreted as {"items": [{"id": "5"}]}.

DRF-Base64

DRF-Base64 provides a set of field and model serializers that handles the upload of base64-encoded files.

QueryFields

djangorestframework-queryfields allows API clients to specify which fields will be sent in the response via inclusion/exclusion query parameters.

DRF Writable Nested

The drf-writable-nested package provides writable nested model serializer which allows to create/update models with nested related data.