[jarrettc]

True, but the parent commenter is getting at something important. The article suggests that researchers have found a new, much more concise way to express the solutions to difficult problems. That's different from a library, which merely packages pre-built solutions to a finite set of problems.

It's like the difference between a complete kitchen that fits in your pocket and an iPhone app that lets you order a burrito. The article suggests something like the former. A library which encapsulates 1000 lines of code into a single function call is like the latter.

[derefr]

Even a "kitchen that fits in your pocket" isn't general enough. A library that parses a DSL, such that you can then code in that DSL, is still a lame duck if that library, plus the encodings of all the useful solutions in the domain, add up to more code than just the solutions would be when expressed in a general language. The ROI of (learning the DSL + maintaining the library) would be negative.

On the other hand, there are things like Prolog. You can think of Prolog as a backtracking constraint-solving library, and then another library that parses a DSL for expressing facts and procedural constraints and feeds it to the first library. But Prolog's language isn't really a DSL, because it isn't particular to any domain: there's no closed solution-space where Prolog applies. The efficiency gains you get from Prolog's elision of proceduralized contraint-solution code can apply to any program you write. And so its value is unbounded; its ROI is certainly positive, whatever the cost was to implement it.

That's the comparison that's useful here, I think. Is this something that only solves problems in one domain? Or is this something that could be applied to (at least some little bits of) any problem you encounter?

[baldfat]

Some languages are almost UNUSABLE without libraries. Looking at R with the dplyr, ggplot2, reshape 2 packages being mandatory for my work flow.

Python also has some mandatory libraries if you want to do any specific. Numpy and pandas for statistical analysis make them required.

My code is concise and clean but it is because of these libraries.

I am also certain that there are exceptions.