Python currently is the dominant language in the field of Machine Learning but is often criticized for being slow to perform certain tasks. In this report, we use the well-known N-queens puzzle as a benchmark to show that once compiled using the Numba compiler it becomes competitive with C++ and Go in terms of execution speed while still allowing for very fast prototyping. This is true of both sequential and parallel programs. In most cases that arise in an academic environment, it therefore makes sense to develop in ordinary Python, identify computational bottlenecks, and use Numba to remove them.
Cite
@article{arxiv.2001.02491,
title = {Comparing Python, Go, and C++ on the N-Queens Problem},
author = {Pascal Fua and Krzysztof Lis},
journal= {arXiv preprint arXiv:2001.02491},
year = {2020}
}