How an MIT research project became the Julia programming language

I really want to like Julia. It has a nice type system, a good ecosystem, reasonable syntax, and it’s far faster than Python. But there are several issues with its DX that prevent me from using it: the most severe of which being the complete lack of a cache for the JIT (or JIT like system), inducing multi second compile times for scripts that run in <100ms. There are some external packages that try to solve this issue, but they are far from first-party quality, and, in my experience, are quite buggy.

(I last tried Julia a few years ago; perhaps this has been improved since?)

Julia uses 1-based indexing. It's competes with R and Matlab for the same set of users. Both R and Julia have their core functions written in C++. Absolutely nothing new.

From my experience, grad students use Julia when their PI thinks a new programming language will help differentiate their next NSF proposal among vast funding requests.

Thought that it would be about Lisp....

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