Something fascinating happened in the world of scientific publishing last week: The prestigious journal Nature featured an overview[1] of a 15-year-old programming library for the language Python. The widely popular library, called NumPy, gives Python the ability to perform scientific computing functions[2].
Asked on Twitter why a paper is coming out now, 15 years after NumPy's creation, Stefan van der Walt of the University of California at Berkeley's Institute for Data Science, one of the article's authors, said that the publication of the article would give long-overdue formal recognition to some of NumPy's contributors.
Our last paper was ~2010 & not fully representative of the team. While we love that people use our software, many of our team members are in academia where citations count. We hope this will give them the credit needed to receive grant funding & produce more high quality software
— Stefan van der Walt (@stefanvdwalt) September 16, 2020[3]
The paper may be timely in another way. As accomplished as NumPy is in the Python programming world, there are clues in the paper that its future may be even more significant.
NumPy has the prospect of becoming an important piece of infrastructure for computing over and above just being a very valuable library.
As the article points out, NumPy has moved beyond its original scope of functions on multidimensional arrays. It has over time acquired aspects of infrastructure. The authors write, "It is no longer a small community project, but core scientific infrastructure." That's true in more ways than one. NumPy is not only a very valuable library of functions. It is becoming the center of a constellation of emerging libraries.
To understand why you must understand the modern