Convert a string key to int in a Dictionary

Question

My question is very similar to this one, except I have a dictionary of lists and I\'m interested in changing both the key value and all elements in every list form str

Answer 1

This solution will work for the case where you have an iterable as your value, as in the json you provided.

my_dict = {"0": ["1", "2", "3", "4"], "1": ["0", "2", "3", "4", "27", "94", "95", "97", "128", "217", "218", "317"], "2": ["0", "1", "3", "4", "94", "95"], "3": ["0", "1", "2", "4", "377"], "4": ["0", "1", "2", "3", "27", "28"], "5": ["6", "7", "8"], "6": ["5", "7", "8"], "7": ["5", "6", "8", "14", "23", "40", "74", "75", "76", "362", "371", "372"], "8": ["5", "6", "7", "66"], "9": ["10", "11", "12"], "10": ["9", "11", "12", "56", "130", "131"]}

output_dict = {}
for key, value in my_dict.iteritems():
    output_dict[int(key)] = [int(item) for item in value]

output_dict

Output:

{0: [1, 2, 3, 4],
 1: [0, 2, 3, 4, 27, 94, 95, 97, 128, 217, 218, 317],
 2: [0, 1, 3, 4, 94, 95],
 3: [0, 1, 2, 4, 377],
 4: [0, 1, 2, 3, 27, 28],
 5: [6, 7, 8],
 6: [5, 7, 8],
 7: [5, 6, 8, 14, 23, 40, 74, 75, 76, 362, 371, 372],
 8: [5, 6, 7, 66],
 9: [10, 11, 12],
 10: [9, 11, 12, 56, 130, 131]}

For the second part of the question, you can use a dict comprehension in line as you read the file. It's obfuscated as hell though.

with open('coauthorshipGraph.txt', 'r') as f:
    json_data = { int(key) : [int(item) for item in value] for key, value in json.load(f).iteritems()}

json_data

This yields the same output as above.

Answer 2

d = {'1':'145' , '2':'254' , '3':'43'}
d = {int(k):int(v) for k,v in d.items()}
>>> d
{1: 145, 2: 254, 3: 43}

for lists in values

>>> d = { '1':['1', '2', '3', '4'] , '2':['1', '4'] , '3':['43','176'] }
>>> d = {int(k):[int(i) for i in v] for k,v in d.items()}

in your case:

coautorshipDictionary = {int(k):int(v) for k,v in json.load(json_data)}

or

coautorshipDictionary = {
    int(k):[int(i) for i in v] for k,v in json.load(json_data)}

Answer 3

Similar to Decency's answer, but taking advantage of the object_hook argument:

coautorshipDictionary = json.load(json_data, object_hook=lambda d: {int(k): [int(i) for i in v] if isinstance(v, list) else v for k, v in d.items()}) # iteritems() for Python 2

The main advantage of this method is that, if you ever end up with any nested dicts, the loader will handle each nested dict on its own as it loads the data without you having to write code to walk through your result dict. You could also add in checks for cases where values in lists are not numeric strings or the lists themselves contain dicts as well, if your JSON structure gets more complicated, and if your data will only have lists as the values for your top-level dict you can remove the if isinstance(v, list) else v part.