Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

From Python to NumPy (2017)

labri.fr

Post reply on HN
Print view View original

1–10 of 78 posts

Re: From Python to NumPy (2017)

#3

Post by DigiDigiorno »

I'm totally a fan of educational work aimed at a subset of programmers. And I myself went from Python to NumPy. This would have been great if it was around when I was working with SciPy stuff.

That said, I think a NumPy to Python, or really any big package or framework to Python (e.g. Django to Python) is the normal progression these days. People seem to learn the language through a package and end up with some misleading inferences.

Again, I don't intend to diminish the article, I just see the opposite progression so much I figured I'd comment on it.

Re: From Python to NumPy (2017)

#7

Post by DigiDigiorno »

dhgaiK wrote: post #5

Quoted post unavailable.

I'm half amused and half concerned for your mental health.

There are too many places to start a counter argument. It could start with what MLMs actually are, it could be that many businesses don't care about the talks and use scipy packages, it could be the cause and effect confusion of scipy packages existing and academic users using them--which relates to the Ruby part.

But seriously, I hope I'm wrong, but your post comes off as a bit paranoid and crazy.

Re: From Python to NumPy (2017)

#8

Post by z9znz »

Numpy is a great thing, and also a terrible thing (because it is built on Python).

Python is a terrible language compared to many others, not the least of which is Ruby (and I would include Java, Clojure, Elixir, and even C++ and probably C# and almost certainly F# if I knew them well).

To make matters worse, there's a common mentality amongst Pythonistas of being aggressively complacent. A typical response to a question about a missing capability is, "Why would you ever need that?"

I have a lengthy collection of "why Python sucks" notes. However, I would argue that anyone who disagrees that Python is bad (excepting the practical capabilities afforded by libraries like Numpy which could just as well have been build for other languages) has simply not spent enough time other other, better languages.

Python is Blub, from the Paul Graham essay Beating the Averages. http://www.paulgraham.com/avg.html

Re: From Python to NumPy (2017)

#9

Post by z9znz »

DigiDigiorno wrote: post #7
dhgaiK wrote: post #5

Quoted post unavailable.

I'm half amused and half concerned for your mental health. There are too many places to start a counter argument. It could start with what MLMs actually are, it could be that many businesses don't care about the talks and use scipy packages, it could be the cause and effect confusion of scipy packages existing and academic users using them--which relates to the Ruby part. But seriously, I hope I'm wrong, but your pos…

His MLM analogy does not fit, but I think the point is that Python got where it is because of luck. If the scientific computing and research community (and plenty of physicists) had known a better language, they would not be using Python now. Maybe it helps that Python was installed by default on many Linux systems, and Ruby was not.

Much of the success of Python these days is related to non-CompSci users. And no offense, but many of them are focused entirely on results which have very little concern for code quality, maintainability, or other software engineering concerns.

So now we have startups galore who want to be "AI" or "data science", and their PHBs gravitate to Python because Python is the machine learning language. Or so they've heard.

Ironically, and perhaps one thing the parent poster was alluding to, most AI/ML/data science companies actually end up doing very little of those and instead just doing normal software development. Maybe they have a small sprinkle of data analysis.

Re: From Python to NumPy (2017)

#10

Post by z9znz »

l33t2328 wrote: post #6
dhgaiK wrote: post #5

Quoted post unavailable.

How is prothletising a free tool an MLM scheme?

I'm guessing the parent poster really meant something like "hyped snake oil".

There is absolutely nothing about Python which makes it especially suited to scientific programming or any other kind of programming. In fact, it is poorly designed for most software engineering goals, short of just simple one-file, few line scripts. But those could just as well have been written in many other languages.

Python just happened to be installed by default on most Linux systems, and it was more powerful than *sh. Just maybe one could argue that it was more accessible than perl because it had fewer $#!@$ symbols. If Python had not tried to offer OOP features (entirely built with duct tape, hotglue, and post-it notes) maybe Python projects wouldn't be such a mess. Simple procedural code would be better than the @decorator littered mess which is required to make Python have OO features approximating (but not fully supporting) other languages.

Post reply on HN