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<li><a href="#pre-release-notes:">Pre-release notes:</a></li>
<li class="main"><a href="#rest-framework-30">REST framework 3.0</a></li>
<li><a href="#new-features">New features</a></li>
<li><a href="#request-objects">Request objects</a></li>
<li><a href="#serializers">Serializers</a></li>
<li><a href="#serializer-fields">Serializer fields</a></li>
<li><a href="#generic-views">Generic views</a></li>
<li><a href="#the-metadata-api">The metadata API</a></li>
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<h2 id="pre-release-notes">Pre-release notes:</h2>
<p>The 3.0 release is now ready for some tentative testing and upgrades for super keen early adopters. You can install the development version directly from GitHub like so:</p>
<pre class="prettyprint lang-py"><code>pip install https://github.com/tomchristie/django-rest-framework/archive/version-3.0.zip
</code></pre>
<p>See the <a href="https://github.com/tomchristie/django-rest-framework/pull/1800">Version 3.0 GitHub issue</a> for more details on remaining work.</p>
<p>The most notable outstanding issues still to be resolved on the <code>version-3.0</code> branch are as follows:</p>
<ul>
<li>Finish forms support for serializers and in the browsable API.</li>
<li>Optimisations for serializing primary keys.</li>
<li>Refine style of validation errors in some cases, such as validation errors in <code>ListField</code>.</li>
</ul>
<p><strong>Your feedback on the upgrade process and 3.0 changes is hugely important!</strong></p>
<p>Please do get in touch via twitter, IRC, a GitHub ticket, or the discussion group.</p>
<hr />
<h1 id="rest-framework-30">REST framework 3.0</h1>
<p>The 3.0 release of Django REST framework is the result of almost four years of iteration and refinement. It comprehensively addresses some of the previous remaining design issues in serializers, fields and the generic views.</p>
<p>This release is incremental in nature. There <em>are</em> some breaking API changes, and upgrading <em>will</em> require you to read the release notes carefully, but the migration path should otherwise be relatively straightforward.</p>
<p>The difference in quality of the REST framework API and implementation should make writing, maintaining and debugging your application far easier.</p>
<h2 id="new-features">New features</h2>
<p>Notable features of this new release include:</p>
<ul>
<li>Printable representations on serializers that allow you to inspect exactly what fields are present on the instance.</li>
<li>Simple model serializers that are vastly easier to understand and debug, and that make it easy to switch between the implicit <code>ModelSerializer</code> class and the explicit <code>Serializer</code> class.</li>
<li>A new <code>BaseSerializer</code> class, making it easier to write serializers for alternative storage backends, or to completely customize your serialization and validation logic.</li>
<li>A cleaner fields API plus new <code>ListField</code> and <code>MultipleChoiceField</code> classes.</li>
<li>Super simple default implementations for the generic views.</li>
<li>Support for overriding how validation errors are handled by your API.</li>
<li>A metadata API that allows you to customize how <code>OPTIONS</code> requests are handled by your API.</li>
<li>A more compact JSON output with unicode style encoding turned on by default.</li>
</ul>
<p>Below is an in-depth guide to the API changes and migration notes for 3.0.</p>
<hr />
<h2 id="request-objects">Request objects</h2>
<h4 id="the-data-and-query_params-properties">The <code>.data</code> and <code>.query_params</code> properties.</h4>
<p>The usage of <code>request.DATA</code> and <code>request.FILES</code> is now pending deprecation in favor of a single <code>request.data</code> attribute that contains <em>all</em> the parsed data.</p>
<p>Having separate attributes is reasonable for web applications that only ever parse url-encoded or multipart requests, but makes less sense for the general-purpose request parsing that REST framework supports.</p>
<p>You may now pass all the request data to a serializer class in a single argument:</p>
<pre class="prettyprint lang-py"><code># Do this...
ExampleSerializer(data=request.data)
</code></pre>
<p>Instead of passing the files argument separately:</p>
<pre class="prettyprint lang-py"><code># Don't do this...
