Checkr

Checkr is a powerful validation library that enables developers to easily and accurately validate user input and other data. With Checkr, you can quickly perform a wide range of checks, and ensuring that data conforms to specific formatting requirements. With a simple and intuitive API, Checkr is easy to integrate into any project, and its flexible configuration options make it a powerful tool for building robust and reliable applications.

Installation

pip install checkr

Usage

1. First of all, You need to create a request class that has two methods:

from checkr.BaseRequest import BaseRequest
from typing import Dict


class SampleRequest(BaseRequest):

    @staticmethod
    def authorize() -> bool:
        return True

    @staticmethod
    def rules() -> Dict:
        return {
            'name': 'required|string|min:3',  # You can use the pipe
            'age': ['required', 'numeric', 'gte:18'],  # Or you can just provide a list
        }

2. Use the request class to validate data:

from checkr import validate
from checkr.exceptions import ValidationError


request_data = {
    'name': 'john doe'
}

try:
    validate(SampleRequest, request_data)
except ValidationError as e:
    # Do anything with the validation result here.
    print(e.errors)

Authorizing the request

This method is useful when you want to ensure that validation is performed only by certain parties or by specific users. In your request class, include a static method named authorize that returns a boolean.

Customizing the validation messages

To customize the validation messages returned when the validation of a field fails, you can use the messages method. Here's an example:

from typing import Dict
from checkr.BaseRequest import BaseRequest


class SampleRequest(BaseRequest):
    ...

    @classmethod
    def messages(cls) -> Dict:
        return {
            'name.required': 'Please provide a name!',
            'age.number': 'Oops! not a number!'
        }

    ...

Adding fields before starting the validation

Sometimes, you may find it useful to add a field before the process of validation starts. You can accomplish this by using the prepare_for_validation hook as demonstrated in the following example:

from typing import Dict
from checkr.BaseRequest import BaseRequest


class SampleRequest(BaseRequest):
    ...

    @classmethod
    def prepare_for_validation(cls) -> Dict:
        cls.merge(data_to_add={'foo': 'bar'})

    ...

Adding fields after finishing the validation

It's almost identical to adding fields before starting the validation. You'll use passed_validation hook as demonstrated in the following example:

Notice that this method will not run if the validation finds invalid data.

from typing import Dict
from checkr.BaseRequest import BaseRequest


class SampleRequest(BaseRequest):
    ...

    @classmethod
    def passed_validation(cls) -> Dict:
        cls.merge(data_to_add={'foo': 'bar'})

    ...

Available rules

Adding custom validation rules:

In some cases, it is useful to create a rule that validates an input in custom way like checking if a phone number has a specific format or checking that a city name exists in reality. The following example demonstrates how to accomplish this:

from typing import Any
from checkr.rules.BaseRule import BaseRule

class CustomRule(BaseRule):

    def __str__(self):
        return 'custom_rule'  # required. If not provided, incorrect errors dictionary will be returned

    def validate(self, attribute: str, value: Any) -> bool:
        return True

    def message(self, attribute: str):
        return f'This field failed because something was incorrect'

You can use the validate method to validate against a condition. note that this method takes two arguments:

• attribute which is the name of the field
• value which is the actual value.

There's also another method called message which is used to return a message in case the validation fails. This method receives one parameter, attribute, which is the name of the field under validation.