Form and field validation

Form validation happens when the data is cleaned. If you want to customize this process, there are various places you can change, 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 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 error message to the ValidationError constructor. If no ValidationError is raised, the method should return the cleaned (normalized) data as a Python object.

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.

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 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 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. This 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 in 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.

    This method should return the cleaned value obtained from cleaned_data, regardless of whether it changed anything or not.

  • The Form subclass’s clean() method. This method can perform any validation that requires access to multiple fields from the form at once. This is where you might put in things to check that if field A is supplied, field B must contain a valid email address and the like. The data that this method returns is the final cleaned_data attribute for the form, so don’t forget to return the full list of cleaned data if you override this method (by default, Form.clean() just returns self.cleaned_data).

    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 will need to access the _errors attribute on the form, which is described later.

    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.

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.

The clean() method for the Form class or subclass is always run. If that method raises a ValidationError, cleaned_data will be an empty dictionary.

The previous paragraph means that if you are overriding Form.clean(), you should iterate through self.cleaned_data.items(), possibly considering the _errors dictionary attribute on the form as well. In this way, you will already know which fields have passed their individual validation requirements.

Form subclasses and modifying field errors

Sometimes, in a form’s clean() method, you will want to add an error message to a particular field in the form. This won’t always be appropriate and the more typical situation is to raise a ValidationError from Form.clean(), which is turned into a form-wide error that is available through the Form.non_field_errors() method.

When you really do need to attach the error to a particular field, you should store (or amend) a key in the Form._errors attribute. This attribute is an instance of a django.forms.util.ErrorDict class. Essentially, though, it’s just a dictionary. There is a key in the dictionary for each field in the form that has an error. Each value in the dictionary is a django.forms.util.ErrorList instance, which is a list that knows how to display itself in different ways. So you can treat _errors as a dictionary mapping field names to lists.

If you want to add a new error to a particular field, you should check whether the key already exists in self._errors or not. If not, create a new entry for the given key, holding an empty ErrorList instance. In either case, you can then append your error message to the list for the field name in question and it will be displayed when the form is displayed.

There is an example of modifying self._errors in the following section.

What’s in a name?

You may be wondering why is this attribute called _errors and not errors. Normal Python practice is to prefix a name with an underscore if it’s not for external usage. In this case, you are subclassing the Form class, so you are essentially writing new internals. In effect, you are given permission to access some of the internals of Form.

Of course, any code outside your form should never access _errors directly. The data is available to external code through the errors property, which populates _errors before returning it).

Another reason is purely historical: the attribute has been called _errors since the early days of the forms module and changing it now (particularly since errors is used for the read-only property name) would be inconvenient for a number of reasons. You can use whichever explanation makes you feel more comfortable. The result is the same.

Using validation in practice

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.

Using validators

Django’s form (and model) fields support use of simple utility functions and classes known as validators. 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 EmailField:

class EmailField(CharField):
    default_error_messages = {
        'invalid': _('Enter a valid email address.'),
    default_validators = [validators.validate_email]

As you can see, EmailField is just a CharField with customized error message and a validator that validates email addresses. This can also be done on field definition so:

email = forms.EmailField()

is equivalent to:

email = forms.CharField(validators=[validators.validate_email],
        error_messages={'invalid': _('Enter a valid email address.')})

Form field default cleaning

Let’s firstly 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(MultiEmailField, self).validate(value)

        for email in value:

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.

Cleaning a specific field attribute

Continuing on from the previous example, suppose that in our ContactForm, we want to make sure that the recipients field always contains the address "". 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:

class ContactForm(forms.Form):
    # Everything as before.

    def clean_recipients(self):
        data = self.cleaned_data['recipients']
        if "" not in data:
            raise forms.ValidationError("You have forgotten about Fred!")

        # Always return the cleaned data, whether you have changed it or
        # not.
        return data

Cleaning and validating fields that depend on each other

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:

class ContactForm(forms.Form):
    # Everything as before.

    def clean(self):
        cleaned_data = super(ContactForm, self).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.")

        # Always return the full collection of cleaned data.
        return cleaned_data

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.

Note that the call to super(ContactForm, self).clean() in the example code ensures that any validation logic in parent classes is maintained.

The second approach 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:

class ContactForm(forms.Form):
    # Everything as before.

    def clean(self):
        cleaned_data = super(ContactForm, self).clean()
        cc_myself = cleaned_data.get("cc_myself")
        subject = cleaned_data.get("subject")

        if cc_myself and subject and "help" not in subject:
            # We know these are not in self._errors now (see discussion
            # below).
            msg = u"Must put 'help' in subject when cc'ing yourself."
            self._errors["cc_myself"] = self.error_class([msg])
            self._errors["subject"] = self.error_class([msg])

            # These fields are no longer valid. Remove them from the
            # cleaned data.
            del cleaned_data["cc_myself"]
            del cleaned_data["subject"]

        # Always return the full collection of cleaned data.
        return cleaned_data

As you can see, this approach requires a bit more effort, not withstanding the extra design effort to create a sensible form display. The details are worth noting, however. Firstly, earlier we mentioned that you might need to check if the field name keys already exist in the _errors dictionary. In this case, since we know the fields exist in self.cleaned_data, they must have been valid when cleaned as individual fields, so there will be no corresponding entries in _errors.

Secondly, once we have decided that the combined data in the two fields we are considering aren’t valid, we must remember to remove them from the cleaned_data.

Django used to remove the cleaned_data attribute entirely if there were any errors in the form. Since version 1.5, cleaned_data is present even if the form doesn’t validate, but it contains only field values that did validate.