DTOs in Python with Pydantic

Introduction

Overview of DTOs (Data Transfer Objects)

DTOs, or Data Transfer Objects, are essentially containers for data that facilitate communication between different parts of a system. Fowler describes DTOs as a way to streamline communication between processes by bundling multiple parameters into a single call, thereby reducing the number of roundtrips to the server. This consolidation helps minimize network overhead, particularly in remote operations.

Additionally, DTOs offer the advantage of encapsulating serialization logic, which is the process of translating object structures and data into a format suitable for storage and transmission. By centralizing this logic, DTOs provide a single point of control for managing serialization details. Moreover, they foster decoupling between domain models and presentation layers, allowing each to evolve independently.

What is Pydantic?

using Python’s type annotations. At its core, Pydantic allows developers to define data models that enforce strict data types and validation rules, ensuring that the data your application works with is both accurate and reliable.

Unlike traditional data validation libraries, Pydantic leverages Python’s built-in type hints to automatically…