Python Dataclasses
Dataclasses are a feature introduced in Python 3.7 that provides a decorator and functions for automatically adding generated special methods such as __init__() and __repr__() to user-defined classes. They are primarily used to store data.
Importing the Module
from dataclasses import dataclassBasic Usage
To create a dataclass, decorate a class with @dataclass.
from dataclasses import dataclass
@dataclass
class Point:
x: int
y: int
p = Point(10, 20)
print(p) # Output: Point(x=10, y=20)Default Values
You can provide default values for fields.
from dataclasses import dataclass
@dataclass
class Product:
name: str
price: float
quantity: int = 1
item = Product("Laptop", 999.99)
print(item) # Output: Product(name='Laptop', price=999.99, quantity=1)field() Function
For mutable default values (like lists) or more complex field configuration, use the field() function.
from dataclasses import dataclass, field
from typing import List
@dataclass
class Student:
name: str
grades: List[int] = field(default_factory=list)
s = Student("Alice")
s.grades.append(90)
print(s)Immutable Dataclasses (Frozen)
You can make a dataclass immutable (read-only) by setting frozen=True. This also makes instances hashable, so they can be used as dictionary keys or in sets.
@dataclass(frozen=True)
class Point:
x: int
y: int
p = Point(10, 20)
# p.x = 30 # This would raise a FrozenInstanceErrorPost-Init Processing
The __post_init__ method allows for additional initialization after __init__ has been called.
@dataclass
class Rectangle:
width: float
height: float
area: float = field(init=False)
def __post_init__(self):
self.area = self.width * self.height