There's already some notes on
https://docs.carpentries.org/topic_folders/hosts_instructors/instructor_tips.html#handling-software-installation
and it would be great to incorporate/edit those notes based on this email
thread!

Cheers,
Christina

On Thu, Sep 20, 2018 at 10:58 AM Kunal Marwaha via discuss <
[email protected]> wrote:

> This sounds like a good blog post (or start of a wiki page)!
>
> On Sep 19, 2018, at 4:49 PM, Katrin Tirok via discuss <
> [email protected]> wrote:
>
> Thanks everyone for the interesting feedback and discussion. I definitely
> learned about some new tools I had not discovered yet, to add one more to
> the round, there is also CoCalc (https://cocalc.com/), which offers
> jupyter notebooks for different languages in the web, base version is free.
>
> What I take for myself from this:
>
>    - I will still follow The Carpentries philosophy of getting each
>    participant set up with a working system locally on their laptop.
>    - If there is decent internet access, I can rely on services like
>    RstudioCloud for R or Microsoft Azure and CoCalc for python with Jupyter as
>    a backup. These online offers can also serve as an alternative for
>    participants whose computer is very slow or for participants who don’t have
>    their own laptop and use a Lan computer in the workshop. For the three
>    services mentioned above, one creates a free account which would be
>    persistent and accessible from any computer (actually any internet device).
>    Google Colab is another option for Jupyter python notebooks although their
>    look is a bit different to the standard notebook.
>    - I also want to include more pair-programming in my teaching, which
>    can also take pressure of individual technical issues (not the main reason
>    though)
>    - If a workshop is in a place with limited internet access, a laptop
>    or mini computer with RstudioServer or JupyterHub with extra router sounds
>    like a good backup option. In addition, there is also the option of
>    installing and run certain software from a usb drive, or an entire
>    operating system (live linux distributions). I remember also the option of
>    creating a local package repository,  e.g. miniCran for R, to use for
>    package installations.
>    - Virtual machines are surely a nice option and I will likely play
>    with them for my own interest, but I tend to leave those out for short
>    workshops, they seem to introduce another level of complexity to explain to
>    participants.
>
>
> summary list with links to tools mentioned:
> RstuioCloud https://rstudio.cloud
>
> Microsoft Azure notebooks https://notebooks.azure.com
>
> CoCalc https://cocalc.com
>
> Colab https://colab.research.google.com
>
> RstudioServer https://www.rstudio.com/products/rstudio-server/
>
> JupyterHub https://jupyter.org/hub
> https://jupyterhub.readthedocs.io/en/stable/
>
> miniCran https://andrie.github.io/miniCRAN/
> https://docs.microsoft.com/en-us/sql/advanced-analytics/r/create-a-local-package-repository-using-minicran?view=sql-server-2017
>
>
> Docker https://www.docker.com
>
> binder https://mybinder.org/
>
> VirtualBox https://www.virtualbox.org
>
> R/Rstudio portable https://sourceforge.net/projects/rportable/
>
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-- 
Christina Koch - Research Computing Facilitator,
University of Wisconsin - Madison <http://www.wisc.edu/>, Center for High
Throughput Computing <http://chtc.cs.wisc.edu/>
Wisconsin Institute for Discovery <http://wid.wisc.edu/>; Advanced
Computing Initiative <http://aci.wisc.edu/>; ACI-REF <https://aciref.org/>
email: [email protected] // phone: (608) 316 - 4041 // calendar:
tinyurl.com/ChristinaCHTC

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