Array Programming with NumPy

Post by konjin » Fri, Sep 18, 2020, 1:52 AM UTC

teorema wrote: post #19

lacker wrote: post #14

Earlier quoted context omitted.

I think this is great. Nature is really a way for scientists to score points, not a publication that you read cover to cover that needs stylistic consistency. Right now the academic citation-count scoring mechanism doesn’t give enough incentive for people to work on the important infrastructure pieces like Numpy. So this is a good step towards putting scientific priorities in the right place.

I definitely think things like the infrastructure don't get enough credit. I also mean no criticism of numpy. But is Numpy per se conceptually that innovative, from a computer science perspective? I guess to me this just seemed unusually introductory, about a specific library for a specific language. Put another way: if I was going to cite numpy, would I cite this? Probably not. Would I cite this paper for any of the…

Post by sndean » Fri, Sep 18, 2020, 2:12 AM UTC

throrthaway wrote: post #6

Ah, just the right time to publish about numpy - right when everyone is moving over to Julia because of numpy's warts.

Post by Fishysoup » Fri, Sep 18, 2020, 2:17 AM UTC

lumost wrote: post #10

ddavis wrote: post #4

Earlier quoted context omitted.

If, going forward, 5% of all papers that use NumPy to get their results actually cite this paper, it will be one of Nature's most cited papers every year.

There's an interesting trend of what content gets published in peer-reviewed journals vs. blogs/github/etc. I suspect there is an audience segment that strongly values peer reviewed pieces that are equivalent content wise to introductory material in a variety of formats. I wonder if github should add a "Review" feature to provide a similar content authoring experience.

Post by flor1s » Fri, Sep 18, 2020, 2:24 AM UTC

etimberg wrote: post #12

teorema wrote: post #3

For some reason this struck me as inappropriate for the outlet. It's a nice piece as an introduction to array programming with numpy, but seemed out of place to me.

Yeah, this is a review article. Nature is not the right spot for it.

Post by BeetleB » Fri, Sep 18, 2020, 2:48 AM UTC

Fishysoup wrote: post #26

alanbernstein wrote: post #18

Earlier quoted context omitted.

I'm interested in Julia, but if numpy has warts, I suppose Julia has not yet had time to even grow its skin.

Theoretically Julia is better for scientific computing, the only issue is its package ecosystem isn't as mature as Python's. But it's growing incredibly fast and there have already been libraries available for a few years that would be really impractical to write and maintain at such a level in C++ for Python. I assume that for science at least Julia will catch on a lot.