ಆಯ್ಕೆಮಾಡಿದರೆ, ನಿಮ್ಮ ನಗರ ಅಥವಾ ನಿಖರ ಸ್ಥಳದಂತಹ ಸ್ಥಳ ಮಾಹಿತಿಯನ್ನು ವೆಬ್ ಅಥವಾ ಮೂರನೇ-ಪಾರ್ಟಿ ಅಪ್ಲಿಕೇಶನ್ಗಳಿಂದ ನೀವು ಸೇರಿಸಬಹುದು. ನಿಮ್ಮ ಟ್ವೀಟ್ ಸ್ಥಳ ಇತಿಹಾಸವನ್ನು ಅಳಿಸುವ ಆಯ್ಕೆಯನ್ನು ನೀವು ಸದಾ ಹೊಂದಿರುತ್ತೀರಿ. ಇನ್ನಷ್ಟು ತಿಳಿಯಿರಿ
I wonder how many 1000s of hours of some of the brightest minds in science are being wasted creating cool #rstats packages that only 10 people will ever use to shave 5 minutes off the time taken to solve a problem and which will stop working with dependency issues 2 years later.
I don't follow all that many people and yet every other day there's a new cool package in my timeline that only a few people will ever have time to learn. But someone will use it, and in a couple of years time someone else will want to run their code, and it will choke.
The standard answer to this seems to be "But it's open source, so you can fix the package when it breaks". Great. So now anyone who wants to use code written by A has to be able to fix B's package, of arbitrary complexity.
I don't have any magical solutions for this, other than suggesting that people think about as long and hard before producing new packages as they would about buying a dog.
Thanks for the advice, person without a single R package! I wonder how many 1000s of hours people wasted by listening to a bad personal coach instead of pursuing a passion until they excel at it.
I certainly haven't spent 1000s of hours coaching people. But I have been coding since 1975 and I have a certain amount of experience of digging systems out of dependency holes. I think that when ppl release code, they need to make their future maintenance commitment clear.
There’s an xkcd comic for everything https://xkcd.com/1205/ pic.twitter.com/EX0EZmtYEW
Love this chart. But note that it's about one person writing code in the hopes of saving *themselves* time. A package can save lots of people time.
Yeah, that’s a very good point!
Yes, but at the possible cost of future time. Of course, it's easier for our future selves to run away than our present selves. 
Tbf, it's hard to predict how useful something is going to be, beforehand. Better to go with it, maybe it'll take off. Analysis paralysis...
I'm coming to this from my 43 years experience of programming, including many horror stories when people discovered they were dependent on stuff that couldn't be fixed. It's sort of an epidemiological problem, rather than an individual one.
Coming at this from my decades covering enterprise IT as a tech journalist as well as programming, my suggestion: Be as smart as you can about dependencies. Does author have a track record? Is pkg popular enough that it's likely to be maintained?
If not, unless the issue is a dependency's dependency, fork the project into your own GitHub so you have copy of functions as they exist when you needed them. Or use something like packrat https://rstudio.github.io/packrat/ .
Deciding *not* to stretch yourself by experimenting with writing packages seems a poor response to a solvable problem. Is “Something may go wrong in 2 years! Why bother?” really the preferred action?
the thing about #rstats pkg development, as many things in life: you *can't* know which approaches will work in advance, it's stochastic and complex (#Hayek etc.). So making (futile) draws may be commendable, not wasteful.https://twitter.com/tslumley/status/1074495575532265473 …
I'm concerned about the cost of the externalities for people who are not aware that selecting a package and committing their own time to building code on it is a stochastic exercise. Maybe there can be some way to determine current package maintenance status?
agreed, pkg maintenance status is important. I always look at # of git commits, CRAN releases, issues, stars, forks, name-brand/reputation of dev ... much like in other FOSS. Worked ok for me. I guess *users* and new ctbs should strongly favor winners such as tidyverse.
You're right. They're much better off writing papers only 4 people will ever read the full text of, that contain findings that have negligible impact on the scientific discourse let alone the community.
It's the same thing in both worlds. A lot of junk gets created but we accept that because that is the exhaust of striving for things that make a lasting impact.
And as many others have said, all work still has value to the person honing their craft. Some of the most venerated R packages are reboots. ggplot2 dplyr etc.
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