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Data Classes in Python (dataclasses)
The dataclasses is a new module added in Python's standard library since version 3.7. It defines @dataclass decorator that automatically generates constructor magic method __init__(), string representation method __repr__(), the __eq__() method which overloads == operator (and a few more) for a user defined class.
The dataclass decorator has following signature
dataclass(init=True, repr=True, eq=True, order=False, unsafe_hash=False, frozen=False)
All the arguments take a Boolean value indicating whether a respective magic method or methods will be automatically generated or not.
The 'init' argument is True by default. It will automatically generate __init__() method for the class.
Let us define Student class using dataclass decorator as follows
from dataclasses import dataclass @dataclass class Student(object): name : str age : int percent : float
The auto-generated __init__() method is like
def __init__(self, name: str, age: int, percent: float): self.name = name self.age = age self.percent = percent
If the class explicitly defines __init__() method, then init parameter is ignored.
The repr argument is true also by default. Hence __repr__() method will be generated automatically. The __repr__() is a formal string representation of object. If the class already defines __repr__(), this parameter is ignored.
The eq argument is by default true . This will auto-generate the __eq__() method. This method gets called in response to equals comparison operator (==). Again, if the class already defines __eq__(), this parameter is ignored.
If the 'order' parameter is true (the default is False), the magic methods for comparison, __lt__(), __le__(), __gt__(), and __ge__() methods will beauto- generated, they implement comparison operators < <= > ans >= respectively. If order is true and eq is false, a ValueError is raised. If the class already defines any ofthese methods), it reults into TypeError.
unsafe_hash argument if False (the default), a __hash__() method is generated according to how eq and frozen are set.
frozen argument: If true (the default is False), emulates read-only frozen instances.
>>> from data_class import Student
>>> s1=Student('Naveen', 21, 50.50)
>>> s2=Student('Mangesh', 20, 50.00)
>>> s1==s2
Falseasdict()
This function converts class instance into a dictionary object.
>>> import dataclasses
>>> dataclasses.asdict(s1)
{'name': 'Naveen', 'age': 21, 'percent': 50.5}astuple()
This function converts class instance into a tuple object.
>>> dataclasses.astuple(s2)
('Mahesh', 20, 50.0)make_dataclass()
This function creates a new dataclass from the list of tuples given as fields argument.
>>> NewClass=dataclasses.make_dataclass('NewClass', [('x',int),('y',float)])
>>> n = NewClass(10,20)
>>> n
NewClass(x=10, y=20)
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