easydatamodel - The easiest way to create type-safe dataclasses in Python

Just annotate your fields and you're good to go.

from easydatamodel import Model

class Person(Model):
    name: str
    age: int

Now you have a completely type-safe model that will validate your data for you, every time.

Person(name="John Doe", age=1)  # ✅ OK
Person(name="John Doe", age="timeless")  # ❌ InvalidModelError

# easydatamodel also validates new value assignments
person = Person(name="John Doe", age=1)
person.age = "is but a number" # ❌ raises a TypeError

Install

pip install easydatamodel

Requirements

• Python 3.11+

easydatamodel vs. pydantic and dataclasses

Feature	easydatamodel	pydantic	dataclasses
Validates data on instantiation	✅	✅	❌
Validates data on assignment	✅	Off by default	❌
ClassVar validation	✅	❌	❌
Automagic type coercion by default	❌	✅	❌

Should you use easydatamodel?

easydatamodel is perfect for simple, type-safe dataclasses with minimal effort and low overhead.

However, you should consider using pydantic if you need more advanced features.

easydatamodel as a meta-programming resource

Given the size of the easydatamodel codebase, easydatamodel is a fantastic resource for intermediate and advanced Python developers looking to learn how Python metaprogramming works.

This codebase demonstrates how only a few files of Python code can create a powerful library with an ergonomic syntax.