Book Image

Learning Julia

By : Anshul Joshi, Rahul Lakhanpal
Book Image

Learning Julia

By: Anshul Joshi, Rahul Lakhanpal

Overview of this book

Julia is a highly appropriate language for scientific computing, but it comes with all the required capabilities of a general-purpose language. It allows us to achieve C/Fortran-like performance while maintaining the concise syntax of a scripting language such as Python. It is perfect for building high-performance and concurrent applications. From the basics of its syntax to learning built-in object types, this book covers it all. This book shows you how to write effective functions, reduce code redundancies, and improve code reuse. It will be helpful for new programmers who are starting out with Julia to explore its wide and ever-growing package ecosystem and also for experienced developers/statisticians/data scientists who want to add Julia to their skill-set. The book presents the fundamentals of programming in Julia and in-depth informative examples, using a step-by-step approach. You will be taken through concepts and examples such as doing simple mathematical operations, creating loops, metaprogramming, functions, collections, multiple dispatch, and so on. By the end of the book, you will be able to apply your skills in Julia to create and explore applications of any domain.
Table of Contents (17 chapters)
Title Page
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
8
Data Visualization and Graphics

Chapter 2. Programming Concepts with Julia

In the previous chapter, we discussed how Julia is great for prototyping and performs almost as well as C. Julia caters to seasoned programmers and novices equally. Julia is designed in a way that someone who has just started with programming will be able to be up and running in a day with the help of REPL or Jupyter Notebook. It provides lots of features that are useful to data scientists, statisticians, and those working in the field of scientific computing.

Knowledge of other languages would make the reading enjoyable, but is not required. The reader will find that Julia is quite similar to MATLAB, Python, and R.

Julia’s version 1.0 is planned for release in a few months. Although there could be some changes by then, most of the concepts and code should be valid for that version.

In this chapter, the reader will go through the syntax, as well as one of the many ways to program in Julia. The following topics will be covered in this chapter:

  • Revisiting...