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
Dedication
About Packt
Contributors
Preface
Index

Learning about functions


Before we get to write our first full-fledged Julia program, the web crawler, we need to take yet another important detour. It's the last one, I promise.

As our code becomes more and more complex, we should start using functions. The REPL is great for exploratory programming due to its quick input-output feedback loop, but for any non-trivial piece of software, using functions is the way to go. Functions are an integral part of Julia, promoting readability, code reuse, and performance.

In Julia, a function is an object that takes a tuple of values as an argument and returns a value:

julia> function add(x, y) 
           x + y 
       end 
add (generic function with 1 method)

There's also a compact assignment form for function declaration:

julia> add(x, y) = x + y 
add (generic function with 1 method)

This second form is great for simple one-line functions.

Invoking a function is simply a matter of calling its name and passing it the required arguments:

julia> add...