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

Executing loops efficiently with conditional statements

In this recipe, we want to calculate a sum of the positive entries of a large vector in an efficient way.

Getting ready

Open the Julia console. Make sure that you have the BenchmarkTools.jl package installed. If it is missing you can add it by running the following commands: using Pkg; Pkg.add("BenchmarkTools").

Before we begin, load the required packages and generate the vector over which we will perform a sum:

julia> using Random, BenchmarkTools

julia> Random.seed!(1);

julia> x = randn(10^6);

Notice that we use ; at the end of the expressions to suppress the output of the results.


In the GitHub repository for this recipe, you will find the commands.txt file that contains the presented sequence of shell and Julia commands.

Now open your favorite terminal to execute the commands.

How to do it...

In the following steps, we investigate different methods for how the sum of positive values in a vector can be calculated, and then compare...