Cerberus Example Explanation

This document explains a simple Cerberus example for validating user registration data.

Overview

The example demonstrates how to:

1. Define a schema using Cerberus
2. Create a Validator instance
3. Validate data against the schema
4. Handle validation errors

Code Explanation

Imports and Schema Definition

from cerberus import Validator

schema = {
    'username': {'type': 'string', 'minlength': 3, 'maxlength': 30},
    'email': {'type': 'string', 'regex': r'^[a-zA-Z0-9_.+-]+@[a-zA-Z0-9-]+\.[a-zA-Z0-9-.]+$'},
    'age': {'type': 'integer', 'min': 18, 'max': 99},
    'interests': {'type': 'list', 'schema': {'type': 'string'}}
}

This section imports the Validator class from Cerberus and defines the schema. The schema specifies the structure and constraints for each field in the user data.

Validator Creation

v = Validator(schema)

Here, we create a Validator instance using the defined schema. This validator will be used to check the validity of user data.

Valid Data Example

user_data = {
    'username': 'johndoe',
    'email': 'john@example.com',
    'age': 30,
    'interests': ['python', 'data science', 'hiking']
}

if v.validate(user_data):
    print("Data is valid!")
else:
    print("Validation errors:", v.errors)

This section defines a valid user data dictionary and demonstrates how to use the validator to check it. If the data is valid, it prints a success message; otherwise, it displays the validation errors.

Invalid Data Example

invalid_user = {
    'username': 'jo',  # too short
    'email': 'not_an_email',  # invalid email format
    'age': 15,  # under 18
    'interests': ['python', 42]  # 42 is not a string
}

if v.validate(invalid_user):
    print("Data is valid!")
else:
    print("Validation errors:", v.errors)

This part demonstrates validation with invalid data. It intentionally includes errors to show how Cerberus handles and reports validation failures.

Running the Example

To run this example:

1. Ensure you have Cerberus installed:

   pip install cerberus
   

2. Save the code in a file (e.g., cerberus_example.py)

3. Run the script:

   python cerberus_example.py
   

The script will validate both the valid and invalid user data, printing the results of each validation.

Key Points

• Cerberus allows for flexible schema definition with various validation rules.
• The Validator class is used to create a reusable validator based on the schema.
• The validate method returns a boolean indicating whether the data is valid.
• When validation fails, the errors attribute of the validator contains detailed error information.
• Cerberus can handle nested structures (like the 'interests' list in this example) and apply validation rules to them.