Ask HN: Ask HN: Should I learn Julia? (good investment now?)
Julia has ~everything that made Python popular for general programming and data science, plus much more, without the flaws.
Some of these benefits include super low cost abstraction, beautiful syntax, multiple dispatch, coroutines, hygienic macros, almost c like speeds, dynamic type inference, high productivity etc
Coming in the next release is multithreading, package precompilation, Interactive C++ FFI, array and matrix views, Generational GC and more. After that there are plans for standalone binary/shared library creation and handling of distributed, streaming, and out of core data sets.
Facilities to call Python and R alleviate the package scarcity to an extent. There are the bugs though, but they should be ironed out.
Why wouldn't Julia become wildly popular with all this stuff , and thus would it be a good idea to get ahead of the curve? Or, is path dependence on go, python, r, node too strong?
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