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It seems like the point of the article is that that push is insubstantial, if it even exists. Given the language has been around this long it's a bit worrying t

by s_Hogg 4y ago

It seems like the point of the article is that that push is insubstantial, if it even exists. Given the language has been around this long it's a bit worrying that stuff like that is the potential target for moving a language forward. Julia has always had a reputation in my mind at least of being "by academics, for academics" and there's unfortunately a dark side to that in terms of reliability and maintainability. The concept and goals are great, which is annoying. If this language had stayed focussed on the basics, it would be extremely handy for someone like me who trains and deploys models in an edge computing environment. No way I'm doing that with stuff like this going on.

NeutralForest 4y ago
I suppose we'll see? Honestly this is maybe an opportunity to adjust some goals of the language if this is the feeling people are having now and outreach to purely CS and SE people will probably be needed but seeing the presence it has at the MIT, I don't see it being a problem.
fluidcruft 4y ago
For what it's worth many people feel similarly about R. R is great for people actively working in statistics research (I assume because that's what I'm always told). But for a lot of us who just want to do some analysis, it's constantly breaking and we've learned to default to just starting from scratch when we need to revisit something we did a few years ago. Or we figure out how to buy a commercial system.
- tylermw 4y ago
  R is not constantly breaking. R Core does a remarkable job ensuring backwards compatibility. There are only a few prominent examples of significant "breaking" behavior across decades of the language existing, and those can often be reverted by setting an option (e.g. `options(stringsAsFactors = TRUE)`). But backwards compatibility is the primary concern with any update to the R language or the packages maintained by R Core. Now, if you're thinking about changes introduced by a specific user-contributed package breaking your analysis, that can indeed be a problem. But that can't be blamed on the R language. And the main user-contributed R statistics packages that have been around for decades (such as lme4 or survival) are mature and stable.
- deleted 4y ago
  [deleted]

by s_Hogg 4y ago

NeutralForest 4y ago

I suppose we'll see? Honestly this is maybe an opportunity to adjust some goals of the language if this is the feeling people are having now and outreach to purely CS and SE people will probably be needed but seeing the presence it has at the MIT, I don't see it being a problem.

fluidcruft 4y ago

For what it's worth many people feel similarly about R. R is great for people actively working in statistics research (I assume because that's what I'm always told). But for a lot of us who just want to do some analysis, it's constantly breaking and we've learned to default to just starting from scratch when we need to revisit something we did a few years ago. Or we figure out how to buy a commercial system.

tylermw 4y ago
R is not constantly breaking. R Core does a remarkable job ensuring backwards compatibility. There are only a few prominent examples of significant "breaking" behavior across decades of the language existing, and those can often be reverted by setting an option (e.g. `options(stringsAsFactors = TRUE)`). But backwards compatibility is the primary concern with any update to the R language or the packages maintained by R Core. Now, if you're thinking about changes introduced by a specific user-contributed package breaking your analysis, that can indeed be a problem. But that can't be blamed on the R language. And the main user-contributed R statistics packages that have been around for decades (such as lme4 or survival) are mature and stable.
deleted 4y ago
[deleted]