Please, be patient and open :)
2015 post: https://news.ycombinator.com/item?id=8803678
2017 post: https://news.ycombinator.com/item?id=13161700
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Please, be patient and open :)
2015 post: https://news.ycombinator.com/item?id=8803678
2017 post: https://news.ycombinator.com/item?id=13161700
For scientific or other high-performance computing: Julia
For scripting, writing Pandoc filters, extending NeoVim, doing magic with TeX: Lua
For web applications: Elixir with LiveView.
It depends on what you want to do. For scientific or other high-performance computing: Julia For scripting, writing Pandoc filters, extending NeoVim, doing magic with TeX: Lua For web applications: Elixir with LiveView.
[1] https://lwn.net/Articles/731581/ (I'm assuming you're the same Lee Phillips.)
It depends on what you want to do. For scientific or other high-performance computing: Julia For scripting, writing Pandoc filters, extending NeoVim, doing magic with TeX: Lua For web applications: Elixir with LiveView.
NeoVim put Lua on my radar, but your article on LuaTeX [1] that was shared here recently raised it much higher on the priority list. The chickenize package seems a fun way to get comfortable with it as well. [1] https://lwn.net/Articles/731581/ (I'm assuming you're the same Lee Phillips.)
And, yes, plus Chickenize has some fun documentation.
It depends on what you want to do. For scientific or other high-performance computing: Julia For scripting, writing Pandoc filters, extending NeoVim, doing magic with TeX: Lua For web applications: Elixir with LiveView.
It depends on what you want to do. For scientific or other high-performance computing: Julia For scripting, writing Pandoc filters, extending NeoVim, doing magic with TeX: Lua For web applications: Elixir with LiveView.
We're in the same situation with Julia than 10 years ago when we started moving from IDL to Python. It was painful as Python wasn't born a scientific language, it awkwardly became so with numarray, numpy, numba, pandas, matplotlib, numexpr, scipy, pythran, scikit and whatever never-ending additional mess it requires.
At least Julia is domain specific. Like Matlab and IDL, it's JITed, vectorized and ready to use OOTB without the need for third-party libs.
Still, I really wish GDL was ready back then...
That said, I don't think you are ever going to regret learning how to communicate better. Software is fundamentally about serving human needs and is usually done in a team context, so improving communication is always worthwhile.