Stop staying you can't put R in prod.  

I made a blog post with my thoughts and reactions.

#rstats #rust #putRinprod

https://josiahparry.com/posts/2023-07-06-r-is-still-fast.html

Josiah Parry - R is still fast: a salty reaction to a salty blog post

@josiah How about maintainability?

Never met a developer who liked R, and to put things into production, you have to work with devs.
The new people coming into data science all know python. Even among older data scientists, you rarely find one that prefers R (unless they're a statistician working in academia).

Who is going to maintain that code after the person who wrote it leaves for another company?

@orizuru show them quarto, they will love R for generating static websites https://r4ds.hadley.nz/quarto-formats.html#websites-and-books
R for Data Science (2e) - 30  Quarto formats

@jrosell quarto also supports python. So it's a hard sell.

The thing R has got going for it is the plots, they are pretty.
I'm sorry, but the rest just lags behind, from the syntax to the ecosystem (except very specific stats packages).

Just having array indexes starting at 1 will make a Dev's skin crawl.

@orizuru @jrosell funny how many ideas that started in our dead language in just the last 5 years keep getting ported to these mainstream ones.

@milesmcbain @orizuru @jrosell

Dev are fragile creature and they cant handle Julia or Fortan (yup index starting at 1 or "pick your number"). Anyway I am always amazed how everyone can have enough confidence to claim something is dead from punk, to relational database or more recently data science.

@defuneste @milesmcbain @jrosell again, maybe not in your field, but in production environments in most companies it's super rare (and when you see it, it's usually legacy code).

As for Fortran, I definitely never seen it outside of academia, and even there, it was already legacy (people were moving away from it).

@orizuru @milesmcbain @jrosell

NumPy and Scipy need Fortran. (like a lot of packages in R).

@defuneste @milesmcbain @jrosell

Yes, but my point is, it's still a legacy language with a very narrow use-case.

Consider these:
1. How many data scientists actually ever touch Fortran code?

2. How much of the Fortran code has been migrated to more modern languages?

3. How many new libraries are being written in Fortran?

@orizuru @milesmcbain @jrosell

Yes we have different definition of production. Is R less used than Python? 100% Should it be used in high load production env.? Probably not but that does not mean people shouldn't try it. If we took your logic we should all only use Java (it was "the" stuff before).

I nearly never write in c/c++ but I install prog depending on it every day/week (idem Fortran).

Data scientist optimizing math libraries are probably few but we all depend on them.

@defuneste @milesmcbain @jrosell

We probably work in different fields. But when it comes to prod systems in a company, R is an oddity.

The blogpost was about a webserver in R.
In this scenario, you have to think beyond the paper/report you're writing. You have to think about long term maintainability. You have to think about other developers, and how easy is to hire a new person.

> Data scientist optimizing math libraries are probably few but we all depend on them.

100% agree.