python's method of constructing a dictionary by means of dict (zip) and {}

In python, this is usually done through thedictcap (a poem)zipcombinations to build key-value pairs.

For example:

aid = [i for i in range(10)]
name = [[1] * 3] * len(aid)
dic1 = dict(zip(aid,name))
print('dic1:', dic1)

Get:

{0: [1, 1, 1],
1: [1, 1, 1],
2: [1, 1, 1],
3: [1, 1, 1],
4: [1, 1, 1],
5: [1, 1, 1],
6: [1, 1, 1],
7: [1, 1, 1],
8: [1, 1, 1],
9: [1, 1, 1]}

This establishes theaidcap (a poem)nameof the one-to-one mapping relationship, using the aid as the key and the second column as the value.

It can also be accessed through thedicfunction of the form or{}direct construction

dic2 = {'aid': aid,'name':name}
print('\ndic2:',dic2)

{
‘aid’: [0, 1, 2, 3, 4, 5, 6, 7, 8, 9],
‘name’: [[1, 1, 1], [1, 1, 1], [1, 1, 1], [1, 1, 1], [1, 1, 1], [1, 1, 1], [1, 1, 1], [1, 1, 1], [1, 1, 1], [1, 1, 1]]
}

This way by creating a new key, the list is stored as a value.

The above two methods, if you want to go through the aids for indexing to get the corresponding value:

Method 1 can be taken out directly, method 2 still need to get to the index and then take the value. So method 1 is faster but in contrast, method 1 stores many key-value pairs, which is not as good as method 2 in terms of storage space.

The space occupancy tests are as follows:

aid = [i for i in range(10)]
name = [[1] * 3] * len(aid)

dic1 = dict(zip(aid,name))
dic2 = {'aid': aid,'name':name}
print('dic1:', dic1)
print((dic1))

print('\ndic2:',dic2)
print((dic2))

dic1: {0: [1, 1, 1], 1: [1, 1, 1], 2: [1, 1, 1], 3: [1, 1, 1], 4: [1, 1, 1], 5: [1, 1, 1], 6: [1, 1, 1], 7: [1, 1, 1], 8: [1, 1, 1], 9: [1, 1, 1]}
360

dic2: {'aid': [0, 1, 2, 3, 4, 5, 6, 7, 8, 9], 'name': [[1, 1, 1], [1, 1, 1], [1, 1, 1], [1, 1, 1], [1, 1, 1], [1, 1, 1], [1, 1, 1], [1, 1, 1], [1, 1, 1], [1, 1, 1]]}
232

After testing, the dictionary footprint and the number of key-value pairs are not linear. If in a very large data, you need to consider the size of the occupied space, for example. 10000 key-value pairs, occupied 7w bytes. (Applied in saving embeddings offline)

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