Getting started with Julia Programming Language

Enter the exciting world of Julia, a high-performance language for technical computing About This Book Work with Julia in a multi-core, distributed, and networked environment Learn the techniques to create blazingly fast programs with Julia The book walks you through various practical examples to get to grips with Julia Who This Book Is For This book is for you if you are a data scientist or working on any technical or scientific computation projects. The book assumes you have a basic working knowledge of high-level dynamic languages such as MATLAB, R, Python, or Ruby. In Detail Julia is a new open source programming language that is used in the field of data science computing. It was created to solve the dilemma between high-level slow code and fast but low-level code, and the necessity to use both to achieve high performance. This book will give you a head start to tackle your numerical and data problems with Julia. Your journey will begin by learning how to set up a running Julia platform before exploring its various built-in types. You will then move on to cover the different functions and constructs in Julia. The book will then walk you through the two important collection types―arrays and matrices. Over the course of the book, you will also be introduced to homoiconicity, the meta-programming concept in Julia. Towards the concluding part of the book, you will also learn how to run external programs. This book will cover all you need to know about Julia to leverage its high speed and efficiency. Getting Started with Julia Programming 11 Credits 13 About the Author 15 About the Reviewers 17 www.PacktPub.com 19 Support files, eBooks, discount offers, and more 21 Why subscribe? 22 Free access for Packt account holders 23 Preface 24 What this book covers 26 What you need for this book 27 Who this book is for 29 Conventions 31 Reader feedback 33 Customer support 35 Downloading the example code 37 Errata 38 Piracy 39 Questions 40 The Rationale for Julia 41 The scope of Julia 43 Julia's place among the other programming languages 45 A comparison with other languages for the data scientist 48 MATLAB 50 R 51 Python 52 Useful links 53 Summary 55 1. Installing the Julia Platform 57 Installing Julia 59 Windows version – usable from Windows XP SP2 onwards 60 Ubuntu version 62 OS X 63 Building from source 64 Working with Julia's shell 65 Startup options and Julia scripts 69 Packages 71 Adding a new package 74 Installing and working with Julia Studio 75 Installing and working with IJulia 77 Installing Sublime-IJulia 81 Installing Juno 83 Other editors and IDEs 85 How Julia works 87 Summary 90 2. Variables, Types, and Operations 92 Variables, naming conventions, and comments 94 Types 96 Integers 99 Floating point numbers 101 Elementary mathematical functions and operations 103 Rational and complex numbers 105 Characters 107 Strings 109 Formatting numbers and strings 112 Regular expressions 114 Ranges and arrays 117 Other ways to create arrays 120 Some common functions for arrays 121 How to convert an array of chars to a string 123 Dates and times 124 Scope and constants 126 Summary 130 3. Functions 132 Defining functions 134 Optional and keyword arguments 137 Anonymous functions 139 First-class functions and closures 141 Recursive functions 144 Map, filter, and list comprehensions 146 Generic functions and multiple dispatch 149 Summary 153 4. Control Flow 155 Conditional evaluation 157 Repeated evaluation 159 The for loop 161 The while loop 162 The break statement 163 The continue statement 164 Exception handling 165 Scope revisited 169 Tasks 173 Summary 176 5. Collection Types 178 Matrices 180 Tuples 185 Dictionaries 188 Keys and values – looping 191 Sets 194 Making a set of tuples 196 Example project – word frequency 197 Summary 200 6. More on Types, Methods, and Modules 202 Type annotations and conversions 204 Type conversions and promotions 205 The type hierarchy – subtypes and supertypes 207 Concrete and abstract types 210 User-defined and composite types 212 When are two values or objects equal or identical? 215 Multiple dispatch example 216 Types and collections – inner constructors 218 Type unions 221 Parametric types and methods 223 Standard modules and paths 226 Summary 230 7. Metaprogramming in Julia 232 Expressions and symbols 234 Eval and interpolation 237 Defining macros 239 Built-in macros 243 Testing 245 Debugging 246 Benchmarking 247 Starting a task 248 Reflection capabilities 249 Summary 252 8. I/O, Networking, and Parallel Computing 254 Basic input and output 256 Working with files 257 Reading and writing CSV files 260 Using DataFrames 263 Other file formats 269 Working with TCP sockets and servers 270 Interacting with databases 274 Parallel operations and computing 277 Creating processes 279 Using low-level communications 281 Parallel loops and maps 284 Distributed arrays 287 Summary 289 9. Running External Programs 291 Running shell commands 293 Interpolation 294 Pipelining 295 Calling C and FORTRAN 296 Calling Python 299 Performance tips 301 Tools to use 304 Summary 305 10. The Standard Library and Packages 307 Digging deeper into the standard library 309 Julia's package manager 311 Installing and updating packages 313 Publishing a package 314 Graphics in Julia 316 Using Gadfly on data 318 Summary 322 A. List of Macros and Packages 324 Macros 326 List of packages 328 Index 331 Enter the exciting world of Julia, a high-performance language for technical computing In Detail Julia is a new open source programming language that is used in the field of data science computing. It was created to solve the dilemma between high-level slow code and fast but low-level code, and the necessity to use both to achieve high performance. This book will give you a head start to tackle your numerical and data problems with Julia. Your journey will begin by learning how to set up a running Julia platform before exploring its various built-in types. You will then move on to cover the different functions and constructs in Julia. The book will then walk you through the two important collection types–arrays and matrices. Over the course of the book, you will also be introduced to homoiconicity, the meta-programming concept in Julia. Towards the concluding part of the book, you will also learn how to run external programs. This book will cover all you need to know about Julia to leverage its high speed and efficiency. What You Will Learn Set up your Julia environment to achieve the highest productivity Solve your tasks in a high-level dynamic language and use types for your data only when needed Create your own types to extend the built-in type system Visualize your data in IJulia with plotting packages Explore the use of built-in macros for testing, debugging, benchmarking, and more Apply Julia to tackle problems concurrently and in a distributed environment Integrate with other languages such as C, Python, and MATLAB Downloading the example code for this book. You can download the example code files for all Packt books you have purchased from your account at http://www.PacktPub.com. If you purchased this book elsewhere, you can visit http://www.PacktPub.com/support and register to have the files e-mailed directly to you Key FeaturesBook DescriptionWhat you will learnSet up your Julia environment to achieve the highest productivitySolve your tasks in a highlevel dynamic language and use types for your data only when neededCreate your own types to extend the builtin type systemVisualize your data in IJulia with plotting packagesExplore the use of builtin macros for testing, debugging, benchmarking, and moreApply Julia to tackle problems concurrently and in a distributed environmentIntegrate with other languages such as C, Python, and MATLABWho this book is forThis book is for you if you are a data scientist or working on any technical or scientific computation projects. The book assumes you have a basic working knowledge of high-level dynamic languages such as MATLAB, R, Python, or Ruby.