Add RStudio to the base image #64
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- Bump to Ubuntu 20.04. This brings in lots of newer packages, but particularly Python 3.8 (https://phabricator.wikimedia.org/T265957). Many new packages are 3.7+ only. - Use upstream R deb packages (https://cran.r-project.org/bin/linux/ubuntu/), than those from Ubuntu. This is maintained by the same folks who do R in debian. This brings us R 4.x (https://phabricator.wikimedia.org/T268923), but more importantly enables binary package installation. - Use packagemanager.rstudio.com to install R packages. This is a huge benefit - it can install any version of packges, and it has binary package builds for most of them! These binary packages are built against focal + the upstream R debs. See announcement info here: https://blog.rstudio.com/2020/07/01/announcing-public-package-manager/. This reduces the user image build time a *lot* - Put R packages in /srv/r, to match /srv/paws for our venv. Users can more easily install R packages temporarily now, and we don't mess with things under `/usr`. It also simplifies our Dockerfile, reducing number of times we have to switch to root. - Redirect most stdout from apt-get to /dev/null. We still get stderr, so no real functionality lost. - Remove some explicit nbextension enable / install commands. These are no longer necessary. - Specify a loose pin for notebook & jupyterlab versions.
Uses github.com/jupyterhub/jupyter-rsession-proxy/ to provide RStudio :) You can test this with: $ docker build -t paws images/singleuser $ docker run -p 8888:8888 paws jupyter notebook --ip=0.0.0.0 This should start a notebook server, and print a URL with a token you can use to connect to the docker container & test the image. Since this uses port forwarding, it'll most likely only work if you are running docker locally (and not via docker-machine)
yuvipanda
requested review from
crookedstorm and
chicocvenancio
and removed request for
crookedstorm
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chicocvenancio
approved these changes
May 22, 2021
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Uses github.com/jupyterhub/jupyter-rsession-proxy/ to provide
RStudio :)
You can test this with:
$
docker build -t paws images/singleuser$
docker run -p 8888:8888 paws jupyter notebook --ip=0.0.0.0This should start a notebook server, and print a URL with a token
you can use to connect to the docker container & test the image.
Since this uses port forwarding, it'll most likely only work if you
are running docker locally (and not via docker-machine)
You can open RStudio by going to 'New -> RStudio'
Depends on #62