Dataclasses (Python 3.7+) reduce boilerplate for classes that mainly hold data. The @dataclass decorator auto-generates __init__, __repr__, and more from typed fields. Use them instead of plain classes when you're mostly storing attributes with minimal logic. Add frozen=True for immutability.

What you'll learn:

• Using @dataclass for data containers
• Typed fields and default values
• Less code, same behavior

from dataclasses import dataclass


@dataclass
class Point:
    x: float
    y: float


p = Point(3.0, 4.0)
print(p)
print(p.x, p.y)


@dataclass
class Person:
    name: str
    age: int = 0  # default value


alice = Person("Alice", 30)
bob = Person("Bob")  # age defaults to 0
print(alice)
print(bob)

Without @dataclass, you'd write __init__, __repr__, and more by hand. The decorator generates them from the field declarations. Defaults go after required fields.

To run this program:

$ python source/dataclasses.py
Point(x=3.0, y=4.0)
3.0 4.0
Person(name='Alice', age=30)
Person(name='Bob', age=0)

Tip: Use dataclasses for config objects, records, and DTOs. Use regular classes when you have complex behavior.

Try it: Add a @dataclass for a Rectangle with width and height, and a method that returns the area.

Source: dataclasses.py

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