Validators¶
Validators can be useful for re-using validation logic between different types of fields.
‒ Django documentation
Most of the time you’re dealing with validation in REST framework you’ll simply be relying on the default field validation, or writing explicit validation methods on serializer or field classes.
However, sometimes you’ll want to place your validation logic into reusable components, so that it can easily be reused throughout your codebase. This can be achieved by using validator functions and validator classes.
Validation in REST framework¶
Validation in Django REST framework serializers is handled a little differently to how validation works in Django’s ModelForm
class.
With ModelForm
the validation is performed partially on the form, and partially on the model instance. With REST framework the validation is performed entirely on the serializer class. This is advantageous for the following reasons:
It introduces a proper separation of concerns, making your code behavior more obvious.
It is easy to switch between using shortcut
ModelSerializer
classes and using explicitSerializer
classes. Any validation behavior being used forModelSerializer
is simple to replicate.Printing the
repr
of a serializer instance will show you exactly what validation rules it applies. There’s no extra hidden validation behavior being called on the model instance.
When you’re using ModelSerializer
all of this is handled automatically for you. If you want to drop down to using Serializer
classes instead, then you need to define the validation rules explicitly.
Example¶
As an example of how REST framework uses explicit validation, we’ll take a simple model class that has a field with a uniqueness constraint.
class CustomerReportRecord(models.Model):
time_raised = models.DateTimeField(default=timezone.now, editable=False)
reference = models.CharField(unique=True, max_length=20)
description = models.TextField()
Here’s a basic ModelSerializer
that we can use for creating or updating instances of CustomerReportRecord
:
class CustomerReportSerializer(serializers.ModelSerializer):
class Meta:
model = CustomerReportRecord
If we open up the Django shell using manage.py shell
we can now
>>> from project.example.serializers import CustomerReportSerializer
>>> serializer = CustomerReportSerializer()
>>> print(repr(serializer))
CustomerReportSerializer():
id = IntegerField(label='ID', read_only=True)
time_raised = DateTimeField(read_only=True)
reference = CharField(max_length=20, validators=[<UniqueValidator(queryset=CustomerReportRecord.objects.all())>])
description = CharField(style={'type': 'textarea'})
The interesting bit here is the reference
field. We can see that the uniqueness constraint is being explicitly enforced by a validator on the serializer field.
Because of this more explicit style REST framework includes a few validator classes that are not available in core Django. These classes are detailed below.
UniqueValidator¶
This validator can be used to enforce the unique=True
constraint on model fields.
It takes a single required argument, and an optional messages
argument:
queryset
required - This is the queryset against which uniqueness should be enforced.message
- The error message that should be used when validation fails.lookup
- The lookup used to find an existing instance with the value being validated. Defaults to'exact'
.
This validator should be applied to serializer fields, like so:
from rest_framework.validators import UniqueValidator
slug = SlugField(
max_length=100,
validators=[UniqueValidator(queryset=BlogPost.objects.all())]
)
UniqueTogetherValidator¶
This validator can be used to enforce unique_together
constraints on model instances.
It has two required arguments, and a single optional messages
argument:
queryset
required - This is the queryset against which uniqueness should be enforced.fields
required - A list or tuple of field names which should make a unique set. These must exist as fields on the serializer class.message
- The error message that should be used when validation fails.
The validator should be applied to serializer classes, like so:
from rest_framework.validators import UniqueTogetherValidator
class ExampleSerializer(serializers.Serializer):
# ...
class Meta:
# ToDo items belong to a parent list, and have an ordering defined
# by the 'position' field. No two items in a given list may share
# the same position.
validators = [
UniqueTogetherValidator(
queryset=ToDoItem.objects.all(),
fields=['list', 'position']
)
]
Note: The UniqueTogetherValidator
class always imposes an implicit constraint that all the fields it applies to are always treated as required. Fields with default
values are an exception to this as they always supply a value even when omitted from user input.
UniqueForDateValidator¶
UniqueForMonthValidator¶
UniqueForYearValidator¶
These validators can be used to enforce the unique_for_date
, unique_for_month
and unique_for_year
constraints on model instances. They take the following arguments:
queryset
required - This is the queryset against which uniqueness should be enforced.field
required - A field name against which uniqueness in the given date range will be validated. This must exist as a field on the serializer class.date_field
required - A field name which will be used to determine date range for the uniqueness constrain. This must exist as a field on the serializer class.message
- The error message that should be used when validation fails.
The validator should be applied to serializer classes, like so:
from rest_framework.validators import UniqueForYearValidator
class ExampleSerializer(serializers.Serializer):
# ...
class Meta:
# Blog posts should have a slug that is unique for the current year.
validators = [
UniqueForYearValidator(
queryset=BlogPostItem.objects.all(),
field='slug',
date_field='published'
)
]
The date field that is used for the validation is always required to be present on the serializer class. You can’t simply rely on a model class default=...
