Book Image

Julia Programming Projects

By : Adrian Salceanu
Book Image

Julia Programming Projects

By: Adrian Salceanu

Overview of this book

Julia is a new programming language that offers a unique combination of performance and productivity. Its powerful features, friendly syntax, and speed are attracting a growing number of adopters from Python, R, and Matlab, effectively raising the bar for modern general and scientific computing. After six years in the making, Julia has reached version 1.0. Now is the perfect time to learn it, due to its large-scale adoption across a wide range of domains, including fintech, biotech, education, and AI. Beginning with an introduction to the language, Julia Programming Projects goes on to illustrate how to analyze the Iris dataset using DataFrames. You will explore functions and the type system, methods, and multiple dispatch while building a web scraper and a web app. Next, you'll delve into machine learning, where you'll build a books recommender system. You will also see how to apply unsupervised machine learning to perform clustering on the San Francisco business database. After metaprogramming, the final chapters will discuss dates and time, time series analysis, visualization, and forecasting. We'll close with package development, documenting, testing and benchmarking. By the end of the book, you will have gained the practical knowledge to build real-world applications in Julia.
Table of Contents (19 chapters)
Title Page
Copyright and Credits
About Packt

Organizing our code

Up to this point, we've been mostly coding at the REPL. Recently, in the previous chapter, we've started to rely more on the IDE to whip up short Julia files.

But, as our skillset grows and we develop more and more ambitious projects, so will grow the complexity of our programs. This, in turn, will lead to more lines of code, more logic, and more files—and more difficulties in maintaining and understanding all these down the line. As the famous coding axiom goes, the code is read many more times than it is written—so we need to plan accordingly.

Each language comes with its own philosophy and toolset when it comes to code organization. In Julia, we have files, modules, and packages. We'll learn about all of these next.

Using modules to tame our code

Modules group together related functions, variables, and other definitions. But, they are not just organizational units—they are language constructs that can be understood as variable workspaces. They allow us to define variables...