[Numpy-discussion] Intel random number package

Nathaniel Smith njs at pobox.com
Thu Oct 27 12:12:58 EDT 2016

On Oct 27, 2016 8:42 AM, "Robert McLeod" <robbmcleod at gmail.com> wrote:
> Releasing NumPy under GPL would make it incompatible with SciPy, which
may be _slightly_ inconvenient to the scientific Python community:
> https://scipy.github.io/old-wiki/pages/License_Compatibility.html
> https://mail.scipy.org/pipermail/scipy-dev/2013-August/019149.html

There's 0 chance that numpy is going to switch to the GPL in general, so
please don't panic. Also, you're misunderstanding license compatibility, so
let's back up a step :-).

The discussion was about whether numpy might potentially, at some
unspecified future date, be available with *optional* GPL code. A numpy
build with optional GPL bits included would be similar to how the numpy
builds that many people use which that are linked to MKL, and thus subject
to MKL's license terms. In both cases the license is no longer numpy's
regular bsd, but has these extra bits added. Neither changes the
availability of bsd-licensed numpy; they just give another option.

And, both numpy+GPL-bits and numpy+MKL-bits are/would be license
*compatible* with scipy in the sense that matters to end users: you can
absolutely use and distribute numpy+(pick one of the above)+scipy together,
and the licenses are happy to allow that.

The sense in which they're both *in*compatible with scipy is just that if
you want to *add code to scipy itself*, then that code can't be GPL like
pyfftw, or proprietary like MKL, because the scipy devs have decided that
they don't want to allow that. That's a decision they've made for good
reasons, but it isn't a legal inevitability, and it doesn't stop *you* from
using and distributing scipy and GPL code together, or scipy and
proprietary code together.

(The real license incompatibility is between GPL and proprietary. Either
one can be mixed with BSD, but they can't be mixed with each other and then
distributed. Ever notice how Anaconda doesn't provide pyfftw? They can't
legally ship both MKL and pyfftw, and they picked MKL. Even then, though,
this license restriction only applies to software distributors: if you as
an end user go and install MKL and pyfftw together in the privacy of your
own cluster, then that's also totally legal.)

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