See also Matlab, R and typical SciPy distros, all of which are huge. There's an open issue to shrink Base and move a lot of functionality into modules which are separate but available by default: https://github.com/JuliaLang/julia/issues/5155. There's nothing technical standing in the way of this issue, just a bunch of tedious work.
On Thu, Apr 30, 2015 at 5:42 PM, Stefan Karpinski <[email protected]> wrote: > This is not why Base is so large – it's large because people expect > technical computing environments to be "batteries included" and to just > work without having to install additional stuff. > > On Thu, Apr 30, 2015 at 5:26 PM, Scott Jones <[email protected]> > wrote: > >> Maybe because it seems that a lot of the major packages have been put >> into Base, so it isn't a problem, as MA Laforge pointed out, leading to >> Base being incredibly large, >> with stuff that means Julia's MIT license doesn't mean all that much, >> because it includes GPL code by default... >> >> Scott >> >> On Thursday, April 30, 2015 at 5:03:52 PM UTC-4, Stefan Karpinski wrote: >>> >>> On Wed, Apr 29, 2015 at 9:08 PM, Scott Jones <[email protected]> >>> wrote: >>> >>>> Your restrictions are making it very hard to develop easy to use APIs >>>> that make sense for the people using them… >>>> >>>> That’s why so many people have been bringing this issue up… >>>> >>> >>> Not a single person who maintains a major Julia package has complained >>> about this. Which doesn't mean that there can't possibly be an issue here, >>> but it seems to strongly suggest that this is one of those concerns that >>> initially appears dire, when coming from a particular programming >>> background, but which dissipates once one acclimatizes to the multiple >>> dispatch mindset – in particular the idea that "one generic function" = >>> "one verb concept". >>> >> >
