Pro tip: [Julia](https://julialang.org/) is an amazing language, use it.

Reasoning: I got a 25x performance increase for multiple functions by converting from R code to Julia, even with the same or very similar syntax.

They have great implementation of higher order functions like map,reduce, zip, etc. with loads of LLVM optimizations to make declarative syntax as performant as imperative. Multiple dispatch lets you write overloaded code easier, and the type system is really nice imo.

Package management is great like R, it's a pleasure to install new stuff and it doesn't screw up your system or write in the wrong places (*COUGH* PIP *COUGH*).

They also have a CAS system, which integrates beautifully with a simulation framework, which is known in the industry as HECKIN' SICK.

(See this [article] (https://notamonadtutorial.com/modeling-complexity-with-symbolics-jl-and-modelingtoolkit-jl-df923129996b) )

Their [YT channel](https://www.youtube.com/user/JuliaLanguage) is full of awesome innovation by people in loads of different fields from Quant Finance to ML/AI and more.

Finally, it integrates well with python and R, so if there's some library you REALLY want, without needing to re-write the code into Julia, you can still use it (though your performance may not be as good).

Let me know what y'all think. I'm trying to get people onboard; it seriously deserves way more love than it's currently getting, even though MIT is developing it, and doing an amazing job with it.