A 1-post collection

Conda (and Anaconda) for python package management and virtual envs

Of installing scipy

I have once wrote a way to install scipy on Windows 64 bit here

scipy is notoriously hard to install on Windows. It's not a bug or anythnig, it is by design.

Python is a super dynamic language designed to be compatible with C extensions.

That means, Python is affordable to be a little bit slow while keeping its interface with C extensions easy and fast. The advent of GIL (Global Interpreter Lock) in CPython is the testimony of this.

(Somebody has summarized why Python (CPython) uses GIL even though it renders multi-core CPUs useless, it's a good and short read here)

In this case, Python can be as dynamic as it wants, and let the C extensions do the dirty and fast part.

However, it comes with a cost, C is not a write once run anywhere programming language. Most of the time, you need to compile it on your machine to guarantee the usability. If you have a good C compiler installed this should not be much of the problem. But most of us, especially Windows users, don't.

Many people have been trying to circumvent this limitation, thus far I have concerned, many packages can now easily be installed by pip without much to do with any compiler i.e. numpy, that means somebody has compiled it beforehand for you.

But that doesn't include scipy. You cannot install it (as of early 2017), you cannot install it using pip without proper configured compiler on Windows with Python 64 bit version installed.

There is some other way namely conda (bare conda can be installed via Miniconda) and Anaconda (which is a full-fledged python install for scientific use, also comes with conda you have no need to install both) by one of which you can install numpy

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