Python dataclass Cheatsheet

Saving memory

Specifying slots causes the instance’s attribute values to be stored in the form of an array of slots rather than a dictionary, reducing the processing time required to create the dictionary object and the amount of memory used. On the other hand, referencing an attribute in an instance with slots will slow down the process by several percent.

@dataclass(slots=True)
class Person:
    name: str
    age: int
    address: str

Get variables as dictionary

from dataclasses import dataclass, asdict

@dataclass
class Person:
    name: str
    age: int
    address: str
    
    @classmethod
    def from_defaults(
        cls,
        name: str,
        age: int,
        address: str
    ) -> 'Person':
        return cls(
            name, age, address
        )

p = Person("Alice", 30, "Tokyo")

d = asdict(p)
print(d)
# {'name': 'Alice', 'age': 30, 'address': 'Tokyo'}