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

Handling errors like a pro

Sometimes, coding defensively won't be the solution. Maybe a key part of your program requires reading a file on the network or accessing a database. If the resource can't be accessed due to a temporary network failure, there's really not much you can do in the absence of the data.

The try...catch statements

If you identify parts of your code where you think the execution can go off the rails due to conditions that are out of your control (that is, exceptional conditions—hence the name exception), you can use Julia's try...catch statements. This is exactly what it sounds like—you instruct the compiler to try a piece of code and if, as a result of a problem, an exception is thrown, to catch it. The fact that an exception is caught implies that it won't propagate throughout the whole application.

Let's see it in action:

julia> try 
    getattr(dom.root, "href") 
    println("The $(tag(dom.root)) tag doesn't have a 'href' attribute.") 
The HTML tag doesn...