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Jupyter is lovely (and JupyterLab looks delicious), but the set up required to achieve a reproducible local server with the R kernel and versioned R packages is

Jupyter is lovely (and JupyterLab looks delicious), but the set up required to achieve a reproducible local server with the R kernel and versioned R packages is 100% not. Installing R packages through anaconda is like pulling teeth and the docker images for my Jupyter notebooks push past 6GB and take multiple cups of tea to build. Is there a good solution I'm missing? A good hosted solution perhaps?

enriquto 8y ago
you have google colab notebooks: https://colab.research.google.com https://colab.research.google.com
ianhowson 8y ago
I run https://rnotebook.io https://rnotebook.io -- it's free for the foreseeable future. The Docker image is 6GB.
smortaz 8y ago
https://notebooks.azure.com https://notebooks.azure.com (python, r, f#)
kvlr 8y ago
I run https://nextjournal.com https://nextjournal.com We archive full-stack reproducibility by allowing you to install arbitrary software and version these environments using docker. You can reuse these in other articles or pull and use them locally. `xoxo` is a signup code you can you if you want to give it a try.
- thomasfedb 8y ago
  Looks cool, do you have an article that explains the stack from a technical perspective? Is this based on Jupyter?
  - kvlr 8y ago
    Not yet. It isn't based on Jupyter but it's all written in Clojure. Been meaning to do a writeup on our stack for some time… In addition to our own runtime protocol, we support Jupyter kernels and you can import Jupyter and (R)markdown documents.
setgree 8y ago
I work for a company, Code Ocean, that aims to solve this issue. We have a custom-UI for installing packages through a variety of package managers, including Conda, CRAN, etc. Here's an example of some Julia notebooks being rendered to HTML with the environment fully configured and accessible https://codeocean.com/2018/08/16/counterexamples-on-the-monotonicity-of-delay-optimal-transmission-policies-in-energy-harvesting-communication-systems https://codeocean.com/2018/08/16/counterexamples-on-the-mono...

enriquto 8y ago

you have google colab notebooks: https://colab.research.google.com https://colab.research.google.com

ianhowson 8y ago

I run https://rnotebook.io https://rnotebook.io -- it's free for the foreseeable future. The Docker image is 6GB.

smortaz 8y ago

https://notebooks.azure.com https://notebooks.azure.com (python, r, f#)

kvlr 8y ago

I run https://nextjournal.com https://nextjournal.com We archive full-stack reproducibility by allowing you to install arbitrary software and version these environments using docker. You can reuse these in other articles or pull and use them locally. `xoxo` is a signup code you can you if you want to give it a try.

thomasfedb 8y ago
Looks cool, do you have an article that explains the stack from a technical perspective? Is this based on Jupyter?
- kvlr 8y ago
  Not yet. It isn't based on Jupyter but it's all written in Clojure. Been meaning to do a writeup on our stack for some time… In addition to our own runtime protocol, we support Jupyter kernels and you can import Jupyter and (R)markdown documents.

setgree 8y ago

I work for a company, Code Ocean, that aims to solve this issue. We have a custom-UI for installing packages through a variety of package managers, including Conda, CRAN, etc. Here's an example of some Julia notebooks being rendered to HTML with the environment fully configured and accessible https://codeocean.com/2018/08/16/counterexamples-on-the-monotonicity-of-delay-optimal-transmission-policies-in-energy-harvesting-communication-systems https://codeocean.com/2018/08/16/counterexamples-on-the-mono...