I wrote about Crossref clients back nearly two years ago on this blog: Crossref programmatic clients. Since it’s been a while, it seems worth talking again about the the many ways to work programmatically with Crossref data - and focus in on the Python client habanero since it has some recent updates. The 3 clients work with the main Crossref API, which lets you do things like search for works by title, author, etc....
I gave two talks recently at the annual Crossref meeting, one of which was a somewhat technical overview of programmatic clients for Crossref APIs. Check out the talk here. I talked about the motivation for working with Crossref data by writing code/etc. rather than going the GUI route, then went over the various clients, with brief examples. We (rOpenSci) have been working on the R client rcrossref for a while now, but I’m also working on the Python and Ruby clients for Crossref....
lawn is an R wrapper for the Javascript library turf.js for advanced geospatial analysis. In addition, we have a few functions to interface with the geojson-random Javascript library. lawn includes traditional spatial operations, helper functions for creating GeoJSON data, and data classification and statistics tools. There is an additional helper function (see view()) in this package to help visualize data with interactive maps via the leaflet package (https://github.com/rstudio/leaflet). Note that leaflet is not required to install lawn - it’s in Suggests, not Imports or Depends....