[Neuroimaging] Technical details managing Python versions and packages.

[JB Poline]

Hi,

I somehow feel less lonely after your mail J.-Omar: I am also deeply
missing some good reference that would described the mechanisms and
interactions behind the scenes of installations operation. I recently tried
to help a colleague with what seems to be tvtk install issue and I have not
yet recovered (or solved) that ...!

With help from colleagues and friends I ended up doing:

* virtualenvs for python stuff only - cf Matthew's argument
* conda for things that require more than python packages - because you
often need more than python stuff sandboxed

It does mean that I have several things installed several times, but it has
reduced (a little) my level of confusion.

cheers
JB


On Fri, Jul 31, 2015 at 11:13 AM, Ariel Rokem <arokem at gmail.com> wrote:

>
>
> On Fri, Jul 31, 2015 at 10:50 AM, Nolan Nichols <bnniii at uw.edu> wrote:
>
>> ​Not exactly what you asked for, but one suggestion is to standardize
>> your approach to installing packages. From my early experience with Python,
>> package management was notoriously confusing and mixing apt-get,
>> easy_install, and pip was a recipe for disaster.
>>
>> I've switched to using the "Anaconda" distribution of Python and it has
>> made installing libraries a really smooth process. I use "miniconda" (
>> http://conda.pydata.org/miniconda.html) and the "conda" tool to install
>> anything available in their software registry and then I use 'pip' to
>> install everything else. I steer clear of apt-get and easy_install.
>>
>> Conda also makes it super easy to create sandboxed environments to test
>> out new tools. For example, once miniconda is installed you can:
>>
>> # create an environment to use nibabel
>>> conda create -n nibabel-env pip ipython scipy
>>> # activate the environment
>>> source activate ​nibabal
>>> # use pip to install a libary not available through conda
>>> pip install nibabel
>>> # turn off the nibabel environment and switch back to the main
>>> installation
>>> source deactivate
>>
>>
>>
> Moreover, you can do things like:
>
> conda create -n nibabel-py2 python=2.7 pip ipython scipy
>
> or
>
> conda create -n nibabel-py3 python=3.4 pip ipython scipy
>
> To create envs with different versions of python (or any other library,
> e.g. `numpy=1.6`)
>
>
>> ​If you give that a shot it will essentially ignore everything else
>> you've installed and give you a clean slate to work from.​
>>
>>
>> ​Cheers,
>>
>> Nolan​
>>
>>
>> On Fri, Jul 31, 2015 at 10:29 AM, 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.
>>> --
>>> "Cada quien es dueño de lo que calla y esclavo de lo que dice"
>>> -Proverbio chino.
>>> "We all are owners of what we keep silent and slaves of what we say"
>>> -Chinese proverb.
>>>
>>> http://www.cimat.mx/~omar
>>>
>>> _______________________________________________
>>> Neuroimaging mailing list
>>> Neuroimaging at python.org
>>> https://mail.python.org/mailman/listinfo/neuroimaging
>>>
>>>
>>
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>>
>
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