ExampleSerializer(data=request.DATA, files=request.FILES)
</code></pre>
<p>The usage of <code>request.QUERY_PARAMS</code> is now pending deprecation in favor of the lowercased <code>request.query_params</code>.</p>
<h2 id="serializers">Serializers</h2>
<h4 id="single-step-object-creation">Single-step object creation.</h4>
<p>Previously the serializers used a two-step object creation, as follows:</p>
<ol>
<li>Validating the data would create an object instance. This instance would be available as <code>serializer.object</code>.</li>
<li>Calling <code>serializer.save()</code> would then save the object instance to the database.</li>
</ol>
<p>This style is in-line with how the <code>ModelForm</code> class works in Django, but is problematic for a number of reasons:</p>
<ul>
<li>Some data, such as many-to-many relationships, cannot be added to the object instance until after it has been saved. This type of data needed to be hidden in some undocumented state on the object instance, or kept as state on the serializer instance so that it could be used when <code>.save()</code> is called.</li>
<li>Instantiating model instances directly means that you cannot use model manager classes for instance creation, eg <code>ExampleModel.objects.create(...)</code>. Manager classes are an excellent layer at which to enforce business logic and application-level data constraints.</li>
<li>The two step process makes it unclear where to put deserialization logic. For example, should extra attributes such as the current user get added to the instance during object creation or during object save?</li>
</ul>
<p>We now use single-step object creation, like so:</p>
<ol>
<li>Validating the data makes the cleaned data available as <code>serializer.validated_data</code>.</li>
<li>Calling <code>serializer.save()</code> then saves and returns the new object instance.</li>
</ol>
<p>The resulting API changes are further detailed below.</p>
<h4 id="the-create-and-update-methods">The <code>.create()</code> and <code>.update()</code> methods.</h4>
<p>The <code>.restore_object()</code> method is now replaced with two separate methods, <code>.create()</code> and <code>.update()</code>.</p>
<p>When using the <code>.create()</code> and <code>.update()</code> methods you should both create <em>and save</em> the object instance. This is in contrast to the previous <code>.restore_object()</code> behavior that would instantiate the object but not save it.</p>
<p>The following example from the tutorial previously used <code>restore_object()</code> to handle both creating and updating object instances.</p>
<pre class="prettyprint lang-py"><code>def restore_object(self, attrs, instance=None):
if instance:
# Update existing instance
instance.title = attrs.get('title', instance.title)
instance.code = attrs.get('code', instance.code)
instance.linenos = attrs.get('linenos', instance.linenos)
instance.language = attrs.get('language', instance.language)
instance.style = attrs.get('style', instance.style)
return instance
# Create new instance
return Snippet(**attrs)
</code></pre>
<p>This would now be split out into two separate methods.</p>
<pre class="prettyprint lang-py"><code>def update(self, instance, validated_data):
instance.title = validated_data.get('title', instance.title)
instance.code = validated_data.get('code', instance.code)
instance.linenos = validated_data.get('linenos', instance.linenos)
instance.language = validated_data.get('language', instance.language)
instance.style = validated_data.get('style', instance.style)
instance.save()
return instance
def create(self, validated_data):
return Snippet.objects.create(**validated_data)
</code></pre>
<p>Note that these methods should return the newly created object instance.</p>
<h4 id="use-validated_data-instead-of-object">Use <code>.validated_data</code> instead of <code>.object</code>.</h4>
<p>You must now use the <code>.validated_data</code> attribute if you need to inspect the data before saving, rather than using the <code>.object</code> attribute, which no longer exists.</p>
<p>For example the following code <em>is no longer valid</em>:</p>
<pre class="prettyprint lang-py"><code>if serializer.is_valid():
name = serializer.object.name # Inspect validated field data.
logging.info('Creating ticket "%s"' % name)
serializer.object.user = request.user # Include the user when saving.
serializer.save()
</code></pre>
<p>Instead of using <code>.object</code> to inspect a partially constructed instance, you would now use <code>.validated_data</code> to inspect the cleaned incoming values. Also you can't set extra attributes on the instance directly, but instead pass them to the <code>.save()</code> method as keyword arguments.</p>
<p>The corresponding code would now look like this:</p>
<pre class="prettyprint lang-py"><code>if serializer.is_valid():
name = serializer.validated_data['name'] # Inspect validated field data.
logging.info('Creating ticket "%s"' % name)
serializer.save(user=request.user) # Include the user when saving.
</code></pre>
<h4 id="using-serializersvalidationerror">Using <code>serializers.ValidationError</code>.</h4>
<p>Previously <code>serializers.ValidationError</code> error was simply a synonym for <code>django.core.exceptions.ValidationError</code>. This has now been altered so that it inherits from the standard <code>APIException</code> base class.</p>
<p>The reason behind this is that Django's <code>ValidationError</code> class is intended for use with HTML forms and its API makes using it slightly awkward with nested validation errors that can occur in serializers.</p>
<p>For most users this change shouldn't require any updates to your codebase, but it is worth ensuring that whenever raising validation errors you are always using the <code>serializers.ValidationError</code> exception class, and not Django's built-in exception.</p>
<p>We strongly recommend that you use the namespaced import style of <code>import serializers</code> and not <code>from serializers import ValidationError</code> in order to avoid any potential confusion.</p>
<h4 id="change-to-validate_field_name">Change to <code>validate_&lt;field_name&gt;</code>.</h4>
<p>The <code>validate_&lt;field_name&gt;</code> method hooks that can be attached to serializer classes change their signature slightly and return type. Previously these would take a dictionary of all incoming data, and a key representing the field name, and would return a dictionary including the validated data for that field:</p>
<pre class="prettyprint lang-py"><code>def validate_score(self, attrs, source):
if attrs[score] % 10 != 0:
raise serializers.ValidationError('This field should be a multiple of ten.')
return attrs
</code></pre>
<p>This is now simplified slightly, and the method hooks simply take the value to be validated, and return the validated value.</p>
<pre class="prettyprint lang-py"><code>def validate_score(self, value):
if value % 10 != 0:
raise serializers.ValidationError('This field should be a multiple of ten.')
