What is Julia? A fresh approach to numerical computing

A “no compromises” programming language for data scientists, Julia combines the ease of a dynamic language with the speed of a compiled language

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Julia for researchers

Researchers will find many packages of interest, as you can see from the category names in the right-hand column above. In addition, many of the base features of the Julia language are oriented towards science, engineering, and analysis. For example, as you can see in the screenshot below, matrices and linear algebra are built into the language at a sophisticated level.

julia juliabox linear algebra IDG

Julia offers sophisticated support for multi-dimensional arrays and linear algebra operations. 

Learn Julia

As you’ve seen, you can use Julia and many packages for free, and buy enterprise support and advanced features if you need them. There are a few gotchas to consider as you’re starting to evaluate Julia.

First, you need to know that ordinary global variables make Julia slow. That’s because variables at global scope don’t have a fixed type unless you’ve declared one, which in turn means that functions and expressions using the global variable have to handle any type. It’s much more efficient to declare variables inside the scope of functions, so that their type can be determined and the simplest possible code to use them can be generated.

Second, you need to know that variables declared at top level in the Julia command line are global. If you can’t avoid doing that, you can make performance a little better (or less awful) by declaring them const. That doesn’t mean that the value of the variable can’t change—it can. It means that the type of the variable can’t change.

Finally, read the Julia manual and the official list of Julia learning resources. In particular, read the getting started section of the manual and watch Jane Herriman’s introductory tutorial and any other videos in the learning resources that strike you as relevant. If you would prefer to follow along on your own machine rather than on JuliaBox, you may want to clone the JuliaBoxTutorials repo from GitHub and run the Local_installations notebook from Jupyter to install all the packages needed.

Copyright © 2018 IDG Communications, Inc.

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