Validator

A simple way to validate dictionary values by using functions.

Installation

• pip3 install simple-validator

Usage

There are 2 main classes to create custom validation classes(Field, Validator).

from validator import Field, Validator


def is_valid_email(val: str):
    """ A horrible way to check if a string is a valid email. """
    passed = False
    err_msg = "{} isn't a valid email.".format(val)

    if '@' in val:
        passed = True
    return passed, err_msg


class UserValidator(Validator):
    """ Validates a user dictionary. """
    email = Field(data_type=str, validators=[is_valid_email])

Validation

The Validator provides the same api as Django forms for checking if all the fields are valid.

data = {
    'email': '[email protected]'
}

user = UserValidator(data)

if user.is_valid():
    # Do things in here...
    email = user.email # Optionally you can do user.data['email']
else:
    print(user.errors)

Required Fields

To make a Field required, all that needs to be done is add required=True as a kwarg to the definition

If the field isn't present it will be added to `Validator.errors under the key for the declared Field that is set to required.

class UserValidator(Validator):
     """ Validates a user dictionary. """

     email = Field(
         data_type=str,
         validators=[is_valid_email],
         required=True
     )

Errors

The Validator.errors attribute is a defaultdict(list).

When validators don't pass, the declared field(Ex: 'email', 'password' etc..) errors gets populated with the return error string from the validator or required errors if the data is missing.

data = {
    'email': 'sean'
}

user = UserValidator(data)

if user.is_valid():
    # Do things in here...
else:
    print(user.errors['email'])

    # "sean isn't a valid email."

Validating Field Types

The Field class has a data_type parameter which should be used to validate a field value before passing it into validators.

This prevents from having try, except, else blocks inside of validator functions because your guaranteed it won't be passed into validators until it's the correct type.

If the field value is the wrong type, it will ony return an error like the one below

data = {
    'email': 1
}

user = UserValidator(data)

if user.is_valid():
    # Do things in here...
else:
    print(user.errors['email'])

    # "'1' is expected to be a 'String'"

You can optionally pass multiple valid data types for a field as a list. As long as the data matches one of the valid types, it will be accepted.

class HeightValidator(Validator):

     height = Field(
         data_type=[int, float],
         validators=[is_valid_height],
         required=True
     )