Julia Programming Language

A Julia Programming Language is a high-level, high-performance dynamic programming language for technical computing developed at MIT.

• Context:
  • It can be used as a Data Analysis Language.
• Counter-Example(s):
  • Python Language.
  • MATLAB Language.
  • R Language.
• See: Fortran, C++.

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References

2012

• http://julialang.org/
  • QUOTE: Julia is a high-level, high-performance dynamic programming language for technical computing, with syntax that is familiar to users of other technical computing environments. It provides a sophisticated compiler, distributed parallel execution, numerical accuracy, and an extensive mathematical function library. The library, mostly written in Julia itself, also integrates mature, best-of-breed C and Fortran libraries for linear algebra, random number generation, FFTs, and string processing
• http://en.wikipedia.org/wiki/Julia_%28programming_language%29
  • QUOTE: Julia is a high-level, high-performance dynamic programming language for technical computing, with syntax intended to be familiar to users of other technical computing environments. It provides a sophisticated compiler, distributed parallel execution, numerical accuracy, and an extensive mathematical function library. The library, mostly written in Julia itself, also integrates C and Fortran libraries for linear algebra, random number generation, FFTs, and string processing. More libraries continue to be added over time. Julia programs are organized around defining functions, and overloading them for different combinations of argument types (which can also be user-defined).

• http://strata.oreilly.com/2012/10/matlab-r-julia-languages-for-data-analysis.html
  • Julia’s weakness, however, is its libraries. R has CRAN, certainly the most impressive collection of statistical libraries available anywhere. MATLAB also has a wide range of toolboxes available, for a price. Julia also lacks a rich development environment, like RStudio, and has only rudimentary support for plotting, which is a pretty critical part of most exploratory data analysis.

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