Commit 063696a8 authored by Mark Robinson's avatar Mark Robinson


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This is the Renku project for the course [Bio334]( and just a note that this project was initially forked from [Laurent Gatto's course run at UC Louvain](
## Working with the project
## Quick Renku instructions:
The simplest way to start your project is right from the Renku
platform - just click on the `Environments` tab and start a new session.
This will start an interactive environment right in your browser.
1. Go to []( Click on the 'Login or Sign Up' button and make yourself an account if you do not have one, either via 'Register', a 'SWITCH edu-ID' or via a GitHub account.
2. Once logged in, go to the Bio334 "project" that Mark made:
3. Near the top right, click on the button to fork the project; this should bring up a box where you can modify the name (you don't need to) and you can click on the 'Fork' button, putting you on the landing page of your (new) project.
4. Click on the environments tab, then 'New' to open a new environment. Hopefully, it shows "Docker image available". For Python or command line work, select /lab; for R work, select, /rstudio (you can always switch back and forth). Leave the number of CPUs at 0.25 and Memory at 1G. Click 'Start environment'. This may take a couple minutes to boot up.
5. Once it's loaded, 'Connect' to the environment. This should open a new browser window with a web link that looks like:[snip]/bio334_spring2020-198a8763/rstudio/[snip]/bio334_spring2020-198a8763/lab/
Note: you can always go back and forth between the `/rstudio` and `/lab` environments by modifying the end of web link, e.g., if you started in /rstudio, but want to move to /lab, you can remove "rstudio", type "lab" in its place and then press enter.
Note: you can upload files from the local computer into your environment via the left tab of the /lab/ environment.
## Working with Renku
Please see [the documentation]( for
more details about Renku.
## How the images were built
So, the stack to build the images that work on Renku is a bit convoluted, so here is a description of the layers of layers that are involved. This is mostly left as a memento to remind myself how I did it. If I were to do it again, it would probably be worth organizing it all into one github repo.
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