return value
</code></pre>
<p>Any ad-hoc validation that applies to more than one field should go in the <code>.validate(self, attrs)</code> method as usual.</p>
<p>Because <code>.validate_&lt;field_name&gt;</code> would previously accept the complete dictionary of attributes, it could be used to validate a field depending on the input in another field. Now if you need to do this you should use <code>.validate()</code> instead.</p>
<p>You can either return <code>non_field_errors</code> from the validate method by raising a simple <code>ValidationError</code></p>
<pre class="prettyprint lang-py"><code>def validate(self, attrs):
# serializer.errors == {'non_field_errors': ['A non field error']}
raise serailizers.ValidationError('A non field error')
</code></pre>
<p>Alternatively if you want the errors to be against a specific field, use a dictionary of when instantiating the <code>ValidationError</code>, like so:</p>
<pre class="prettyprint lang-py"><code>def validate(self, attrs):
# serializer.errors == {'my_field': ['A field error']}
raise serailizers.ValidationError({'my_field': 'A field error'})
</code></pre>
<p>This ensures you can still write validation that compares all the input fields, but that marks the error against a particular field.</p>
<h4 id="limitations-of-modelserializer-validation">Limitations of ModelSerializer validation.</h4>
<p>This change also means that we no longer use the <code>.full_clean()</code> method on model instances, but instead perform all validation explicitly on the serializer. This gives a cleaner separation, and ensures that there's no automatic validation behavior on <code>ModelSerializer</code> classes that can't also be easily replicated on regular <code>Serializer</code> classes.</p>
<p>This change comes with the following limitations:</p>
<ul>
<li>The model <code>.clean()</code> method will not be called as part of serializer validation. Use the serializer <code>.validate()</code> method to perform a final validation step on incoming data where required.</li>
<li>The <code>.unique_for_date</code>, <code>.unique_for_month</code> and <code>.unique_for_year</code> options on model fields are not automatically validated. Again, you'll need to handle these explicitly on the serializer if required.</li>
</ul>
<h4 id="writable-nested-serialization">Writable nested serialization.</h4>
<p>REST framework 2.x attempted to automatically support writable nested serialization, but the behavior was complex and non-obvious. Attempting to automatically handle these case is problematic:</p>
<ul>
<li>There can be complex dependencies involved in order of saving multiple related model instances.</li>
<li>It's unclear what behavior the user should expect when related models are passed <code>None</code> data.</li>
<li>It's unclear how the user should expect to-many relationships to handle updates, creations and deletions of multiple records.</li>
</ul>
<p>Using the <code>depth</code> option on <code>ModelSerializer</code> will now create <strong>read-only nested serializers</strong> by default.</p>
<p>If you try to use a writable nested serializer without writing a custom <code>create()</code> and/or <code>update()</code> method you'll see an assertion error when you attempt to save the serializer. For example:</p>
<pre class="prettyprint lang-py"><code>&gt;&gt;&gt; class ProfileSerializer(serializers.ModelSerializer):
&gt;&gt;&gt; class Meta:
&gt;&gt;&gt; model = Profile
&gt;&gt;&gt; fields = ('address', 'phone')
&gt;&gt;&gt;
&gt;&gt;&gt; class UserSerializer(serializers.ModelSerializer):
&gt;&gt;&gt; profile = ProfileSerializer()
&gt;&gt;&gt; class Meta:
&gt;&gt;&gt; model = User
&gt;&gt;&gt; fields = ('username', 'email', 'profile')
&gt;&gt;&gt;
&gt;&gt;&gt; data = {
&gt;&gt;&gt; 'username': 'lizzy',
&gt;&gt;&gt; 'email': 'lizzy@example.com',
&gt;&gt;&gt; 'profile': {'address': '123 Acacia Avenue', 'phone': '01273 100200'}
&gt;&gt;&gt; }
&gt;&gt;&gt;
&gt;&gt;&gt; serializer = UserSerializer(data=data)
&gt;&gt;&gt; serializer.save()
AssertionError: The `.create()` method does not suport nested writable fields by default. Write an explicit `.create()` method for serializer `UserSerializer`, or set `read_only=True` on nested serializer fields.
</code></pre>
<p>To use writable nested serialization you'll want to declare a nested field on the serializer class, and write the <code>create()</code> and/or <code>update()</code> methods explicitly.</p>
<pre class="prettyprint lang-py"><code>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
</code></pre>
<p>The single-step object creation makes this far simpler and more obvious than the previous <code>.restore_object()</code> behavior.</p>
<h4 id="printable-serializer-representations">Printable serializer representations.</h4>
<p>Serializer instances now support a printable representation that allows you to inspect the fields present on the instance.</p>
<p>For instance, given the following example model:</p>
<pre class="prettyprint lang-py"><code>class LocationRating(models.Model):
location = models.CharField(max_length=100)
rating = models.IntegerField()
created_by = models.ForeignKey(User)
</code></pre>
<p>Let's create a simple <code>ModelSerializer</code> class corresponding to the <code>LocationRating</code> model.</p>
<pre class="prettyprint lang-py"><code>class LocationRatingSerializer(serializer.ModelSerializer):
class Meta:
model = LocationRating
