What is more in the spirit of the Julia language and philosophy?

Question

I recently started programming in Julia for research purposes. Going through it I started loving the syntax, I positively experienced the community here in SO and now I am thinking about porting some code from other programming languages.

Working with highly computational expensive forecasting models, it would be nice to have them all in a powerful modern language as Julia.

I would like to create a project and I am wondering how I should design it. I am concerned both from a performance and a language perspective (i.e.: Would it be better to create modules – submodules – functions or something else would be preferred? Is it better off to use dictionaries or custom types?).

I have looked at different GitHub projects in my field, but I haven't really found a common standard. Therefore I am wondering: what is more in the spirit of the Julia language and philosophy?

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EDIT:

It has been pointed out that this question might be too generic. Therefore, I would like to focus it on how it would be better structuring modules (i.e. separate modules for main functions and subroutines versus modules and submodules, etc.). I believe this would be enough for me to have a feel about what might be considered in the spirit of the Julia language and philosophy. Of course, additional examples and references are more than welcome.

Answer 1

The most you'll find is that there is an "official" style-guide. The rest of the "Julian" style is ill-defined, but there are some ways to heuristically define it.

First of all, it means designing the software around multiple dispatch and the type system. A software which follows a Julian design philosophy usually won't be defining a bunch of functions like test_pumpkin and test_pineapple, instead it will use dispatches on test for types Pumpkin and Pineapple. This allows for clean/understandable code. It will break tasks up into small type-stable functions which will allow for good performance. It likely will also be written very generically, allowing the user to use items that are subtypes of AbstractArray or Number, and using the power of dispatch to allow their software to work on numbers they've never even heard of. (In this respect, custom types are recommended over dictionaries when you need performance. However, for a type you have to know all of the fields at the beginning, which means some things require dictionaries.)

A software which follows a Julian design philosophy may also implement a DSL (Domain-Specific Language) to allow a simpler interface to the user. Instead of requiring the user to conform to archaic standards derived from C/Fortran, or write large repetitive items and inputs, the package may provide macros to allow the user to more heuristically define the problem for the software to solve.

Other items which are part of the Julian design philosophy are up for much debate. Is proper Julia code devectorized? I would say no, and the loop fusing broadcast . is a powerful way to write MATLAB-style "vectorized" code and have it be perform like a devectorized loop. However, I have seen others prefer devectorized styles.

Also note that Julia is very different from something like Python where in Julia, you can essentially "build your own standard way of doing something". Since there's no performance penalty for functions/types declared in packages rather than Base, you can build your own Julia world if you want, using macros to define your own "function-like" objects, etc. I mean, you can re-create Java styles in Julia if you wanted.