Debugging reason for python running unreasonably slow when adding numbers

[Oscar Benjamin]

On Tue, 14 Mar 2023 at 16:27, Alexander Nestorov <alexandernst at gmail.com> wrote:
>
> I'm working on an NLP and I got bitten by an unreasonably slow behaviour in Python while operating with small amounts of numbers.
>
> I have the following code:
>
> ```python
> import random, time
> from functools import reduce
>
> def trainPerceptron(perceptron, data):
>   learningRate = 0.002
>   weights = perceptron['weights']
>   error = 0
>   for chunk in data:
>       input = chunk['input']
>       output = chunk['output']
>
>       # 12x slower than equivalent JS
>       sum_ = 0
>       for key in input:
>           v = weights[key]
>           sum_ += v

In Python something like your task here would usually use something
along the lines of NumPy. Your two innermost loops involve adding up a
subset of numbers from a list chosen using a list of indices. This is
something that numpy can do much more efficiently with its fancy
indexing e.g.:

In [3]: a = np.array([1, 2, 3, 4, 5, 6, 7])

In [4]: b = np.array([0, 3, 5])

In [5]: a[b]
Out[5]: array([1, 4, 6])

In [6]: a[b].sum()
Out[6]: 11

This a[b].sum() operation in your code would be weights[input].sum()
and would be much faster than the loop shown (the speed difference
will be larger if you increase the size of the input array).

--
Oscar