Form validation happens when the data is cleaned. If you want to customize
this process, there are various places to make changes, each one serving a
different purpose. Three types of cleaning methods are run during form
processing. These are normally executed when you call the is_valid()
method on a form. There are other things that can also trigger cleaning and
validation (accessing the errors attribute or calling full_clean()
directly), but normally they won’t be needed.
In general, any cleaning method can raise ValidationError if there is a
problem with the data it is processing, passing the relevant information to
the ValidationError constructor. See below
for the best practice in raising ValidationError. If no ValidationError
is raised, the method should return the cleaned (normalized) data as a Python
object.
Most validation can be done using validators - simple helpers that can be
reused easily. Validators are simple functions (or callables) that take a single
argument and raise ValidationError on invalid input. Validators are run
after the field’s to_python and validate methods have been called.
Validation of a form is split into several steps, which can be customized or overridden:
The to_python() method on a Field is the first step in every
validation. It coerces the value to a correct datatype and raises
ValidationError if that is not possible. This method accepts the raw
value from the widget and returns the converted value. For example, a
FloatField will turn the data into a Python float or raise a
ValidationError.
The validate() method on a Field handles field-specific validation
that is not suitable for a validator. It takes a value that has been
coerced to a correct datatype and raises ValidationError on any error.
This method does not return anything and shouldn’t alter the value. You
should override it to handle validation logic that you can’t or don’t
want to put in a validator.
The run_validators() method on a Field runs all of the field’s
validators and aggregates all the errors into a single
ValidationError. You shouldn’t need to override this method.
The clean() method on a Field subclass is responsible for running
to_python(), validate(), and run_validators() in the correct
order and propagating their errors. If, at any time, any of the methods
raise ValidationError, the validation stops and that error is raised.
This method returns the clean data, which is then inserted into the
cleaned_data dictionary of the form.
The clean_<fieldname>() method is called on a form subclass – where
<fieldname> is replaced with the name of the form field attribute.
This method does any cleaning that is specific to that particular
attribute, unrelated to the type of field that it is. This method is not
passed any parameters. You will need to look up the value of the field
in self.cleaned_data and remember that it will be a Python object
at this point, not the original string submitted in the form (it will be
in cleaned_data because the general field clean() method, above,
has already cleaned the data once).
For example, if you wanted to validate that the contents of a
CharField called serialnumber was unique,
clean_serialnumber() would be the right place to do this. You don’t
need a specific field (it’s just a CharField), but you want a
formfield-specific piece of validation and, possibly,
cleaning/normalizing the data.
The return value of this method replaces the existing value in
cleaned_data, so it must be the field’s value from cleaned_data (even
if this method didn’t change it) or a new cleaned value.
The form subclass’s clean() method can perform validation that requires
access to multiple form fields. This is where you might put in checks such as
“if field A is supplied, field B must contain a valid email address”.
This method can return a completely different dictionary if it wishes, which
will be used as the cleaned_data.
Since the field validation methods have been run by the time clean() is
called, you also have access to the form’s errors attribute which
contains all the errors raised by cleaning of individual fields.
Note that any errors raised by your Form.clean() override will not
be associated with any field in particular. They go into a special
“field” (called __all__), which you can access via the
non_field_errors() method if you need to. If you
want to attach errors to a specific field in the form, you need to call
add_error().
Also note that there are special considerations when overriding
the clean() method of a ModelForm subclass. (see the
ModelForm documentation for more information)
These methods are run in the order given above, one field at a time. That is,
for each field in the form (in the order they are declared in the form
definition), the Field.clean() method (or its override) is run, then
clean_<fieldname>(). Finally, once those two methods are run for every
field, the Form.clean() method, or its override, is executed whether
or not the previous methods have raised errors.
Examples of each of these methods are provided below.
As mentioned, any of these methods can raise a ValidationError. For any
field, if the Field.clean() method raises a ValidationError, any
field-specific cleaning method is not called. However, the cleaning methods
for all remaining fields are still executed.
ValidationError¶In order to make error messages flexible and easy to override, consider the following guidelines:
Provide a descriptive error code to the constructor:
# Good
ValidationError(_('Invalid value'), code='invalid')
# Bad
ValidationError(_('Invalid value'))
Don’t coerce variables into the message; use placeholders and the params
argument of the constructor:
# Good
ValidationError(
_('Invalid value: %(value)s'),
params={'value': '42'},
)
# Bad
ValidationError(_('Invalid value: %s') % value)
Use mapping keys instead of positional formatting. This enables putting the variables in any order or omitting them altogether when rewriting the message:
# Good
ValidationError(
_('Invalid value: %(value)s'),
params={'value': '42'},
)
# Bad
ValidationError(
_('Invalid value: %s'),
params=('42',),
)
Wrap the message with gettext to enable translation:
# Good
ValidationError(_('Invalid value'))
# Bad
ValidationError('Invalid value')
Putting it all together:
raise ValidationError(
_('Invalid value: %(value)s'),
code='invalid',
params={'value': '42'},
)
Following these guidelines is particularly necessary if you write reusable forms, form fields, and model fields.
While not recommended, if you are at the end of the validation chain
(i.e. your form clean() method) and you know you will never need
to override your error message you can still opt for the less verbose:
ValidationError(_('Invalid value: %s') % value)
The Form.errors.as_data() and
Form.errors.as_json() methods
greatly benefit from fully featured ValidationErrors (with a code name
and a params dictionary).
If you detect multiple errors during a cleaning method and wish to signal all
of them to the form submitter, it is possible to pass a list of errors to the
ValidationError constructor.
