Le mercredi 08 juillet 2015 à 13:20 -0700, Brandon Taylor a écrit : > All functions. Well, I don't know of any language which doesn't have scoping rules...
Anyway, I didn't say scoping rules are necessarily confusing, I was only referring to R formulas. But according to the examples you posted, your question appears to be different. Regards > On Wednesday, July 8, 2015 at 4:18:09 PM UTC-4, Milan Bouchet-Valat > wrote: > > Le mercredi 08 juillet 2015 à 12:57 -0700, Brandon Taylor a écrit : > > > > > If scoping rules are too complicated and cause confusion, why are > > > > > they built into the base implementation of function? > > What do you mean? Which function? > > > > > On Wednesday, July 8, 2015 at 3:48:52 PM UTC-4, Milan Bouchet > > -Valat > > > wrote: > > > > Le mercredi 08 juillet 2015 à 12:34 -0700, Brandon Taylor a > > écrit : > > > > > > > > > I was aware of those packages (though I hadn't read the > > > > discussions > > > > > referenced). Macros are great but they are incredibly > > difficult > > > > to > > > > > reason with concerning issues of scope (at least for me). > > > > Deifying > > > > > environments could solve all of these issues (and so much > > more) > > > > in > > > > > one fell swoop. > > > > On the contrary, I think well-designed macros can be much > > easier to > > > > > > > > think about than environments in R. If the macro takes a > > DataFrame > > > > object and an expression, there's no ambiguity about what the > > scope > > > > is. > > > > This is even better if variables that should be found in the > > data > > > > frame > > > > are passed as symbols, like :var, while standard variables are > > > > specified as usual. > > > > > > > > On the other hand, I find R formulas too flexible and complex > > to > > > > reason > > > > about. You never know whether an object will be found in the > > > > formula's > > > > environment, in one of the parent environments of the > > > > function/package > > > > you called, in your function, or in the global environment. > > > > > > > > > > > > Regards > > > > > > > > > On Wednesday, July 8, 2015 at 3:20:00 PM UTC-4, David Gold > > wrote: > > > > > > > > > > Some of these issues have been thought about fairly > > extensively > > > > by > > > > > > the stats community in particular, precisely on account of > > the > > > > use > > > > > > cases you cite: > > > > > > > > > > > > https://github.com/JuliaStats/DataFrames.jl/pull/472 > > > > > > https://github.com/JuliaStats/DataFrames.jl/issues/504 > > > > > > > > > > > > I think that the matter is still very much an open > > question. I > > > > have > > > > > > no sense that anything is going to be added to Base Julia > > > > itself. > > > > > > Currently, the best way (that I know of, anyway) to achieve > > the > > > > > > > > > > delayed evaluation effect is via the use of macros. See for > > > > > > > > instance: > > > > > > > > > > > > https://github.com/JuliaStats/DataFramesMeta.jl > > > > > > https://github.com/one-more-minute/Lazy.jl > > > > > > > > > > > > I'm hope somebody else will be able to pop in an give a > > more > > > > > > thorough answer, but the above may at least be a place to > > > > start. > > > > > > > > > > > > On Wednesday, July 8, 2015 at 2:03:45 PM UTC-4, Brandon > > Taylor > > > > > > wrote: > > > > > > > Hadley Wickham's lazyeval package in R is pretty cool in > > that > > > > you > > > > > > > can attach an environment to an expression, pass it in > > and > > > > out of > > > > > > > functions with various modifications, and then evaluate > > the > > > > > > > expression within the original environment (or any other > > > > > > > environment that you choose). R in general has the > > functions > > > > like > > > > > > > list2env and list(environment()) that allow one to > > convert an > > > > > > > > > > > environment into a list and back again (list being the R > > > > > > > equivalent of a Dict). Are there any plans to add these > > kind > > > > of > > > > > > > features to Julia? > > > > > > >
