Research paper "Energy Efficiency across Programming Languages: How does energy, time, and memory relate?"

[Paul Moore]

On 20 September 2017 at 13:58, alister via Python-list
<python-list at python.org> wrote:
> On Tue, 19 Sep 2017 14:40:17 -0400, leam hall wrote:
>
>> On Tue, Sep 19, 2017 at 2:37 PM, Stephan Houben <
>> stephanh42 at gmail.com.invalid> wrote:
>>
>>> Op 2017-09-19, Steven D'Aprano schreef <steve+comp.lang.python@
>>> pearwood.info>:
>>>
>>> > There is a significant chunk of the Python community for whom "just
>>> > pip install it" is not easy, legal or even possible. For them, if its
>>> > not in the standard library, it might as well not even exist.
>>>
>>> But numpy *is* in the standard library, provided you download the
>>> correct version of Python, namely the one from:
>>>
>>> https://python-xy.github.io/
>>>
>>> Stephan
>>>
>>>
>> Many of us can't pip install; it's in the OS supplied vendor repo or it
>> doesn't go on the machines.
>>
>> Leam
>
> dnf install <package>
> or
> apt_get install <package>
>
> most of the mainstream modules seem to be there (certainly numpy)

You're missing the point. A significant number of Python users work on
systems where:

1. They have no admin rights
2. Their corporate or other policies prohibit installing 3rd party
software without approval that is typically difficult or impossible to
get
3. Quite possibly the system has no network access outside of the local intranet
4. The system admins may not be able or willing to upgrade or
otherwise modify the system Python

Writing code that works only with stdlib modules is basically the only
option in such environments.

Having said that, I don't advocate that everything be in the stdlib
because of this. A lot of things (such as numpy) belong as 3rd party
packages. But that doesn't mean that "get XYZ off PyPI" (or "install
XYZ alternative Python distribution/version") is a viable solution to
every problem.

Paul