The goal of this app is to demonstrate the development of a complete data service entirely written in the statistical programming language R. Besides this web application, the project includes the creation of a data refresh process (also written in R) that runs inside an AWS Docker container on a daily schedule. Additionally, efforts were made to develop this project in a reproducible way by controlling the operating environmentand the used R version (through Docker containers), a complete list of all required R packages and their specific versions (through packrat) with the intention to promote collaborative development and to reduce the friction of the setup process of R projects in heterogeneous development environments.
Nice app and very relevant to stuff I am doing for the past year with my team!
You may be interested in my cranly R package https://cran.r-project.org/web/packages/cranly/index.html and the vignettes therein. The networks you produce are a subset of what I have termed "package directive networks" in cranly's terminology.
We'll soon have an interface and a paper on cranly, so I naturally look forward to studying what you've done here!
Hi Ioannis,
Thank you for your kind words. It is always nice to get some positive feedback.
Indeed, cranly seems very relevant to my app. Thank you for pointing me in this direction. I think the networks are a good way to browse the landscape of packages and to discover other popular libraries. I am thinking about adding more features to the network graph, e.g. colorising nodes by publication time to better spot new packages that are interesting for a particular use case scenario. I will check out cranly for additional inspiration as well.
I added a README to the github repo to get the project running inside a Docker container. If anyone has some feedback on how easy/hard/impossible it was to set up locally, I would be keen to learn about it.
Thanks and good luck to everyone for the competition!
