Appreciate this post. I remember when I first started using Julia, I wanted to type every argument to every function because I thought static typing made me hip. Ran into a lot of problems with my types not being wide enough, etc. and had no performance impact.<p>Also, good to know about the NamedTuple. I've been away from Julia for about a year and am starting to get back into some development with it.<p>On another note, I just found out today that my department's HPC is still running Julia 0.4 and since we are in between IT people are not going to update it. Considering rewriting my project in Fortran or C++, waiting for the day when Julia is a first-class language
Thanks for posting —- I hit an issue recently this would have prevented: goal was to connect neural nets to probability distributions, the nn library took Float32 and the distribution library took Float64. Double-precision uncertainty seems counter to the purpose of uncertainty!<p>Better to not constrain the type of the inputs, unless it is a big problem