how to make class decorated using dataclasses to throw error if different field types are assigned?

user_2018343 0
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I am not sure what I am doing wrong. How to prevent the Test class to accept & throw error, when input of different types are passed. I am using Python 3.9.2

from dataclasses import dataclass, fields


@dataclass
class Test:
    a: str = 'a'
    b: int = 1


t = Test(2, 'b')

print(fields(t))
print(type(t.a))
print(type(t.b))

# output
# (venv) D:\Playground>python dataClassesTest.py
# (Field(name='a',type=<class 'str'>,default='a',default_factory=<dataclasses._MISSING_TYPE object at 0x00000232952D5880>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({}),_field_type=_FIELD), Field(name='b',type=<class 'int'>,default=1,default_factory=<dataclasses._MISSING_TYPE object at 0x00000232952D5880>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({}),_field_type=_FIELD))
# <class 'int'>
# <class 'str'>
python-dataclasses python-3.x
1 Answers

This can be solved by adding a __post_init__ method to your dataclass where you can check the types

(Based on this solution, with some corrections)

def __post_init__(self):
    for f in fields(type(self)):
        if not isinstance(getattr(self, f.name), f.type):
            current_type = type(getattr(self, f.name))
            raise TypeError(f"The field `{f.name}` was assigned by `{current_type}` instead of `{f.type}`")

Note that this code doesn't work when importing

from __future__ import annotations

Because then the type field in dataclasses.Field becomes a string

user_150989920
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