Travis Oliphant wants to add multiple dispatch to numpy, and references Julia

[Benjamin Silbaugh]

It seems that Julia's multiple dispatch has caught the attention of Travis Oliphant, and he is interested in adding them to numpy: http://technicaldiscovery.blogspot.com/2013/07/thoughts-after-scipy-2013-and-specific.html

It's nice to see that Julia is not just catching the attention of some of the major players in scientific computing, but has gone so far as to get them to rethink their own projects.

(I apologize if this is a repost, or already old news. It didn't come up when I searched the group.)

[Stefan Karpinski]

Interesting. There was this thread: https://groups.google.com/forum/#!topic/julia-dev/etrmmOVnYU0. The link to Mark Florisson's blog post is dead now – in fact the whole GitHub page is gone. It's nice to see generic functions getting the attention they deserve – although we're by no means the first people to recognize the applicability of multiple dispatch to numerical programming. Mathematica has an unusual by very powerful generic function system and Fortress uses multiple dispatch for the same reasons as Julia. It would certainly be a powerful addition to NumPy. The hard parts are: a) having a sufficiently good type system – ideally in the programming language – and b) making it fast enough.