Book Image

Julia 1.0 Programming Cookbook

By : Bogumił Kamiński, Przemysław Szufel
Book Image

Julia 1.0 Programming Cookbook

By: Bogumił Kamiński, Przemysław Szufel

Overview of this book

Julia, with its dynamic nature and high-performance, provides comparatively minimal time for the development of computational models with easy-to-maintain computational code. This book will be your solution-based guide as it will take you through different programming aspects with Julia. Starting with the new features of Julia 1.0, each recipe addresses a specific problem, providing a solution and explaining how it works. You will work with the powerful Julia tools and data structures along with the most popular Julia packages. You will learn to create vectors, handle variables, and work with functions. You will be introduced to various recipes for numerical computing, distributed computing, and achieving high performance. You will see how to optimize data science programs with parallel computing and memory allocation. We will look into more advanced concepts such as metaprogramming and functional programming. Finally, you will learn how to tackle issues while working with databases and data processing, and will learn about on data science problems, data modeling, data analysis, data manipulation, parallel processing, and cloud computing with Julia. By the end of the book, you will have acquired the skills to work more effectively with your data
Table of Contents (18 chapters)
Title Page
Copyright and Credits
About Packt

Multithreading in Julia

In this recipe, we use Julia's multithreading mechanism to speed up computations of statistics over a largeDataFrame.

Getting ready

For this recipe, you need to use theDataFrames.jlandBenchmarkTools.jlpackages, which can be installed with the Julia package manager. If you need to add them then in the Julia command line, press the] key and run these commands:

(v1.0) pkg> add DataFrames
(v1.0) pkg> add BenchmarkTools

This will install theDataFrames.jlandBenchmarkTools.jlpackages and all their dependencies.


In this recipe, we use Julia's threading mechanism. The number of threads is controlled via theJULIA_NUM_THREADSsystem variable, which needs to be assigned before starting thejuliaprocess. In order to set the variable, start a new command-line console and execute this command (Windows version):


In a Linux console, run this:


Now, start Julia:


You can check whether the number of threads has been properly allocated...