</code></pre>
<p>We can now inspect the serializer representation in the Django shell, using <code>python manage.py shell</code>...</p>
<pre class="prettyprint lang-py"><code>&gt;&gt;&gt; serializer = LocationRatingSerializer()
&gt;&gt;&gt; print(serializer) # Or use `print serializer` in Python 2.x
LocationRatingSerializer():
id = IntegerField(label='ID', read_only=True)
location = CharField(max_length=100)
rating = IntegerField()
created_by = PrimaryKeyRelatedField(queryset=User.objects.all())
</code></pre>
<h4 id="the-extra_kwargs-option">The <code>extra_kwargs</code> option.</h4>
<p>The <code>write_only_fields</code> option on <code>ModelSerializer</code> has been moved to <code>PendingDeprecation</code> and replaced with a more generic <code>extra_kwargs</code>.</p>
<pre class="prettyprint lang-py"><code>class MySerializer(serializer.ModelSerializer):
class Meta:
model = MyModel
fields = ('id', 'email', 'notes', 'is_admin')
extra_kwargs = {
'is_admin': {'write_only': True}
}
</code></pre>
<p>Alternatively, specify the field explicitly on the serializer class:</p>
<pre class="prettyprint lang-py"><code>class MySerializer(serializer.ModelSerializer):
is_admin = serializers.BooleanField(write_only=True)
class Meta:
model = MyModel
fields = ('id', 'email', 'notes', 'is_admin')
</code></pre>
<p>The <code>read_only_fields</code> option remains as a convenient shortcut for the more common case. </p>
<h4 id="changes-to-hyperlinkedmodelserializer">Changes to <code>HyperlinkedModelSerializer</code>.</h4>
<p>The <code>view_name</code> and <code>lookup_field</code> options have been moved to <code>PendingDeprecation</code>. They are no longer required, as you can use the <code>extra_kwargs</code> argument instead:</p>
<pre class="prettyprint lang-py"><code>class MySerializer(serializer.HyperlinkedModelSerializer):
class Meta:
model = MyModel
fields = ('url', 'email', 'notes', 'is_admin')
extra_kwargs = {
'url': {'lookup_field': 'uuid'}
}
</code></pre>
<p>Alternatively, specify the field explicitly on the serializer class:</p>
<pre class="prettyprint lang-py"><code>class MySerializer(serializer.HyperlinkedModelSerializer):
url = serializers.HyperlinkedIdentityField(
view_name='mymodel-detail',
lookup_field='uuid'
)
class Meta:
model = MyModel
fields = ('url', 'email', 'notes', 'is_admin')
</code></pre>
<h4 id="fields-for-model-methods-and-properties">Fields for model methods and properties.</h4>
<p>With <code>ModelSerilizer</code> you can now specify field names in the <code>fields</code> option that refer to model methods or properties. For example, suppose you have the following model:</p>
<pre class="prettyprint lang-py"><code>class Invitation(models.Model):
created = models.DateTimeField()
to_email = models.EmailField()
message = models.CharField(max_length=1000)
def expiry_date(self):
return self.created + datetime.timedelta(days=30)
</code></pre>
<p>You can include <code>expiry_date</code> as a field option on a <code>ModelSerializer</code> class.</p>
<pre class="prettyprint lang-py"><code>class InvitationSerializer(serializers.ModelSerializer):
class Meta:
model = Invitation
fields = ('to_email', 'message', 'expiry_date')
</code></pre>
<p>These fields will be mapped to <code>serializers.ReadOnlyField()</code> instances.</p>
<pre class="prettyprint lang-py"><code>&gt;&gt;&gt; serializer = InvitationSerializer()
&gt;&gt;&gt; print repr(serializer)
InvitationSerializer():
to_email = EmailField(max_length=75)
message = CharField(max_length=1000)
expiry_date = ReadOnlyField()
</code></pre>
<h4 id="the-listserializer-class">The <code>ListSerializer</code> class.</h4>
<p>The <code>ListSerializer</code> class has now been added, and allows you to create base serializer classes for only accepting multiple inputs.</p>
<pre class="prettyprint lang-py"><code>class MultipleUserSerializer(ListSerializer):
child = UserSerializer()
</code></pre>
<p>You can also still use the <code>many=True</code> argument to serializer classes. It's worth noting that <code>many=True</code> argument transparently creates a <code>ListSerializer</code> instance, allowing the validation logic for list and non-list data to be cleanly separated in the REST framework codebase. </p>
<p>See also the new <code>ListField</code> class, which validates input in the same way, but does not include the serializer interfaces of <code>.is_valid()</code>, <code>.data</code>, <code>.save()</code> and so on.</p>
<h4 id="the-baseserializer-class">The <code>BaseSerializer</code> class.</h4>
<p>REST framework now includes a simple <code>BaseSerializer</code> class that can be used to easily support alternative serialization and deserialization styles.</p>
<p>This class implements the same basic API as the <code>Serializer</code> class:</p>
<ul>
<li><code>.data</code> - Returns the outgoing primitive representation.</li>
<li><code>.is_valid()</code> - Deserializes and validates incoming data.</li>
<li><code>.validated_data</code> - Returns the validated incoming data.</li>
<li><code>.errors</code> - Returns an errors during validation.</li>
<li><code>.save()</code> - Persists the validated data into an object instance.</li>
</ul>
<p>There are four mathods that can be overriding, depending on what functionality you want the serializer class to support:</p>
<ul>
<li><code>.to_representation()</code> - Override this to support serialization, for read operations.</li>
