Appending to Nested Dictionary with Identical Keys-CodePudding

I have a list containing values that should be used as keys for a dictionary. Right now the list to be converted to keys looks like the following:

myList = ["A", "B"]

I am converting this list to be the keys to a dictionary by doing the following:

newDict = dict.fromkeys(myList, {"Min":[], "Max":[], "Avg":[]})

When printing newDict I get the output:

{'A': {'Min': [], 'Max': [], 'Avg': []}, 'B': {'Min': [], 'Max': [], 'Avg': []}}

However, when trying to write to the newDict["B"]["Avg"] list, the value gets added to both the "A" and "B" keys:

Code:

newDict["B"]["Avg"].append(111)

Output:

{'A': {'Min': [], 'Max': [], 'Avg': [111]}, 'B': {'Min': [], 'Max': [], 'Avg': [111]}}

Is there for the appended value to only be added to the intended key?

CodePudding user response：

That's because both the keys are given the value {"Min":[], "Max":[], "Avg":[]}, which is the one dict in both case, rather than two identical dicts.

You can verify by calling id on each dict.

[id(v) for v in newDict.values()] # gives [4618156608, 4618156608]

CodePudding user response：

This comes a lot when handling arrays and dicts. What I prefer to do is use list/dict comprehensions to initialize a new object every time.

newDict = {k: {"Min":[], "Max":[], "Avg":[]} for k in myList}

With the initial method, your keys are pointing at the same object with the same id. You may briefly check this with a simple

newDict['A'] is newDict['B'] # True