In this blog post, we will explore how to implement custom data types when using SQL Object Relational Mapping (ORM) frameworks. Custom data types allow us to define and use custom classes to represent specific data types in our applications. This can be useful when working with complex data structures or when we want to enforce certain constraints on our data.

Why Use Custom Data Types?

The default data types provided by most SQL databases might not always meet our specific needs. We might have requirements for storing and manipulating data that go beyond what is offered by the standard data types.

By implementing custom data types, we can extend the functionality of the ORM and provide more meaningful representations for our data. For example, we could define a “PhoneNumber” data type that encapsulates the logic for validating and formatting phone numbers.

Implementing Custom Data Types in SQL ORM

The process of implementing custom data types can vary depending on the specific ORM framework being used. However, the general steps are as follows:

1. Define the Custom Data Type Class: Start by creating a class that represents our custom data type. This class will typically inherit from a base class provided by the ORM framework and override certain methods to handle serialization, deserialization, and database representation.

Example code:

from sqlalchemy import types

class PhoneNumber(types.TypeDecorator):
    impl = types.String

    def process_bind_param(self, value, dialect):
        # Validate and format the phone number
        formatted_number = self._validate_and_format(value)
        return formatted_number
        
    def process_result_value(self, value, dialect):
        return PhoneNumber(value)
        
    def _validate_and_format(self, value):
        # Custom logic to validate and format phone numbers
        # ...
        return formatted_number

1. Register the Custom Data Type: Once we have defined our custom data type class, we need to register it with the ORM framework so that it can be used in our models and mappings. This step usually involves associating the custom data type with a corresponding database type.

Example code:

from sqlalchemy import create_engine

engine = create_engine('postgresql://username:password@localhost/mydb')

# Register the custom data type
PhoneNumber().register(engine.dialect)

1. Use the Custom Data Type: With the custom data type registered, we can now use it in our models and mappings. We can define a column of the custom data type in our tables or use it as a property in our model classes.

Example code:

from sqlalchemy import Column, Integer
from sqlalchemy.ext.declarative import declarative_base

Base = declarative_base()

class User(Base):
    __tablename__ = 'users'

    id = Column(Integer, primary_key=True)
    phone_number = Column(PhoneNumber)

Conclusion

Implementing custom data types with SQL ORM frameworks allows us to extend the functionality of the ORM and define more meaningful representations for specific data types. By following the steps outlined in this blog post, we can create and use custom data types in our applications, providing more flexibility and control over our data.

Hashtags: #SQL #ORM