<li><code>.to_internal_value()</code> - Override this to support deserialization, for write operations.</li>
<li><code>.create()</code> and <code>.update()</code> - Overide either or both of these to support saving instances.</li>
</ul>
<h5 id="read-only-baseserializer-classes">Read-only <code>BaseSerializer</code> classes.</h5>
<p>To implement a read-only serializer using the <code>BaseSerializer</code> class, we just need to override the <code>.to_representation()</code> method. Let's take a look at an example using a simple Django model:</p>
<pre class="prettyprint lang-py"><code>class HighScore(models.Model):
created = models.DateTimeField(auto_now_add=True)
player_name = models.CharField(max_length=10)
score = models.IntegerField()
</code></pre>
<p>It's simple to create a read-only serializer for converting <code>HighScore</code> instances into primitive data types.</p>
<pre class="prettyprint lang-py"><code>class HighScoreSerializer(serializers.BaseSerializer):
def to_representation(self, obj):
return {
'score': obj.score,
'player_name': obj.player_name
}
</code></pre>
<p>We can now use this class to serialize single <code>HighScore</code> instances:</p>
<pre class="prettyprint lang-py"><code>@api_view(['GET'])
def high_score(request, pk):
instance = HighScore.objects.get(pk=pk)
serializer = HighScoreSerializer(instance)
return Response(serializer.data)
</code></pre>
<p>Or use it to serialize multiple instances:</p>
<pre class="prettyprint lang-py"><code>@api_view(['GET'])
def all_high_scores(request):
queryset = HighScore.objects.order_by('-score')
serializer = HighScoreSerializer(queryset, many=True)
return Response(serializer.data)
</code></pre>
<h5 id="read-write-baseserializer-classes">Read-write <code>BaseSerializer</code> classes.</h5>
<p>To create a read-write serializer we first need to implement a <code>.to_internal_value()</code> method. This method returns the validated values that will be used to construct the object instance, and may raise a <code>ValidationError</code> if the supplied data is in an incorrect format.</p>
<p>Once you've implemented <code>.to_internal_value()</code>, the basic validation API will be available on the serializer, and you will be able to use <code>.is_valid()</code>, <code>.validated_data</code> and <code>.errors</code>.</p>
<p>If you want to also support <code>.save()</code> you'll need to also implement either or both of the <code>.create()</code> and <code>.update()</code> methods.</p>
<p>Here's a complete example of our previous <code>HighScoreSerializer</code>, that's been updated to support both read and write operations.</p>
<pre class="prettyprint lang-py"><code>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 ValidationError({
'score': 'This field is required.'
})
if not player_name:
raise ValidationError({
'player_name': 'This field is required.'
})
if len(player_name) &gt; 10:
raise 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)
</code></pre>
<h4 id="creating-new-generic-serializers-with-baseserializer">Creating new generic serializers with <code>BaseSerializer</code>.</h4>
<p>The <code>BaseSerializer</code> class is also useful if you want to implement new generic serializer classes for dealing with particular serialization styles, or for integrating with alternative storage backends.</p>
<p>The following class is an example of a generic serializer that can handle coercing aribitrary objects into primitive representations. </p>
<pre class="prettyprint lang-py"><code>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):
# Recursivly deal with items in lists.
output[attribute_name] = [
self.to_representation(item) for item in attribute
]
elif isinstance(attribute, dict):
# Recursivly deal with items in dictionarys.
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)
</code></pre>
<h2 id="serializer-fields">Serializer fields</h2>
<h4 id="the-field-and-readonly-field-classes">The <code>Field</code> and <code>ReadOnly</code> field classes.</h4>
<p>There are some minor tweaks to the field base classes.</p>
<p>Previously we had these two base classes:</p>
<ul>
<li><code>Field</code> as the base class for read-only fields. A default implementation was included for serializing data.</li>
<li><code>WritableField</code> as the base class for read-write fields.</li>
</ul>
<p>We now use the following:</p>
<ul>
<li><code>Field</code> is the base class for all fields. It does not include any default implementation for either serializing or deserializing data.</li>
<li><code>ReadOnlyField</code> is a concrete implementation for read-only fields that simply returns the attribute value without modification.</li>
</ul>
<h4 id="the-required-allow_none-allow_blank-and-default-arguments">The <code>required</code>, <code>allow_none</code>, <code>allow_blank</code> and <code>default</code> arguments.</h4>
<p>REST framework now has more explicit and clear control over validating empty values for fields.</p>
<p>Previously the meaning of the <code>required=False</code> keyword argument was underspecified. In practice its use meant that a field could either be not included in the input, or it could be included, but be <code>None</code>.</p>
<p>We now have a better separation, with separate <code>required</code> and <code>allow_none</code> arguments.</p>
<p>The following set of arguments are used to control validation of empty values:</p>
<ul>
