I think sometimes people go overboard with types, but types allow us to take full advantage of multiple dispatch and abstraction on another level. For example, a diagonal matrix and a full/dense matrix are both the same thing, but if you can dispatch on them differently you can massively improve the effectiveness/performance of the underlying code without much effort. A recent thread here was asking about how to do this effectively in Python, and... well, everyone just kinda laughed at the idea. Types allow us flexibility that we can't have otherwise.
On Sat, Oct 8, 2016 at 10:12 AM, Tsur Herman <tsur.her...@gmail.com> wrote: > I noticed this also .. and this is why I chose to "rip" some packages for > some of its functionality. > > From what I observed the problem is the "coolness" of the language and the > highly creative level of the package writers. Just as the first post here > states the seemingly two advantages , cool language and super-creative > package writers .. can some time have a "babel tower" effect. > > I encountered this with respect to image processing geometry primitive > manipulation etc .. the problem is: too many types!! > > if something can be represented as an array with some convention for > example MxN array where M is the Descriptor size and N is the number of > Descriptors .. then it is better to use and support that > than to declare more specialized types. > > At least for fast paced research and idea validation it is better. > Probably for implementation and performance specialized types optimized for > speed will be required.. > > >
