The dataclasses Module

The dataclasses module, introduced in Python 3.7, provides a decorator and helper functions that automatically generate special methods like __init__(), __repr__(), and __eq__() for your classes.

This is useful in data science when you need lightweight classes to store parameters, results, or configuration settings without writing repetitive boilerplate code.

from dataclasses import dataclass

@dataclass
class ExperimentConfig:
    learning_rate: float
    batch_size: int
    epochs: int

With @dataclass, you get a clean constructor, a readable string representation, and comparison capabilities.

More information at the link 👇

dataclasses — Data Classes

Source code: Lib/dataclasses.py This module provides a decorator and functions for automatically adding generated special methods such …

docs.python.org ↗

5 Lesser-Known Python Features Every Data Scientist Should Know - KDnuggets

Learn about five handy Python features that many people miss but can make your data science work easier.

www.kdnuggets.com ↗