<li><code>required=False</code>: The value does not need to be present in the input, and will not be passed to <code>.create()</code> or <code>.update()</code> if it is not seen.</li>
<li><code>default=&lt;value&gt;</code>: The value does not need to be present in the input, and a default value will be passed to <code>.create()</code> or <code>.update()</code> if it is not seen.</li>
<li><code>allow_none=True</code>: <code>None</code> is a valid input.</li>
<li><code>allow_blank=True</code>: <code>''</code> is valid input. For <code>CharField</code> and subclasses only.</li>
</ul>
<p>Typically you'll want to use <code>required=False</code> if the corresponding model field has a default value, and additionally set either <code>allow_none=True</code> or <code>allow_blank=True</code> if required.</p>
<p>The <code>default</code> argument is there if you need it, but you'll more typically want defaults to be set on model fields, rather than serializer fields.</p>
<h4 id="coercing-output-types">Coercing output types.</h4>
<p>The previous field implementations did not forcibly coerce returned values into the correct type in many cases. For example, an <code>IntegerField</code> would return a string output if the attribute value was a string. We now more strictly coerce to the correct return type, leading to more constrained and expected behavior. </p>
<h4 id="the-listfield-class">The <code>ListField</code> class.</h4>
<p>The <code>ListField</code> class has now been added. This field validates list input. It takes a <code>child</code> keyword argument which is used to specify the field used to validate each item in the list. For example:</p>
<pre class="prettyprint lang-py"><code>scores = ListField(child=IntegerField(min_value=0, max_value=100))
</code></pre>
<p>You can also use a declarative style to create new subclasses of <code>ListField</code>, like this:</p>
<pre class="prettyprint lang-py"><code>class ScoresField(ListField):
child = IntegerField(min_value=0, max_value=100)
</code></pre>
<p>We can now use the <code>ScoresField</code> class inside another serializer:</p>
<pre class="prettyprint lang-py"><code>scores = ScoresField()
</code></pre>
<p>See also the new <code>ListSerializer</code> class, which validates input in the same way, but also includes the serializer interfaces of <code>.is_valid()</code>, <code>.data</code>, <code>.save()</code> and so on.</p>
<h4 id="the-choicefield-class-may-now-accept-a-flat-list">The <code>ChoiceField</code> class may now accept a flat list.</h4>
<p>The <code>ChoiceField</code> class may now accept a list of choices in addition to the existing style of using a list of pairs of <code>(name, display_value)</code>. The following is now valid:</p>
<pre class="prettyprint lang-py"><code>color = ChoiceField(choices=['red', 'green', 'blue'])
</code></pre>
<h4 id="the-multiplechoicefield-class">The <code>MultipleChoiceField</code> class.</h4>
<p>The <code>MultipleChoiceField</code> class has been added. This field acts like <code>ChoiceField</code>, but returns a set, which may include none, one or many of the valid choices.</p>
<h4 id="changes-to-the-custom-field-api">Changes to the custom field API.</h4>
<p>The <code>from_native(self, value)</code> and <code>to_native(self, data)</code> method names have been replaced with the more obviously named <code>to_internal_value(self, data)</code> and <code>to_representation(self, value)</code>.</p>
<p>The <code>field_from_native()</code> and <code>field_to_native()</code> methods are removed.</p>
<h4 id="explicit-queryset-required-on-relational-fields">Explicit <code>queryset</code> required on relational fields.</h4>
<p>Previously relational fields that were explicitly declared on a serializer class could omit the queryset argument if (and only if) they were declared on a <code>ModelSerializer</code>.</p>
<p>This code <em>would be valid</em> in <code>2.4.3</code>:</p>
<pre class="prettyprint lang-py"><code>class AccountSerializer(serializers.ModelSerializer):
organisations = serializers.SlugRelatedField(slug_field='name')
class Meta:
model = Account
</code></pre>
<p>However this code <em>would not be valid</em> in <code>2.4.3</code>:</p>
<pre class="prettyprint lang-py"><code># Missing `queryset`
class AccountSerializer(serializers.Serializer):
organisations = serializers.SlugRelatedField(slug_field='name')
def restore_object(self, attrs, instance=None):
# ...
</code></pre>
<p>The queryset argument is now always required for writable relational fields.
This removes some magic and makes it easier and more obvious to move between implicit <code>ModelSerializer</code> classes and explicit <code>Serializer</code> classes.</p>
<pre class="prettyprint lang-py"><code>class AccountSerializer(serializers.ModelSerializer):
organisations = serializers.SlugRelatedField(
slug_field='name',
queryset=Organisation.objects.all()
)
class Meta:
model = Account
</code></pre>
<p>The <code>queryset</code> argument is only ever required for writable fields, and is not required or valid for fields with <code>read_only=True</code>.</p>
<h4 id="optional-argument-to-serializermethodfield">Optional argument to <code>SerializerMethodField</code>.</h4>
<p>The argument to <code>SerializerMethodField</code> is now optional, and defaults to <code>get_&lt;field_name&gt;</code>. For example the following is valid:</p>
<pre class="prettyprint lang-py"><code>class AccountSerializer(serializers.Serializer):
