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Julia Quick Syntax Reference

A Pocket Guide for Data Science Programming

  • Antonello Lobianco
Book

Table of contents

  1. Front Matter
    Pages i-xvii
  2. Language Core

    1. Front Matter
      Pages 1-1
    2. Antonello Lobianco
      Pages 3-16
    3. Antonello Lobianco
      Pages 17-40
    4. Antonello Lobianco
      Pages 41-55
    5. Antonello Lobianco
      Pages 57-66
    6. Antonello Lobianco
      Pages 67-80
    7. Antonello Lobianco
      Pages 81-90
    8. Antonello Lobianco
      Pages 91-111
    9. Antonello Lobianco
      Pages 113-133
  3. Packages Ecosystem

    1. Front Matter
      Pages 135-135
    2. Antonello Lobianco
      Pages 137-175
    3. Antonello Lobianco
      Pages 177-197
    4. Antonello Lobianco
      Pages 199-209
  4. Back Matter
    Pages 211-216

About this book

Introduction

This quick Julia programming language guide is a condensed code and syntax reference to the Julia 1.x programming language, updated with the latest features of the Julia APIs, libraries, and packages. It presents the essential Julia syntax in a well-organized format that can be used as a handy reference. 

This book provides an introduction that reveals basic Julia structures and syntax; discusses data types, control flow, functions, input/output, exceptions, metaprogramming, performance, and more.  Additionally, you'll learn to interface Julia with other programming languages such as R for statistics or Python. You will learn how to use Julia packages for data analysis, numerical optimization and symbolic computation, and how to disseminate your results in dynamic documents or interactive web pages.  

In this book, the focus is on providing important information as quickly as possible. It is packed with useful information and is a must-have for any Julia programmer.

You will:
  • Set up the software needed to run Julia and your first Hello World example
  • Work with types and the different containers that Julia makes available for rapid application development
  • Use vectorized, classical loop-based code such as logical operators and blocks
  • Explore functions by looking at arguments, return values, polymorphism, parameters, anonymous functions, and broadcasts
  • Build custom structures in Julia
  • Interface Julia with other languages such as C/C++, Python, and R
  • Program a richer API, modifying the code before it is executed using expressions, symbols, macros, quote blocks, and more
  • Maximize your code’s performance 

Keywords

Julia math data science statistics computer science CS programming language software source code development analysis

Authors and affiliations

  • Antonello Lobianco
    • 1
  1. 1.NancyFrance

Bibliographic information