[Neuroimaging] Technical details managing Python versions and packages.

[JB Poline]

That's a very useful page to me -
A quick possible addition : why / when use the  --user option ? (and get
packages in .local/... )

I also wonder if examples of trouble shooting or install that raised
difficulties could be added there in a "use cases" section : by reading how
some issues where solved I'm sure I could learn a bit more how to debug
install that go wrong.

cheers
JB




On Mon, Aug 3, 2015 at 6:56 AM, Matthew Brett <matthew.brett at gmail.com>
wrote:

> Hi,
>
> On Fri, Jul 31, 2015 at 6:57 PM, Matthew Brett <matthew.brett at gmail.com>
> wrote:
> > Hi Omar,
> >
> > On Fri, Jul 31, 2015 at 6:29 PM, Jesus-Omar Ocegueda-Gonzalez
> > <jomaroceguedag at gmail.com> wrote:
> >> Hello Python experts!,
> >> I just wanted to ask if anyone of you could point me out to a good
> reference
> >> to learn a good way to manage different python versions and their
> >> corresponding packages. This is a bit embarrassing, but I guess the
> >> following story may seem familiar to some people (probably those days
> when
> >> you were python newbies): I had python 2.7 with a lot of packages
> already
> >> installed, some of them installed with pip, some with easy_install, some
> >> with apt-get, some built manually from source code... who knows? I just
> >> sequentially tried each installation way, following instructions I
> found in
> >> random internet pages whenever something went wrong, until one of the
> >> installation instructions suddenly worked, and just moved on. Then, at
> some
> >> point, I tried to install Python 3 to reproduce a bug reported to only
> >> happen there, just to discover that now nothing works, I have no numpy,
> no
> >> nibabel, none of the basic packages, so I tried to "re-install" them
> >> (following instructions from random internet pages when something goes
> >> wrong... again), see the pattern?. So the root cause is obviously that I
> >> have no idea of what's going on behind scenes when I use these
> "mysterious"
> >> installers, and how they affect my environment, which of them are
> compatible
> >> with each other and which are not, etc.
> >>
> >> So, to break the pattern, I think this is time to really learn exactly
> >> what's going on when we "install" packages with different tools, and
> how to
> >> correctly manage different versions. Could anyone point me out to a good
> >> reference to learn these details (e.g. Is there a good way to actually
> >> remove everything so we can start a totally fresh installation)?
> >>
> >> Thank you very much in advance!.
> >> With warm regards,
> >> -A frustrated -but motivated- Python user.
> >
> > I'm afraid I don't know of a very good reference.
> >
> > I think your two options are:
> >
> > * start from scratch using virtualenv and pip;
> > * use conda
> >
> > I prefer virtualenv and pip, because want to support standard Python
> > packaging, and am worried about the effect of handing over Python
> > packaging to one company.  Although conda is open-source, almost all
> > the work and all the hosting is done by employees of Continuum IO.
> >
> > Having said that, I have the impression that conda is a reliable
> > solution to the problem of having multiple different Python
> > environments you want to work on.
> >
> > If you want to go the virtualenv / pip route, I recommend you start
> > from scratch.  In particular, easy_install had a very nasty trick of
> > putting installed packages unconditionally at the top of the Python
> > search path, using `easy-install.pth` files.
> >
> > If you're interested to do that, let me know, I'll write up a summary
> > of what to do.  I guess you are on Debian / Ubuntu?
>
> Despite deafening silence, I did write up the summary:
>
> https://matthew-brett.github.io/pydagogue/installing_on_debian.html
>
> Cheers,
>
> Matthew
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