Book Image

Julia 1.0 Programming Complete Reference Guide

By : Ivo Balbaert, Adrian Salceanu
Book Image

Julia 1.0 Programming Complete Reference Guide

By: Ivo Balbaert, Adrian Salceanu

Overview of this book

Julia offers the high productivity and ease of use of Python and R with the lightning-fast speed of C++. There’s never been a better time to learn this language, thanks to its large-scale adoption across a wide range of domains, including fintech, biotech and artificial intelligence (AI). You will begin by learning how to set up a running Julia platform, before exploring its various built-in types. This Learning Path walks you through two important collection types: arrays and matrices. You’ll be taken through how type conversions and promotions work, and in further chapters you'll study how Julia interacts with operating systems and other languages. You’ll also learn about the use of macros, what makes Julia suitable for numerical and scientific computing, and how to run external programs. Once you have grasped the basics, this Learning Path goes on to how to analyze the Iris dataset using DataFrames. While building a web scraper and a web app, you’ll explore the use of functions, methods, and multiple dispatches. In the final chapters, you'll delve into machine learning, where you'll build a book recommender system. By the end of this Learning Path, you’ll be well versed with Julia and have the skills you need to leverage its high speed and efficiency for your applications. This Learning Path includes content from the following Packt products: • Julia 1.0 Programming - Second Edition by Ivo Balbaert • Julia Programming Projects by Adrian Salceanu

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Julia 1.0 Programming Complete Reference Guide
Ivo Balbaert | Adrian Salceanu
May, 2019 | 7 hours 46 minutes
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Table of Contents (18 chapters)
Preface
Preface
Who this book is for
What this book covers
To get the most out of this book
Get in touch
Free Chapter
1
Installing the Julia Platform
Installing the Julia Platform
Installing Julia
Working with Julia's REPL
Startup options and Julia scripts
Packages
Installing and working with IJulia
Installing Juno
Installing julia-vscode
Installing Sublime-IJulia
Other editors and IDEs
How Julia works
Summary
2
Variables, Types, and Operations
Variables, Types, and Operations
Variables, naming conventions, and comments
Types
Integers
Floating point numbers
Elementary mathematical functions and operations
Rational and complex numbers
Characters
Strings
Regular expressions
Ranges and arrays
Dates and times
Scope and constants
Summary
3
Functions
Functions
Defining functions
Optional and keyword arguments
Anonymous functions
First-class functions and closures
functions
Broadcasting
Map, filter, and list comprehensions
Generic functions and multiple dispatch
Summary
4
Control Flow
Control Flow
Conditional evaluation
Repeated evaluation
Exception handling
Scope revisited
Tasks
Summary
5
Collection Types
Collection Types
Matrices
Tuples
Dictionaries
Sets
An example project – word frequency
Summary
6
More on Types, Methods, and Modules
More on Types, Methods, and Modules
Type annotations
The type hierarchy – subtypes and supertypes
Concrete and abstract types
User-defined and composite types
Types and collections – inner constructors
Type unions
Parametric types and methods
Standard modules and paths
Summary
7
Metaprogramming in Julia
Metaprogramming in Julia
Expressions and symbols
Evaluation and interpolation
Defining macros
Built-in macros
Reflection capabilities
Summary
8
I/O, Networking, and Parallel Computing
I/O, Networking, and Parallel Computing
Basic input and output
Working with files
Using DataFrames
Working with TCP sockets and servers
Interacting with databases
Parallel operations and computing
Summary
9
Running External Programs
Running External Programs
Running shell commands
Calling C and Fortran
Calling Python
Performance tips
Summary
10
The Standard Library and Packages
The Standard Library and Packages
Digging deeper into the standard library
Julia's package manager
Graphics in Julia
Using Plots on data
Summary
11
Creating Our First Julia App
Creating Our First Julia App
Technical requirements
Defining variables
Comments
Strings
Regular expressions
Raw string literals
Numbers
Tuples
Ranges
Arrays
Exploratory data analysis with Julia
Using simple statistics to better understand our data
Loading and saving our data
Summary
12
Setting Up the Wiki Game
Setting Up the Wiki Game
Technical requirements
Data harvesting through web scraping
Understanding HTML documents
Accessing the internet from Julia
Handling HTTP responses
Understanding HTTP responses
Dictionaries
Using the HTTP response
Coding defensively
Handling errors like a pro
Learning about functions
Writing a basic web crawler – take one
Carrying on with the crawler's implementation
Summary
13
Building the Wiki Game Web Crawler
Building the Wiki Game Web Crawler
Technical requirements
Six Degrees of Wikipedia, the gameplay
Organizing our code
Setting up our game's architecture
Building our Wikipedia crawler - take two
Implementing the gameplay
Finishing touches
Learning about Julia's type system
Using article types
Methods
Working with relational databases
Summary
14
Adding a Web UI for the Wiki Game
Adding a Web UI for the Wiki Game
Technical requirements
The game plan
Learning about Julia's web stack
Developing the game's web UI
Starting a new game
Displaying a Wikipedia article page
Showing the solution
Handling any other requests
Wrapping it up
Summary
15
Implementing Recommender Systems with Julia
Implementing Recommender Systems with Julia
Technical requirements
Understanding recommender systems
Classifying recommender systems
Summary
16
Machine Learning for Recommender Systems
Machine Learning for Recommender Systems
Technical requirements
Comparing the memory-based versus model-based recommenders
Machine learning-based recommendations
Testing the recommendations
Learning about hybrid recommender systems
Summary
17
Other Books You May Enjoy
Other Books You May Enjoy
Leave a review - let other readers know what you think

Installing Juno

Juno (http://junolab.org/) is a full-fledged IDE for Julia by Mike Innes, which is based on the Atom environment. The setup page at https://github.com/JunoLab/uber-juno/blob/master/setup.md provides detailed instructions for installing and configuring Juno. Here is a summary of the steps:

  1. Download and install Atom (https://atom.io/)
  2. Start it up, go to Settings, and then click Install Panel
  3. Enter uber-juno into the search box

Atom works extensively with a command palette that you can open by typing Ctrl + spacebar, entering a command, and then selecting it. Juno provides an integrated console, and you can evaluate single expressions in the code editor directly by typing Ctrl + Enter at the end of the line. A complete script is evaluated by typing Ctrl + Shift + Enter. More on basic usage can be found here: http://docs.junolab.org/latest/man/basic_usage.html.

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