Let\'s assume you have defined a Python dataclass:
@dataclass
class Marker:
a: float
b: float = 1.0
Another option which may be more elegant:
import dataclasses
marker_a = Marker(1.0, 2.0)
marker_b = Marker(**dataclasses.asdict(marker_a))
The dataclasses.replace
function returns a new copy of the object.
Without passing in any changes, it will return a copy with no modification:
>>> import dataclasses
>>> @dataclasses.dataclass
... class Dummy:
... foo: int
... bar: int
...
>>> dummy = Dummy(1, 2)
>>> dummy_copy = dataclasses.replace(dummy)
>>> dummy_copy.foo = 5
>>> dummy
Dummy(foo=1, bar=2)
>>> dummy_copy
Dummy(foo=5, bar=2)
Note that this is a shallow copy.
@dataclass
class Marker:
a: float
b: float = 1.0
marker_a = Marker(0.5)
marker_b = Marker(**m1.__dict__)
marker_b
# Marker(a=0.5, b=1.0)
If you didn't want to create a new instance, try this:
marker_a = Marker(1.0, 2.0)
marker_b = Marker(11.0, 12.0)
marker_b.__dict__ = marker_a.__dict__.copy()
# result: Marker(a=1.0, b=2.0)
Not sure whether that's considered a bad hack though...
I think that looping over the fields probably is the easiest way. All the other options I can think of involve creating a new object.
from dataclasses import fields
marker_a = Marker(5)
marker_b = Marker(0, 99)
for field in fields(Marker):
setattr(marker_b, field.name, getattr(marker_a, field.name))
print(marker_b) # Marker(a=5, b=1.0)