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

Using object serialization in Julia

Julia, similar to other programming languages, supports object serialization. This is a mechanism where a byte representation of any object can be acquired and stored directly to disk or sent across a network. Normally, the serialization mechanism is used for short-term data storage. It is not guaranteed to work across even minor environment upgrades or on other system architectures; different platforms might have different binary representations of data. However, if storage is needed only during runtime (for example, caching), then serialization is the recommended approach.  


When data serialization is required for longer periods, along with better cross-platform compatibility, then use of theJDL2.jl or BSON.jl packages is recommended. Please note that at the time of writing, both libraries are under intensive development, so you should test which package best suits your needs. However, for long-term data storage, we recommend the BSON format, because...