Ensuring Data Integrity: Constraints and Validations in Python Flask

Invalid data is the boogeyman of web applications: it hides in your database until the worst possible moment, then jumps out and ruins everything by causing confusing errors.It is essential to ensure data integrity and security in your applications. One crucial aspect of achieving this is through the use of constraints and validations. In this blog post, I will explore how to implement constraints and validations in Python Flask to ensure the reliability of your web applications.

Constraints and Validations: Why Are They Important?

Constraints and validations are essential for maintaining the quality and integrity of data within your web application. They help prevent incorrect or malicious data from entering your system, which can lead to various issues such as:
Data Integrity: Constraints and validations ensure that the data stored in your application's database is accurate, consistent, and follows predefined rules. This is crucial for reliable and trustworthy data.
Security: Validations can help protect your application from common security vulnerabilities, such as SQL injection, cross-site scripting (XSS), and data tampering.
User Experience: Implementing constraints and validations can enhance the user experience by providing immediate feedback to users when they enter incorrect or invalid data. Now, let's dive into how to implement constraints and validations in Python Flask.

1. Constraints

Invalid values in our database can cause all kinds of problems when we want to use the data. To keep invalid values out of our database we can use SQLAlchemy constraints. These constraints work at a database level to control the data we add to the database.

unique and nullable Constraints

The nullable constraint allows us to make sure the values added to the columns are not null. We can define this by adding the argument nullable=False to the Column constructor. If it's required that the values in your columns must be unique then the unique constraint can be specified by adding the argument unique=True to the Column constructor.
These two constraints are common in the login froms, the username must be unique to each user also, username and password must not be null. Here is a simple example

class Users(base):
    __tablename__='users'
    username = Column(String, Unique=True, nullable=False)
    password = Column(String, nullable=False)

CheckConstraint

CheckConstraints can be created for columns and tables. The text of the CheckConstraint is passed directly through to the database. Some databases like MySQL do not support CheckConstraints. Here is an example of a Patient table that uses constraints to control input of birth_year and death_year.

class Patient(base):
    __tablename__ = 'patient'
    name = Column(String(length=50), primary_key=True)
    # Constraint defined at the Column level
    birth_year = Column(Integer,
                        CheckConstraint('birth_year < 2023'),
                        nullable=False)
    death_year = Column(Integer)
    # Constraint defined at the Table level
    __table_args__ = (
        CheckConstraint('(death_year is NULL) or (death_year >= birth_year)'),
    )

Here we have a column CheckConstraint which makes sure we cannot add a birth_year that is greater than 2023. We also have a table CheckConstraint that makes sure the death year is after the birth year or the death year is null (meaning that the patient is still alive).

2. Validations

In the context of Python, validations are special method calls that go at the top of model class definitions and prevent them from being saved to the database if their data doesn't look right.
In general, validations consist of code that performs the job of protecting the database from invalid data.
Here is a basic example how we can validate an email.

class EmailAddress(Base):
    __tablename__ = 'address'

    id = Column(Integer, primary_key=True)
    email = Column(String)

    @validates('email')
    def validate_email(self, key, address):
        if '@' not in address:
            raise ValueError("failed simple email validation")
        return address

email = EmailAddress(email='banana')
session.add(email)
# => ValueError: failed simple email validation

In this example, we wrote a validate_email() function, preventing the object from being saved if its email attribute does not include @. We can return a custom message by raising a ValueError with the message.

Conclusion

Implementing constraints and validations in Python Flask is crucial for ensuring data integrity, security, and a better user experience. By using input validation libraries, database constraints, and custom validators, you can build robust web applications that handle data safely and reliably. Remember to always handle both front-end and back-end validations to provide a seamless user experience while maintaining data integrity.