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unordered_map<int, vector<float>> equivalent in Python

I need a structure in Python which maps an integer index to a vector of floating point numbers. My data is like:

[0] = {1.0, 1.0, 1.0, 1.0}
[1] = {0.5, 1.0}

If I were to write this in C++ I would use the following code for define / add / access as follows:

std::unordered_map<int, std::vector<float>> VertexWeights;
VertexWeights[0].push_back(0.0f);
vertexWeights[0].push_back(1.0f);
vertexWeights[13].push_back(0.5f);
std::cout <<vertexWeights[0][0];

What is the equivalent structure of this in Python?

How about dictionary and lists like this:

>>> d = {0: [1.0, 1.0, 1.0, 1.0], 1: [0.5, 1.0]}
>>> d[0]
[1.0, 1.0, 1.0, 1.0]
>>> d[1]
[0.5, 1.0]
>>> 

The key can be integers and associated values can be stored as a list. Dictionary in Python is a hash map and the complexity is amortized O(1) .

A dictionary of this format -> { (int) key : (list) value }

d = {}  # Initialize empty dictionary.
d[0] = [1.0, 1.0, 1.0, 1.0] # Place key 0 in d, and map this array to it.
print d[0]
d[1] = [0.5, 1.0]
print d[1]
>>> [1.0, 1.0, 1.0, 1.0]
>>> [0.5, 1.0]
print d[0][0]  # std::cout <<vertexWeights[0][0];
>>> 1.0

I would go for a dict with integers as keys and list as items, eg

m = dict()
m[0] = list()
m[0].append(1.0)
m[0].append(0.5)
m[13] = list()
m[13].append(13.0)

if it is not too much data

In python we can this data structure as Dictionary. Dictionaries are used to store data values in key:value pairs. Example for Dictionary: mydict = { "brand": "Ford", "model": "Mustang", "year": 1964 } we can also perform various operations like add, remove.

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