Julia for Computing

The Julia computing language is a relative newcomer to the compute world that is proving to be very powerful and effective for scientific computation. It aims to combine the flexibility and ease-of-use of am interpreted, dynamic language (like Matlab) with the speed and efficiency of a compiled, statically typed language (like C or C++).

There are many online resources for learning the Julia language. A good place to start is the documentation provided by the Julia developers at: http://docs.julialang.org/

A good resource for new users is here: https://en.wikibooks.org/wiki/Introducing_Julia

There are many software packages that have been developed for Julia to do many common computational tasks. The list of registered Julia packages can be found at http://pkg.julialang.org.

This chapter focuses on how to use Julia within a Jupyter notebook. Doing simple calculations in Julia is very straightforward. We show how to make a few plots, and how to build rich graphics files.

A couple of caveats: The Julia language is still under development, and so some functionality is a bit shaky. For instance, loading a new package (Pkg.add("whatever")) often will fail. Also, the "binder button" in this book will not run Julia code for you.