# `method_name='get_billing_details'` by default.
billing_details = serializers.SerializerMethodField()
def get_billing_details(self, account):
return calculate_billing(account)
</code></pre>
<p>In order to ensure a consistent code style an assertion error will be raised if you include a redundant method name argument that matches the default method name. For example, the following code <em>will raise an error</em>:</p>
<pre class="prettyprint lang-py"><code>billing_details = serializers.SerializerMethodField('get_billing_details')
</code></pre>
<h4 id="enforcing-consistent-source-usage">Enforcing consistent <code>source</code> usage.</h4>
<p>I've see several codebases that unnecessarily include the <code>source</code> argument, setting it to the same value as the field name. This usage is redundant and confusing, making it less obvious that <code>source</code> is usually not required.</p>
<p>The following usage will <em>now raise an error</em>:</p>
<pre class="prettyprint lang-py"><code>email = serializers.EmailField(source='email')
</code></pre>
<h4 id="the-uniquevalidator-and-uniquetogethervalidator-classes">The <code>UniqueValidator</code> and <code>UniqueTogetherValidator</code> classes.</h4>
<p>REST framework now provides two new validators that allow you to ensure field uniqueness, while still using a completely explicit <code>Serializer</code> class instead of using <code>ModelSerializer</code>.</p>
<p>The <code>UniqueValidator</code> should be applied to a serializer field, and takes a single <code>queryset</code> argument.</p>
<pre class="prettyprint lang-py"><code>from rest_framework import serializers
from rest_framework.validators import UniqueValidator
class OrganizationSerializer(serializers.Serializer):
url = serializers.HyperlinkedIdentityField(view_name='organisation_detail')
created = serializers.DateTimeField(read_only=True)
name = serializers.CharField(
max_length=100,
validators=UniqueValidator(queryset=Organisation.objects.all())
)
</code></pre>
<p>The <code>UniqueTogetherValidator</code> should be applied to a serializer, and takes a <code>queryset</code> argument and a <code>fields</code> argument which should be a list or tuple of field names.</p>
<pre class="prettyprint lang-py"><code>class RaceResultSerializer(serializers.Serializer):
category = serializers.ChoiceField(['5k', '10k'])
position = serializers.IntegerField()
name = serializers.CharField(max_length=100)
default_validators = [UniqueTogetherValidator(
queryset=RaceResult.objects.all(),
fields=('category', 'position')
)]
</code></pre>
<h2 id="generic-views">Generic views</h2>
<h4 id="simplification-of-view-logic">Simplification of view logic.</h4>
<p>The view logic for the default method handlers has been significantly simplified, due to the new serializers API.</p>
<h4 id="changes-to-prepost-save-hooks">Changes to pre/post save hooks.</h4>
<p>The <code>pre_save</code> and <code>post_save</code> hooks no longer exist, but are replaced with <code>perform_create(self, serializer)</code> and <code>perform_update(self, serializer)</code>.</p>
<p>These methods should save the object instance by calling <code>serializer.save()</code>, adding in any additional arguments as required. They may also perform any custom pre-save or post-save behavior.</p>
<p>For example:</p>
<pre class="prettyprint lang-py"><code>def perform_create(self, serializer):
# Include the owner attribute directly, rather than from request data.
instance = serializer.save(owner=self.request.user)
# Perform a custom post-save action.
send_email(instance.to_email, instance.message)
</code></pre>
<p>The <code>pre_delete</code> and <code>post_delete</code> hooks no longer exist, and are replaced with <code>.perform_destroy(self, instance)</code>, which should delete the instance and perform any custom actions.</p>
<pre class="prettyprint lang-py"><code>def perform_destroy(self, instance):
# Perform a custom pre-delete action.
send_deletion_alert(user=instance.created_by, deleted=instance)
# Delete the object instance.
instance.delete()
</code></pre>
<h4 id="removal-of-view-attributes">Removal of view attributes.</h4>
<p>The <code>.object</code> and <code>.object_list</code> attributes are no longer set on the view instance. Treating views as mutable object instances that store state during the processing of the view tends to be poor design, and can lead to obscure flow logic.</p>
<p>I would personally recommend that developers treat view instances as immutable objects in their application code.</p>
<h4 id="put-as-create">PUT as create.</h4>
<p>Allowing <code>PUT</code> as create operations is problematic, as it necessarily exposes information about the existence or non-existance of objects. It's also not obvious that transparently allowing re-creating of previously deleted instances is necessarily a better default behavior than simply returning <code>404</code> responses.</p>
<p>Both styles "<code>PUT</code> as 404" and "<code>PUT</code> as create" can be valid in different circumstances, but we've now opted for the 404 behavior as the default, due to it being simpler and more obvious.</p>
<p>If you need to restore the previous behavior you can include the <code>AllowPUTAsCreateMixin</code> class in your view. This class can be imported from <code>rest_framework.mixins</code>.</p>
<h4 id="customizing-error-responses">Customizing error responses.</h4>
<p>The generic views now raise <code>ValidationFailed</code> exception for invalid data. This exception is then dealt with by the exception handler, rather than the view returning a <code>400 Bad Request</code> response directly.</p>
<p>This change means that you can now easily customize the style of error responses across your entire API, without having to modify any of the generic views.</p>
<h2 id="the-metadata-api">The metadata API</h2>
<p>Behavior for dealing with <code>OPTIONS</code> requests was previously built directly into the class based views. This has now been properly separated out into a Metadata API that allows the same pluggable style as other API policies in REST framework.</p>
