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Comment by pen2l | Hacker News Reader

This may be a liiiitle bit off-topic, but I really need to get it off my chest: Python for high-performance scientific computer works beautifully... it's a dream. Scipy/numpy, matplotlib, pandas, ipython. They're all unbelievably awesome. It all just works.

Except, when you're on Windows, and it just doesn't. Just installing things and doing the 'hello world' for aforementioned libraries is laughably impossible.

So, use Python, but use it only on Linux.

(Okay, if you absolutely must do it in Windows: Use Anaconda).

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FUD. I've been using Python on windows for years and between Anaconda and Christoph Gohlke's python packages and I've yet to run into something that didn't just work.

Yeah with Anaconda it's not as bad. But no-one told me that's what I needed if I wanted all the science packages to work on Windows... I'd never even heard of Anaconda before this. It took all of my blood and tears for weeks before I got everything fixed. So I guess what's wrong here is the lack of documentation.

NumPy/SciPy's install page tells you to use Anaconda (or equivalent) for Windows, and build from repositories for Linux.

http://www.scipy.org/install.html

Granted, it does not say "and by the way, when you do that you get tons of other great things like pandas, matplotlib, etc". But they are very clear about not trying to do this yourself.

Interestingly though, Windows version of Numpy on Anaconda is quite a lot faster than what you'll get with Ubuntu, like 2x faster easily. I think it has to do with the fact that AVX instructions are used on the windows linalg routines that it binds to. If you buy MKL of course you get much more speed again.

Christian Gohlke distributes free NumPy binaries built against MKL.

I was going to mention anaconda but you already said that.

This is a problem for many languages that have external libs requiring local compilation (C, C++, etc.), given many of them are principally developed on Linux, with Windows compatibility being an afterthought. Its a problem not unique to Python.

It's similar on Linux. Every time I'm trying to get some outside-written Python software to work, there are many, many troubles.

Python works fine, in your own virtualenv. Outside of it... not so much.

I guess, if you don't know what to do with your money, you can get the similar results on any real operating system (e.g., Mac OS X).

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