Nick Coghlan added the comment:

>From a general philosophical perspective, I share Steve's view - the vast 
>majority of potential CPython users don't want to be consuming upstream Python 
>themselves, they want to be getting it from a redistributor.

This has nothing to do with the quality of the software itself, and everything 
to do with the fact that the open source meta-experience is tailored towards 
DIY co-collaboration, rather than producing a streamlined and completely hassle 
free customer experience for a given problem domain. For education, the 
Raspberry Pi foundation will be a better supplier than us, for data analysis, 
Enthought or Continuum Analytics, for Linux system management, the relevant 
Linux distributor.

For Windows at the moment the default supported redistribution choice is going 
to be ActiveState (that's certainly the one we used when I used to do 
professional Windows based Python development), but our upstream relationship 
there isn't as good as the ones we have the Linux distributors or the data 
analysis focused redistributors.

As Steve says, that leaves the upstream Windows installers trying to fulfil two 
different roles - both being something which users can install purely for their 
own use *and* being suitable for a corporate IT department to incorporate into 
a Standard Operating Environment. At the moment it's more the latter, which is 
also fine for users with full administrative control over their own system, but 
no good for restricted corporate systems.

The immediate workaround is to use the Anaconda distribution from Continuum 
Analytics in such cases, even if you don't need the data analysis components.

In terms of consistency with what we do on the POSIX side, the case can 
definitely be made that "System Python" is the right default behaviour for 
upstream.

The "Python-as-a-library" use case is currently a problem on both POSIX and 
Windows, and PEP 432 goes into several of the reasons why. There are also a 
host of additional issues at least on POSIX related to building extension 
modules, and this is one of the big reasons Continuum Analytics don't use pip 
natively and use conda instead - getting extension module builds to work 
reliably cross-platform when running from a user directory is a genuinely hard 
problem even if you're just linking to C libraries, let alone if you might be 
linking to C++ and FORTRAN libraries as well. That's a large part of why conda 
is on my short list of possible language independent user level package 
management tools to consider proposing for use in Fedora: 
https://fedoraproject.org/wiki/Env_and_Stacks/Projects/UserLevelPackageManagement
 (and it's the *only* platform independent one, since Nix doesn't work on 
Windows)

----------
nosy: +ncoghlan

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