from dataclasses import dataclass
@dataclass
class ThreeDPoint:
x: int | float
y = 0.0
z: int | float = 0.0
point_1 = ThreeDPoint(1.0,2)
point_3 = ThreeDPoint(1,2)
print(point_1 == point_3)
The result is true.
I ran it in python playground. The result said it is true. I think this dataclass module might play some magic trick inside but I am not sure what is exactly happening.
There is no magic trick. In Python, integer 1 and float 1.0 are the same
> 1 == 1.0
True
On the other hand, type(1) is not the same as type(1.0)
> type(1) == type(1.0)
False
If you would like the equality operator to behave the way you suggested (= returning False when x has the same value but different type), then you could define your own equality method for the class, like so:
from dataclasses import dataclass
@dataclass
class ThreeDPoint:
x: int | float
y = 0.0
z: int | float = 0.0
def __eq__(self, other):
for var, var_value in self.__dict__.items():
try:
other_var_value = getattr(other, var)
if not (var_value == other_var_value and type(var_value) is type(other_var_value)):
return False
except AttributeError:
return False
return True
point_1 = ThreeDPoint(1.0, 2)
point_3 = ThreeDPoint(1, 2)
print(point_1 == point_3)
other_var_value = getattr(other, var).
is/is not for the type comparison): Attempt This Online!AttributeError to be raised for you to handle, get rid of the third argument to getattr (which is returned instead of raising an AttributeError, and could be mistaken for the correct value if any of the attributes could legally take a value of False).1.0 equals to 1 in python, so 1.0 == 1 will return true.
Just like Barmar said, when you compare dataclasses you are comparing instances using their attributes, so
1.0 == 1 is true.
2 == 2 is true
Therefore, ThreeDPoint(1.0,2) == ThreeDPoint(1,2) is true.
1.0 == 1give you?1is equal to float1.0.dataclassoverrides the==operation, and compares instances by comparing the attributes (similar to the way dictionaries are compared).