<p>This makes it far easier to use a different style for <code>OPTIONS</code> responses throughout your API, and makes it possible to create third-party metadata policies.</p>
<h2 id="api-style">API style</h2>
<p>There are some improvements in the default style we use in our API responses.</p>
<h4 id="unicode-json-by-default">Unicode JSON by default.</h4>
<p>Unicode JSON is now the default. The <code>UnicodeJSONRenderer</code> class no longer exists, and the <code>UNICODE_JSON</code> setting has been added. To revert this behavior use the new setting:</p>
<pre class="prettyprint lang-py"><code>REST_FRAMEWORK = {
'UNICODE_JSON': False
}
</code></pre>
<h4 id="compact-json-by-default">Compact JSON by default.</h4>
<p>We now output compact JSON in responses by default. For example, we return:</p>
<pre class="prettyprint lang-py"><code>{"email":"amy@example.com","is_admin":true}
</code></pre>
<p>Instead of the following:</p>
<pre class="prettyprint lang-py"><code>{"email": "amy@example.com", "is_admin": true}
</code></pre>
<p>The <code>COMPACT_JSON</code> setting has been added, and can be used to revert this behavior if needed:</p>
<pre class="prettyprint lang-py"><code>REST_FRAMEWORK = {
'COMPACT_JSON': False
}
</code></pre>
<h4 id="file-fields-as-urls">File fields as URLs</h4>
<p>The <code>FileField</code> and <code>ImageField</code> classes are now represented as URLs by default. You should ensure you set Django's <a href="https://docs.djangoproject.com/en/dev/ref/settings/#std:setting-MEDIA_URL">standard <code>MEDIA_URL</code> setting</a> appropriately, and ensure your application <a href="https://docs.djangoproject.com/en/dev/howto/static-files/#serving-uploaded-files-in-development">serves the uploaded files</a>.</p>
<p>You can revert this behavior, and display filenames in the representation by using the <code>UPLOADED_FILES_USE_URL</code> settings key:</p>
<pre class="prettyprint lang-py"><code>REST_FRAMEWORK = {
'UPLOADED_FILES_USE_URL': False
}
</code></pre>
<p>You can also modify serializer fields individually, using the <code>use_url</code> argument:</p>
<pre class="prettyprint lang-py"><code>uploaded_file = serializers.FileField(user_url=False)
</code></pre>
<p>Also note that you should pass the <code>request</code> object to the serializer as context when instantiating it, so that a fully qualified URL can be returned. Returned URLs will then be of the form <code>https://example.com/url_path/filename.txt</code>. For example:</p>
<pre class="prettyprint lang-py"><code>context = {'request': request}
serializer = ExampleSerializer(instance, context=context)
return Response(serializer.data)
</code></pre>
<p>If the request is omitted from the context, the returned URLs will be of the form <code>/url_path/filename.txt</code>.</p>
<h4 id="throttle-headers-using-retry-after">Throttle headers using <code>Retry-After</code>.</h4>
<p>The custom <code>X-Throttle-Wait-Second</code> header has now been dropped in favor of the standard <code>Retry-After</code> header. You can revert this behavior if needed by writing a custom exception handler for your application.</p>
<h4 id="date-and-time-objects-as-iso-8859-1-strings-in-serializer-data">Date and time objects as ISO-8859-1 strings in serializer data.</h4>
<p>Date and Time objects are now coerced to strings by default in the serializer output. Previously they were returned as <code>Date</code>, <code>Time</code> and <code>DateTime</code> objects, and later coerced to strings by the renderer.</p>
<p>You can modify this behavior globally by settings the existing <code>DATE_FORMAT</code>, <code>DATETIME_FORMAT</code> and <code>TIME_FORMAT</code> settings keys. Setting these values to <code>None</code> instead of their default value of <code>'iso-8859-1'</code> will result in native objects being returned in serializer data.</p>
<pre class="prettyprint lang-py"><code>REST_FRAMEWORK = {
# Return native `Date` and `Time` objects in `serializer.data`
'DATETIME_FORMAT': None
'DATE_FORMAT': None
'TIME_FORMAT': None
}
</code></pre>
<p>You can also modify serializer fields individually, using the <code>date_format</code>, <code>time_format</code> and <code>datetime_format</code> arguments:</p>
<pre class="prettyprint lang-py"><code># Return `DateTime` instances in `serializer.data`, not strings.
created = serializers.DateTimeField(format=None)
</code></pre>
<h4 id="decimals-as-strings-in-serializer-data">Decimals as strings in serializer data.</h4>
<p>Decimals are now coerced to strings by default in the serializer output. Previously they were returned as <code>Decimal</code> objects, and later coerced to strings by the renderer.</p>
<p>You can modify this behavior globally by using the <code>COERCE_DECIMAL_TO_STRING</code> settings key.</p>
<pre class="prettyprint lang-py"><code>REST_FRAMEWORK = {
'COERCE_DECIMAL_TO_STRING': False
}
</code></pre>
<p>Or modify it on an individual serializer field, using the <code>corece_to_string</code> keyword argument.</p>
<pre class="prettyprint lang-py"><code># Return `Decimal` instances in `serializer.data`, not strings.
amount = serializers.DecimalField(
max_digits=10,
decimal_places=2,
coerce_to_string=False
)
</code></pre>
<p>The default JSON renderer will return float objects for uncoerced <code>Decimal</code> instances. This allows you to easily switch between string or float representations for decimals depending on your API design needs.</p>
<h2 id="whats-coming-next">What's coming next.</h2>
<p>3.0 is an incremental release, and there are several upcoming features that will build on the baseline improvements that it makes.</p>
<p>The 3.1 release is planned to address improvements in the following components:</p>
<ul>
<li>Request parsing, mediatypes &amp; the implementation of the browsable API.</li>
<li>Introduction of a new pagination API.</li>
<li>Better support for API versioning.</li>
</ul>
<p>The 3.2 release is planned to introduce an alternative admin-style interface to the browsable API.</p>
<p>You can follow development on the GitHub site, where we use <a href="https://github.com/tomchristie/django-rest-framework/milestones">milestones to indicate planning timescales</a>.</p>
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