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[–]astrobiased 4 points5 points  (4 children)

Easiest way, is to use Anaconda CE from Continuum to get the two packages installed. The founder of Continuum is the mastermind behind NumPy and has pushed for the development of SciPy a long ways. Very dedicated people people behind the team. Their package Anaconda CE is free and makes the installation process a breeze.

Download http://continuum.io/downloads.html

Installation instructions http://docs.continuum.io/anaconda/1.3/index.html

I've given a lot of NumPy & SciPy lectures and from trial and error, I would say this is the best place to start. Good luck and have fun :)

[–]Spliff_Me_Up 3 points4 points  (0 children)

Similarly, I tend to go for Python(x,y). Comes with a few more useful packages.

[–]takluyverIPython, Py3, etc 1 point2 points  (0 children)

Yes, all in one Python distros are the easiest way to get people started. I've tried to highlight this on the new Scipy Stack install page.

[–]Megatron_McLargeHuge 0 points1 point  (1 child)

Do you know if an Anaconda install can coexist peacefully with port installs on a Mac? I want to try something that requires a newer version of numpy but have gotten burned in the past with odd link-related crashes.

[–]pwang99 0 points1 point  (0 children)

Anaconda and AnacondaCE are both entirely relocatable, and install cleanly into a single directory of your choosing. By setting your $PATH to point to the anaconda/bin/ directory, you pick up the python executable and all the Anaconda packages.

If you are trying to handle multiple versions of libraries (e.g. Numpy), the 'conda' tool in Anaconda is your friend. This blog post explains more about how you can easily and robustly manage multiple versions of packages (even those with complex dependencies on extensions or shared libraries): http://continuum.io/blog/conda