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

Implementing the gameplay

Our Wikipedia parser is pretty robust now, and the addition of Cascadia greatly simplifies the code. It's time to think about the actual gameplay.

The most important thing, the core of the game, is to create the riddle—asking the player to find a path from the initial article to the end article. We previously decided that in order to be sure that a path between two articles really exists, we will pre-crawl all the pages, from the first to the last. In order to navigate from one page to the next, we'll simply randomly pick one of the internal URLs.

We also mentioned including difficulty settings. We will use the common-sense assumption that the more links there are between the start article and the end article, the less related their subjects will be; and thus, the more difficult to identify the path between them, resulting in a more challenging level.

All right, time to get coding! For starters, create a new file inside the sixdegrees/ folder. Name it Gameplay.jl and...