Declaring a multi dimensional dictionary in python

Question

I need to make a two dimensional dictionary in python. e.g. new_dic[1][2] = 5

When I make new_dic = {}, and try to insert values, I get a KeyError:

new_dic[1][2] = 5 KeyError: 1 

How to do this?

Answer 1

A multi-dimensional dictionary is simply a dictionary where the values are themselves also dictionaries, creating a nested structure:

new_dic = {} new_dic[1] = {} new_dic[1][2] = 5 

You'd have to detect that you already created new_dic[1] each time, though, to not accidentally wipe that nested object for additional keys under new_dic[1].

You can simplify creating nested dictionaries using various techniques; using dict.setdefault() for example:

new_dic.setdefault(1, {})[2] = 5 

dict.setdefault() will only set a key to a default value if the key is still missing, saving you from having to test this each time.

Simpler still is using the collections.defaultdict() type to create nested dictionaries automatically:

from collections import defaultdict  new_dic = defaultdict(dict) new_dic[1][2] = 5 

defaultdict is just a subclass of the standard dict type here; every time you try and access a key that doesn't yet exist in the mapping, a factory function is called to create a new value. Here that's the dict() callable, which produces an empty dictionary when called.

Demo:

>>> new_dic_plain = {} >>> new_dic_plain[1] = {} >>> new_dic_plain[1][2] = 5 >>> new_dic_plain {1: {2: 5}} >>> new_dic_setdefault = {} >>> new_dic_setdefault.setdefault(1, {})[2] = 5 >>> new_dic_setdefault {1: {2: 5}} >>> from collections import defaultdict >>> new_dic_defaultdict = defaultdict(dict) >>> new_dic_defaultdict[1][2] = 5 >>> new_dic_defaultdict defaultdict(<type 'dict'>, {1: {2: 5}}) 

Answer 2

Check it out:

def nested_dict(n, type):     if n == 1:         return defaultdict(type)     else:         return defaultdict(lambda: nested_dict(n-1, type)) 

And then:

new_dict = nested_dict(2, float) 

Now you can:

new_dict['key1']['key2'] += 5 

You can create as many dimensions as you want, having the target type of your choice:

new_dict = nested_dict(3, list) new_dict['a']['b']['c'].append(5) 

Result will be:

new_dict['a']['b']['c'] = [5]