There''s a good Jake Vanderplas blog post on this if you haven't seen it
already:
http://jakevdp.github.io/blog/2017/12/05/installing-python-packages-from-jupyter/index.html

Tutorial looks pretty good at first glance, can't wait to teach this

David Nicholson, Ph.D.
https://nicholdav.info/
https://github.com/NickleDave
Prinz lab <http://www.biology.emory.edu/research/Prinz/>, Emory University,
Atlanta, GA, USA


On Wed, Jun 12, 2019 at 11:39 AM David Pugh <[email protected]> wrote:

> Aleksandra,
>
> I have never encountered issues using conda and Jupyter notebooks of the
> kind you describe.  But this long thread confirms that you are not alone.
>
> https://github.com/jupyter/notebook/issues/2359
>
> I will try to add a call out box with a best practice for installing
> jupyter notebook and juypterlab etc.
>
> Thanks for clarifying!
>
>
>
> Sent from my iPhone
>
> On Jun 12, 2019, at 18:20, Giuseppe Profiti <[email protected]>
> wrote:
>
> First, good job David.
> Aleksandra: there are few things to consider when using conda and jupyter.
> Just recently we managed to deploy a jupyterhub on a computing cluster,
> along with several different conda environments.
> Long story short: you should register the environment kernel in the
> jupyter instance. I hope my boss let me write a blog post about it soon.
>
> Best,
> Giuseppe
>
> Il giorno mer 12 giu 2019 alle ore 17:02 Aleksandra Taranov <
> [email protected]> ha scritto:
>
>> David, to answer your question, the reason I stopped using conda and
>> switched to pip installs was that I'd conda install jupyter and conda
>> install packages, but then when I tried to run them, jupyter notebooks
>> couldn't find the package. I'm probably making some very basic error here,
>> but I'm also likely not the only one confused about this.
>>
>> Thanks again for making this great resource.
>>
>> On Wed, Jun 12, 2019, 7:58 AM Michael Sarahan <[email protected]> wrote:
>>
>>> That's a good point, but rather than say "don't use conda at all" -
>>> that's more reason to have custom channels where conda is set up to comply
>>> with those needs.  Conda need not be mutually exclusive with these things,
>>> but it does take some setup to get them working together.
>>>
>>> Saying "don't use conda at all" is ignoring the work that has to happen
>>> either way.  Either you have to reproduce what conda is providing somehow,
>>> or you have to make conda use the part on the system side.  That's
>>> definitely a case-by-case scenario for everyone, and we need to document
>>> both paths.
>>>
>>> For your example of MPI, conda packages are setup to explicitly require
>>> some MPI implementation where necessary.  That package can come from an
>>> actual conda MPICH package, or it can come from a known binary compatible
>>> system installation that has a conda package setup to reference it.  Conda
>>> is not dogmatic about being hermetic (unlike, say, bazel).  Binary
>>> compatibility with external libraries can be pretty tricky, though.
>>>
>>> On Wed, Jun 12, 2019 at 9:48 AM Maxime Boissonneault <
>>> [email protected]> wrote:
>>>
>>>> Hi,
>>>> How about including a part about when *not* to use Conda ?
>>>>
>>>> In particular, if they are going to be computing on a supercomputer,
>>>> they should consult with your cluster specialists first.
>>>> Conda works well on somebody's desktop, but it creates a lot of
>>>> problems on supercomputers, because it does crazy stuff like installing MPI
>>>> by itself instead of relying on staff-installed modules and software
>>>> packages.
>>>>
>>>> Cheers,
>>>>
>>>> Maxime
>>>>
>>>>
>>>> On 2019-06-12 9:49 AM, David Pugh wrote:
>>>>
>>>> All,
>>>>
>>>> I have developed a Software Carpentry style lesson for Conda and would
>>>> be keen to get feedback from the community!
>>>>
>>>> Website:
>>>>
>>>>
>>>> https://kaust-vislab.github.io/introduction-to-conda-for-data-scientists/
>>>>
>>>> Repo:
>>>>
>>>>
>>>> https://github.com/kaust-vislab/introduction-to-conda-for-data-scientists
>>>>
>>>> Thanks and look forward to hearing from you!
>>>>
>>>> David
>>>>
>>>>
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