Improving python function efficiency by translating to Cython

We are a small company working with decision support tools developed in Python.
We want to test if we can reduce our computation time be introducing Cython functions where we have bottlenecks in our code.
This is an initial test with some simple functions to start (see the attachment), but we would want to expand this approach to a lot of areas if it successful.

The task is to write equivalent functions in Cyhton, compile them and create a benchmark script that shows significant improvements over the initial functions.

We have 4 functions we want rewritten:
linspace_latlon
linspace_leg_space
NumbaNearestIdx
NumbaNearestIdxInList

we have a reference function to compare NumbaNearestIdxInList with
Benchmark_NearestIdxInList, this is the function we want to beat with the Cython version of NumbaNearestIdxInList

The script has been uploaded as a txt file as .py files are not allowed.
The scripts consists of a section with the function definitions and a if __name__ == "__main__": section with the input data and the timing of the current functions.
By running this script you can see the times to beat.

We know that there are many ways to speed up this code, but for this specific project we want to explore the use of Cython.