Introduced in Python 3.7, dataclasses provide a decorator and functions for automatically adding special methods to user-defined classes. They simplify the process of creating classes that primarily store data.
Why Use Dataclasses?
- Less Boilerplate: Automatically generate methods like
__init__and__repr__. - Type Annotations: Enforce data types for class attributes.
- Immutability: Option to make instances immutable.
Basic Usage
from dataclasses import dataclass
@dataclass
class Person:
name: str
age: int
person = Person(name='Alice', age=30)
print(person)
# Output: Person(name='Alice', age=30)
Default Values
You can assign default values to fields:
@dataclass
class Person:
name: str
age: int = 25
Immutable Dataclasses
Set frozen=True to make instances immutable:
@dataclass(frozen=True)
class Point:
x: int
y: int
Field Metadata
Use field() to add metadata or manage how fields are handled:
from dataclasses import dataclass, field
@dataclass
class InventoryItem:
name: str
price: float = field(default=0.0, metadata={'unit': 'USD'})
Conclusion
Dataclasses simplify the creation of classes that are primarily used to store data. They reduce boilerplate code and enhance readability.