As above, it is recommended to pass a list of ValidationError instances
with codes and params but a list of strings will also work:
# Good
raise ValidationError([
ValidationError(_('Error 1'), code='error1'),
ValidationError(_('Error 2'), code='error2'),
])
# Bad
raise ValidationError([
_('Error 1'),
_('Error 2'),
])
The previous sections explained how validation works in general for forms. Since it can sometimes be easier to put things into place by seeing each feature in use, here are a series of small examples that use each of the previous features.
Django’s form (and model) fields support use of simple utility functions and
classes known as validators. A validator is merely a callable object or
function that takes a value and simply returns nothing if the value is valid or
raises a ValidationError if not. These can be
passed to a field’s constructor, via the field’s validators argument, or
defined on the Field class itself with the
default_validators attribute.
Simple validators can be used to validate values inside the field, let’s have
a look at Django’s SlugField:
from django.core import validators
from django.forms import CharField
class SlugField(CharField):
default_validators = [validators.validate_slug]
As you can see, SlugField is just a CharField with a customized
validator that validates that submitted text obeys to some character rules.
This can also be done on field definition so:
slug = forms.SlugField()
is equivalent to:
slug = forms.CharField(validators=[validators.validate_slug])
Common cases such as validating against an email or a regular expression can be
handled using existing validator classes available in Django. For example,
validators.validate_slug is an instance of
a RegexValidator constructed with the first
argument being the pattern: ^[-a-zA-Z0-9_]+$. See the section on
writing validators to see a list of what is already
available and for an example of how to write a validator.
Let’s first create a custom form field that validates its input is a string containing comma-separated email addresses. The full class looks like this:
from django import forms
from django.core.validators import validate_email
class MultiEmailField(forms.Field):
def to_python(self, value):
"""Normalize data to a list of strings."""
# Return an empty list if no input was given.
if not value:
return []
return value.split(',')
def validate(self, value):
"""Check if value consists only of valid emails."""
# Use the parent's handling of required fields, etc.
super().validate(value)
for email in value:
validate_email(email)
Every form that uses this field will have these methods run before anything else can be done with the field’s data. This is cleaning that is specific to this type of field, regardless of how it is subsequently used.
Let’s create a simple ContactForm to demonstrate how you’d use this
field:
class ContactForm(forms.Form):
subject = forms.CharField(max_length=100)
message = forms.CharField()
sender = forms.EmailField()
recipients = MultiEmailField()
cc_myself = forms.BooleanField(required=False)
Simply use MultiEmailField like any other form field. When the
is_valid() method is called on the form, the MultiEmailField.clean()
method will be run as part of the cleaning process and it will, in turn, call
the custom to_python() and validate() methods.
Continuing on from the previous example, suppose that in our ContactForm,
we want to make sure that the recipients field always contains the address
"fred@example.com". This is validation that is specific to our form, so we
don’t want to put it into the general MultiEmailField class. Instead, we
write a cleaning method that operates on the recipients field, like so:
from django import forms
class ContactForm(forms.Form):
# Everything as before.
...
def clean_recipients(self):
data = self.cleaned_data['recipients']
if "[email protected]" not in data:
raise forms.ValidationError("You have forgotten about Fred!")
# Always return a value to use as the new cleaned data, even if
# this method didn't change it.
return data
Suppose we add another requirement to our contact form: if the cc_myself
field is True, the subject must contain the word "help". We are
performing validation on more than one field at a time, so the form’s
clean() method is a good spot to do this. Notice that we are
talking about the clean() method on the form here, whereas earlier we were
writing a clean() method on a field. It’s important to keep the field and
form difference clear when working out where to validate things. Fields are
single data points, forms are a collection of fields.
By the time the form’s clean() method is called, all the individual field
clean methods will have been run (the previous two sections), so
self.cleaned_data will be populated with any data that has survived so
far. So you also need to remember to allow for the fact that the fields you
are wanting to validate might not have survived the initial individual field
checks.
There are two ways to report any errors from this step. Probably the most
common method is to display the error at the top of the form. To create such
an error, you can raise a ValidationError from the clean() method. For
example:
from django import forms
class ContactForm(forms.Form):
# Everything as before.
...
def clean(self):
cleaned_data = super().clean()
cc_myself = cleaned_data.get("cc_myself")
subject = cleaned_data.get("subject")
if cc_myself and subject:
# Only do something if both fields are valid so far.
if "help" not in subject:
raise forms.ValidationError(
"Did not send for 'help' in the subject despite "
"CC'ing yourself."
)
In this code, if the validation error is raised, the form will display an error message at the top of the form (normally) describing the problem.
The call to super().clean() in the example code ensures that any validation
logic in parent classes is maintained. If your form inherits another that
doesn’t return a cleaned_data dictionary in its clean() method (doing
so is optional), then don’t assign cleaned_data to the result of the
super() call and use self.cleaned_data instead:
def clean(self):
super().clean()
cc_myself = self.cleaned_data.get("cc_myself")
...
The second approach for reporting validation errors might involve assigning the error message to one of the fields. In this case, let’s assign an error message to both the “subject” and “cc_myself” rows in the form display. Be careful when doing this in practice, since it can lead to confusing form output. We’re showing what is possible here and leaving it up to you and your designers to work out what works effectively in your particular situation. Our new code (replacing the previous sample) looks like this:
from django import forms
class ContactForm(forms.Form):
# Everything as before.
...
def clean(self):
cleaned_data = super().clean()
cc_myself = cleaned_data.get("cc_myself")
subject = cleaned_data.get("subject")
if cc_myself and subject and "help" not in subject:
msg = "Must put 'help' in subject when cc'ing yourself."
self.add_error('cc_myself', msg)
self.add_error('subject', msg)
The second argument of add_error() can be a simple string, or preferably
an instance of ValidationError. See Raising ValidationError for
more details. Note that add_error() automatically removes the field
from cleaned_data.
Nov 02, 2020