Pengesahan formulir dan bidang

Pengesahan formulir terjadi ketika data dibersihkan. Jika anda ingin menyesuaikan pengolahan ini, ada beragam tempat untuk membuat perubahan, setiap satu melayani tujuan berbeda. Tiga jenis dari metode membersihkan berjalan selama pengolahan formulir. Ini biasanya dijalankan ketika anda memanggil metode is_valid() pada sebuah formulir. Ada hal-hal lain yang dapat juga memicu membersihkan dan pengesahan (mengakses atribut errors atau memanggil full_clean() langsung), tetapi biasanya mereka tidak akan dibutuhkan.

Secara umum, metode pembersihan apapun dapat memunculkan ValidationError jika ada sebuah masalah dengan data itu sedang olah, melewatkan informasi bersangkut pautke pembangun ValidationError. See below untuk latihan terbaik dalam memunculkan ValidationError. Jika tidak ValidationError dimunculkan, metode harus mengembalikan data dibersihkan (dinormalkan) sebagai sebuah obyek Python.

Most validation can be done using validators - helpers that can be reused. Validators are 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.

Pengesahan dari sebuah formulir dibagi menjadi beberapa langkah, yang dapat disesuaikan atau ditimpa:

  • 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.

  • Metode clean_<fieldname>()` dipanggil di sebuah formulir subkelas -- dimana <fieldname> diganti dengan nama dari atribut bidang formulir. Metode ini melakukan pembersihan apapun yaitu khusus pada atribut tertentu, tidak terkait pada jenis dari bidang bahwa itu adalah. Metode ini tidak melewatkan parameter apapun. Anda akan butuh mencari nilai dari bidang di self.cleaned_data dan mengingat bahwa itu akan menjadi obyek Python pada titik ini, bukan string asli yang diajukan di formulir (itu akan di cleaned_data karena metode clean() bidang umum, diatas, telah membersihkan data sekali).

    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 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.

Contoh dari setiap cara ini disediakan dibawah.

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.

Membangkitkan ValidationError

Untuk membuat pesan-pesan kesalahan lebih elastis dan mudah ditimpa, pertimbangkan panduan berikut ini:

  • Sediakan gambaran code kesalahan pada pembangun:

    # 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)
    
  • Menggunakan kunci-kunci pemetaan daripada pembentukan penempatan. Ini mengadakan menaruh variabel dalam pesanan apapun atau menghilangkan mereka saam sekali ketika menulis kembali pesan:

    # Good
    ValidationError(
        _("Invalid value: %(value)s"),
        params={"value": "42"},
    )
    
    # Bad
    ValidationError(
        _("Invalid value: %s"),
        params=("42",),
    )
    
  • Bungkus pesan dengan gettext untuk mengadakan terjemahan:

    # Good
    ValidationError(_("Invalid value"))
    
    # Bad
    ValidationError("Invalid value")
    

Menaruh semua bersama:

raise ValidationError(
    _("Invalid value: %(value)s"),
    code="invalid",
    params={"value": "42"},
)

Mengikuti panduan ini terutama jika anda menulis formulir digunakan kembali, bidang formulir, dan bidang model.

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).

Membangkitkan banyak kesalahan

Jika anda mengenali banyak kesalahan selama metode pembersihan dan berharap mensinyalkan semua dari mereka ke pengaju formulir, itu memungkinkan melewatkan daftar ke pembangun ValidationError.

Seperti diatas, itu dianjutkan melewatkan daftar dari instance ValidationError dengan code dan params tetapi sebuah daftar string juga akan bekerja:

# Good
raise ValidationError(
    [
        ValidationError(_("Error 1"), code="error1"),
        ValidationError(_("Error 2"), code="error2"),
    ]
)

# Bad
raise ValidationError(
    [
        _("Error 1"),
        _("Error 2"),
    ]
)

Menggunakan pengesahan dalam praktik

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.

Menggunakan pengesah

Django's form (and model) fields support use of utility functions and classes known as validators. A validator is a callable object or function that takes a value and 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.

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 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()

setara pada:

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_]+\Z. 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.

Pembersihan awalan bidang formulir

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 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)

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.

Membersihkan atribut bidang khusus

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
from django.core.exceptions import ValidationError


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

    def clean_recipients(self):
        data = self.cleaned_data["recipients"]
        if "fred@example.com" not in data:
            raise 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

Membersihkan dan memeriksa bidang yang tergantung satu sama lain

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
from django.core.exceptions import ValidationError


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 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. Such errors are non-field errors, which are displayed in the template with {{ form.non_field_errors }}.

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 string, or preferably an instance of ValidationError. See Membangkitkan ValidationError for more details. Note that add_error() automatically removes the field from cleaned_data.

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