[Numpy-discussion] Defining a base linux-64 environment [was: Should I use pip install numpy in linux?]

[Robert McGibbon]

Hi all,

I followed Nathaniel's advice and restricted the search down to the
packages included in the Anaconda release (as opposed to all of the
packages in their repositories), and fixed some technical issues with the
way I was doing the analysis.

The new list is much smaller. Here are the shared libraries that the
components of Anaconda require that the system provides on Linux 64:

libpanelw.so.5, libncursesw.so.5, libgcc_s.so.1, libstdc++.so.6, libm.so.6,
libdl.so.2, librt.so.1, libcrypt.so.1, libc.so.6, libnsl.so.1,
libutil.so.1, libpthread.so.0, libX11.so.6, libXext.so.6,
libgobject-2.0.so.0, libgthread-2.0.so.0, libglib-2.0.so.0,
libXrender.so.1, libICE.so.6, libSM.so.6, libGL.so.1.

Many of these libraries are required simply for the interpreter. The
remaining ones that aren't required by the interpreter are, but are
required by some other package in Anaconda are:

libgcc_s.so.1, libstdc++.so.6, libXext.so.6, libSM.so.6,
libgthread-2.0.so.0, libgobject-2.0.so.0, libglib-2.0.so.0, libICE.so.6,
libXrender.so.1, and libGL.so.1.

Most of these are parts of X11 required by Qt (
http://doc.qt.io/qt-5/linux-requirements.html).

-Robert



On Sat, Jan 9, 2016 at 4:42 PM, Robert McGibbon <rmcgibbo at gmail.com> wrote:

> > Maybe a better approach would be to look at what libraries are used on
> by an up-to-date default Anaconda install (on the assumption that this
> is the best tested configuration)
>
> That's not a bad idea. I also have a couple other ideas about how to filter
> this based on using debian popularity-contests and the package graph. I
> will report back when I have more info.
>
> -Robert
>
> On Sat, Jan 9, 2016 at 3:04 PM, Nathaniel Smith <njs at pobox.com> wrote:
>
>> On Sat, Jan 9, 2016 at 3:52 AM, Robert McGibbon <rmcgibbo at gmail.com>
>> wrote:
>> > Hi all,
>> >
>> > I went ahead and tried to collect a list of all of the libraries that
>> could
>> > be considered to constitute the "base" system for linux-64. The
>> strategy I
>> > used was to leverage off the work done by the folks at Continuum by
>> > searching through their pre-compiled binaries from
>> > https://repo.continuum.io/pkgs/free/linux-64/ to find shared libraries
>> that
>> > were dependened on (according to ldd)  that were not accounted for by
>> the
>> > declared dependencies that each package made known to the conda package
>> > manager.
>> >
>> > The full list of these system libraries, sorted in from
>> > most-commonly-depend-on to rarest, is below. There are 158 of them.
>> [...]
>> > So it's not perfect. But it might be a useful starting place.
>>
>> Unfortunately, yeah, it looks like there's a lot of false positives in
>> here :-(. For example your list contains liblzma and libsqlite, but
>> both of these are shipped as dependencies of python itself. So
>> probably someone just forgot to declare the dependency explicitly, but
>> got away with it because the libraries were pulled in anyway.
>>
>> Maybe a better approach would be to look at what libraries are used on
>> by an up-to-date default Anaconda install (on the assumption that this
>> is the best tested configuration), and then erase from the list all
>> libraries that are shipped by this configuration (ignoring declared
>> dependencies since those seem to be unreliable)? It's better to be
>> conservative here, since the end goal is to come up with a list of
>> external libraries that we're confident have actually been tested for
>> compatibility by lots and lots of different users.
>>
>> -n
>>
>> --
>> Nathaniel J. Smith -- http://vorpus.org
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>> https://mail.scipy.org/mailman/listinfo/numpy-discussion
>>
>
>
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