, because the value being used for the default wouldn’t be generated until after the validation has run.
There are a couple of styles you may want to use for this depending on how you want your API to behave. If you’re using ModelSerializer
you’ll probably simply rely on the defaults that REST framework generates for you, but if you are using Serializer
or simply want more explicit control, use on of the styles demonstrated below.
Using with a writable date field.¶
If you want the date field to be writable the only thing worth noting is that you should ensure that it is always available in the input data, either by setting a default
argument, or by setting required=True
.
published = serializers.DateTimeField(required=True)
Using with a read-only date field.¶
If you want the date field to be visible, but not editable by the user, then set read_only=True
and additionally set a default=...
argument.
published = serializers.DateTimeField(read_only=True, default=timezone.now)
Advanced field defaults¶
Validators that are applied across multiple fields in the serializer can sometimes require a field input that should not be provided by the API client, but that is available as input to the validator.
Two patterns that you may want to use for this sort of validation include:
Using
HiddenField
. This field will be present invalidated_data
but will not be used in the serializer output representation.Using a standard field with
read_only=True
, but that also includes adefault=…
argument. This field will be used in the serializer output representation, but cannot be set directly by the user.
REST framework includes a couple of defaults that may be useful in this context.
A default class that can be used to represent the current user. In order to use this, the ‘request’ must have been provided as part of the context dictionary when instantiating the serializer.
owner = serializers.HiddenField(
default=serializers.CurrentUserDefault()
)
A default class that can be used to only set a default argument during create operations. During updates the field is omitted.
It takes a single argument, which is the default value or callable that should be used during create operations.
created_at = serializers.DateTimeField(
default=serializers.CreateOnlyDefault(timezone.now)
)
Limitations of validators¶
There are some ambiguous cases where you’ll need to instead handle validation
explicitly, rather than relying on the default serializer classes that
ModelSerializer
generates.
In these cases you may want to disable the automatically generated validators,
by specifying an empty list for the serializer Meta.validators
attribute.
Optional fields¶
By default “unique together” validation enforces that all fields be
required=True
. In some cases, you might want to explicit apply
required=False
to one of the fields, in which case the desired behaviour
of the validation is ambiguous.
In this case you will typically need to exclude the validator from the
serializer class, and instead write any validation logic explicitly, either
in the .validate()
method, or else in the view.
For example:
class BillingRecordSerializer(serializers.ModelSerializer):
def validate(self, attrs):
# Apply custom validation either here, or in the view.
class Meta:
fields = ['client', 'date', 'amount']
extra_kwargs = {'client': {'required': False}}
validators = [] # Remove a default "unique together" constraint.
Updating nested serializers¶
When applying an update to an existing instance, uniqueness validators will
exclude the current instance from the uniqueness check. The current instance
is available in the context of the uniqueness check, because it exists as
an attribute on the serializer, having initially been passed using
instance=...
when instantiating the serializer.
In the case of update operations on nested serializers there’s no way of applying this exclusion, because the instance is not available.
Again, you’ll probably want to explicitly remove the validator from the
serializer class, and write the code for the validation constraint
explicitly, in a .validate()
method, or in the view.
Debugging complex cases¶
If you’re not sure exactly what behavior a ModelSerializer
class will generate it is usually a good idea to run manage.py shell
, and print an instance of the serializer, so that you can inspect the fields and validators that it automatically generates for you.
>>> serializer = MyComplexModelSerializer()
>>> print(serializer)
class MyComplexModelSerializer:
my_fields = ...
Also keep in mind that with complex cases it can often be better to explicitly
define your serializer classes, rather than relying on the default
ModelSerializer
behavior. This involves a little more code, but ensures
that the resulting behavior is more transparent.
Writing custom validators¶
You can use any of Django’s existing validators, or write your own custom validators.
Function based¶
A validator may be any callable that raises a serializers.ValidationError
on failure.
def even_number(value):
if value % 2 != 0:
raise serializers.ValidationError('This field must be an even number.')
Field-level validation¶
You can specify custom field-level validation by adding .validate_<field_name>
methods
to your Serializer
subclass. This is documented in the
Serializer docs
Class-based¶
To write a class-based validator, use the __call__
method. Class-based validators are useful as they allow you to parameterize and reuse behavior.
class MultipleOf:
def __init__(self, base):
self.base = base
def __call__(self, value):
if value % self.base != 0:
message = 'This field must be a multiple of %d.' % self.base
raise serializers.ValidationError(message)
Accessing the context¶
In some advanced cases you might want a validator to be passed the serializer
field it is being used with as additional context. You can do so by setting
a requires_context = True
attribute on the validator. The __call__
method
will then be called with the serializer_field
or serializer
as an additional argument.
requires_context = True
def __call__(self, value, serializer_field):
...