Folks bashing PHP like it's crap but praising any crappy thing if it's built with an esoteric lisp-based language. I mean, if you're starting out, chances are you're better off with js/py or even go but in the end you're paid for the types of problems you solve, not by the language you use... It just turns out that some problems are easier in this or that language, or even people who are good at solving this or that problem just happen to use an specific language (like the bioinformatics people using R when they could have used py).
R is another language that it is bashed constantly, but it is generally much productive in its field (EDA and stats on structured data) than the alternatives like Python.
This. While I'm not sure I'd build a website or something with R, for pretty much anything data related R is a first choice. Even for big data on clusters or something. It's absolutely amazing at what it does. Super easy Fortran and C++ interop. Bonus that it's well enough known in academia and fields like statistics or economics.
I have. Guess I haven't tried to build something bigger with it. Seemed to me to be mostly something to share visualisations, not for building say, a whole CRUD site Rails or Django-style.
You're right - in my experience it's great for, say, creating an online calculator/simulator for something specific but it too fast becomes difficult when you started trying to add features like SSO, persistence etc.
Absolutely agreed! You can feel that R was made for its specific use case. Exploration, visualization, experimentation and modeling just __click__ for me in R in a way Python can never inspire.
In the Python ML world only the matrix libraries - numpy and similar APIs like torch.tensor and jax feel natural and click in my brain. The rest - data frame, visualization, scientific libraries; I'm not very sure how to explain it, but it always feels like some context switch is needed between using Python the language, and calling out to these libraries.
