From Scala to Python - Python dataclasses
There are two things I missed when I started working with Python after three years of writing Scala code: types and immutability. Fortunately, it turned out that I missed them only because I did not know Python well enough. There is a way of getting some of that functionality in Python without using external libraries!
Spoiler alert. Don’t expect too much. It won’t be like Scala types ;)
Let’s start with types. Using data classes, it is possible to specify the type of a field in a class. The most basic usage looks like this:
1 2 3 4 5 6 from dataclasses import dataclass @dataclass() class User: name: str age: int
Seems to be good, but look what happens when I try to assign a string to the age field.
1 2 3 >>> u = User('Test', 'aaa') >>> u User(name='Test', age='aaa')
It works! It should not work! There is a more powerful way of defining types which does not work either.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 from typing import NewType Name = NewType('Name', str) Age = NewType('Age', int) @dataclass class User: name: Name age: Age >>> User('Name', 123) User(name='Name', age=123) >>> User(Name('Test'), Name(1555)) User(name='Test', age=1555)
I am so disappointed.
At least, we can specify the expected type of a function parameter and the type of the returned value! Can we?
It makes no sense, because still, nothing stops me from misusing it…
1 2 3 4 5 def name_to_age(name: Name) -> Age: return Age(123) >>> name_to_age(Age(50)) 123
Fortunately, there is one thing which works as expected. Python elegantly solves the problem of immutability. All we need to do is adding a parameter to an annotation.
1 2 3 4 5 6 7 8 9 10 11 @dataclass(frozen = True) class User: name: str age: int >>> u = User('Test', 123) >>> u.name = 'Another user' Traceback (most recent call last): File "<stdin>", line 1, in <module> File "<string>", line 3, in __setattr__ dataclasses.FrozenInstanceError: cannot assign to field 'name'
At least something works. What about types? It seems that I can use them only as a part of the documentation. For data validation, https://pydantic-docs.helpmanual.io library must be used.
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