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Comments (22)

• prof-dr-ir
  Julia is fantastic if you do numerical work and want to write out your inner loops explicitly without sacrificing too much performance, either for pedagogical reasons or because you want to fiddle with the algorithm.It is a lot of fun to start from an empty file, add maybe an import LinearAlgebra, and develop things like a convolutional neural network or a Markov-chain Monte Carlo algorithm completely from scratch. And then it is very rewarding to have such a program be fast enough (looking at Python here) to train on the MNIST dataset or find reasonable estimates for critical exponents.I am not sure there are languages better suited than Julia for these kind of things.
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  maxall4
  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?)
• ashton314
  Julia is my go-to when I need a fast language that I can reason about in a functional way. The type system is fine, the pattern matching is pretty darn good, the metaprogramming story could be significantly better but it’s not bad and boy howdy it’s fast. So stinking fast.
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  hn_submit
  Safe for BASIC I believe it's very difficult to make a programming language which is easy-to-learn like the creators of Julia proclaim. It may be somewhat easier to implement specific scientific functionality in the language but does that warrant the creation of yet another language?Scanning the language it doesn't strike me at all as "simple."
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  Alien1Being
  Thought that it would be about Lisp....
• anon
  undefined
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  muragekibicho
  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.
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  bretnach
  Yet another example of MIT taking far too much credit for something...
• drnick1
  [dead]
• xuchenyi
  [flagged]