Consider the following example:
from copy import deepcopy
item = [0]
orig = [item, item]
copy = deepcopy(orig)
orig[0][0] = 1
print(f"{orig=} {copy=}")
copy[0][0] = 2
print(f"{orig=} {copy=}")
The first print outputs what I would expect because the same reference is duplicated in the list.
orig=[[1], [1]] copy=[[0], [0]]
However, the second print surprised me.
orig=[[1], [1]] copy=[[2], [2]]
I would have expected the deepcopy to end up with two independent references inside the copy list. Instead it maintains the property of a single list reference duplicated. I'm guessing that's alluded to in this part of the docs:
A deep copy constructs a new compound object and then, recursively, inserts copies into it of the objects found in the original.
I see that the deepcopy function has a memo argument. Is there anything interesting that could be done with this argument to prevent the duplicated reference, such that the final output would become:
orig=[[1], [1]] copy=[[2], [0]]
If your whole point is to copy data that could come from JSON, i.e. list, dict, string, numbers, bool, then you can trivially implement your own function:
def copy_jsonlike(data):
if isinstance(data, list):
return [copy_jsonlike(x) for x in data]
elif isinstance(data, dict):
return {k: copy_jsonlike(v) for k,v in data.items()}
else:
return data
It has the added bonus of probably being faster than copy.deepcopy
Or, your original solution, json.loads(json.dumps(data)) isn't a bad idea either.