Open Source

I’m sure there’s already a way to do this, but here goes. OR maybe this is an anti-pattern. Either way, this is me, asking the stupid question. I ran into this a few hours ago: Sys.unsetenv("ENTREZ_KEY") library(brranching) mynames <- c("Poa annua", "Salix goodingii", "Helianthus annuus") phylomatic_names(taxa = mynames, format='rsubmit') No ENTREZ API key provided Get one via taxize::use_entrez() See https://ncbiinsights.ncbi.nlm.nih.gov/2017/11/02/new-api-keys-for-the-e-utilities/ No ENTREZ API key provided Get one via taxize::use_entrez() See https://ncbiinsights....

The longer you do anything, the more preferences you may develop for that thing. One of these things is making R packages. One preference I’ve developed is in limiting package dependencies - or at least limiting to the least painful dependencies - in the packages I maintain. Ideally, if a base R solution can be done then do it that way. Everybody has base R packages if they are using R, so you can’t fail there, at least on package installation....

I occasionally think about these various topics and ping back and forth between them, thinking I’ve got to make a package more user friendly, then back to thinking oh, I really should make this package easier to maintain, but what if that makes it less user friendly? I’ve wanted to get these thoughts written down for a while now, so here goes. User friendliness and code fragility It’s an unassailable good to make your code more user friendly....

In rOpenSci - as in presumably most open source projects - we want the entire project to be sustainable, but also each individual software project to be sustainable. A big part of each software project (aka R package in this case) being sustainable is the people making it, particularly whether: how many contributors a project has, and how contributions are spread across contibutors There are discussions going on about how to increase contributors to any given project....

Measuring use of open source software isn’t always straightforward. The problem is especially acute for software targeted largely at academia, where usage is not measured just by software downloads, but also by citations. Citations are a well-known pain point because the citation graph is privately held by iron doors (e.g., Scopus, Google Scholar). New ventures aim to open up citation data, but of course it’s an immense amount of work, and so does not come quickly....

UPDATE: there were some errors in the tests for taxize, so the binaries aren’t avaiable yet. You can install from source though, see below. Getting taxonomic information for the set of species you are studying can be a pain in the ass. You have to manually type, or paste in, your species one-by-one. Or, if you are lucky, there is a web service in which you can upload a list of species....