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

Beginning with test-driven Julia development

Test-driven development is a software development practice based on a simple workflow that puts automated testing center stage. The basic idea is that the requirements are turned into very specific, well-defined, and targeted test cases. Each test should address only one piece of functionality. Once the test is ready, we run the whole test suite. Obviously, as we first write the test, it will initially fail. Next, we add the minimal implementation to make the test pass. That's it—all we need to do is repeat the same process until all the requirements are implemented. This approach ensures that our code base is thoroughly tested and that we focus on delivering just the requirements, avoiding feature creep.

Julia provides built-in unit testing capabilities under the Test module. It is very straightforward and easy to use, providing enough methods to cover all the basic testing scenarios: value and exception checking, approximate values, types, and...