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Getting started with Julia Programming Language, by Ivo Balbaert
Fee Download Getting started with Julia Programming Language, by Ivo Balbaert
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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
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.
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
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.
- Sales Rank: #584668 in Books
- Published on: 2015-02-27
- Released on: 2015-02-26
- Original language: English
- Number of items: 1
- Dimensions: 9.25" h x .49" w x 7.50" l, .83 pounds
- Binding: Paperback
- 159 pages
About the Author
Ivo Balbaert
Ivo Balbaert is currently a lecturer in (web) programming and databases at CVO Antwerpen (www.cvoantwerpen.be), a community college in Belgium. He received a PhD degree in applied physics from the University of Antwerp in 1986. He worked for 20 years in the software industry as a developer and consultant in several companies, and for 10 years as a project manager at the University Hospital of Antwerp. From 2000 onward, he switched to partly teaching and developing software (KHM Mechelen, CVO Antwerp). He also wrote an introductory book in Dutch about developing in Ruby and Rails, Programmeren met Ruby en Rails, Van Duuren Media. In 2012, he authored a book on the Go programming language, The Way To Go, iUniverse. In 2013, in collaboration with Dzenan Ridzanovic, he authored Learning Dart and Dart Cookbook, both by Packt Publishing.
Most helpful customer reviews
13 of 14 people found the following review helpful.
A Nice First Step
By MSE fanatic
When I learned about the Julia language I was thrilled that there is a community which wants to marry the simplicity and joy of coding in Python/R/Matlab with the power and speed of C/Fortran. This book is a rapid introduction into the basic structure, syntax, and building blocks of the Julia language. The book goes over data/collection types, functions, control flow, metaprogramming, and parallel programming in a first delievery approach. There also are comments and a few pages which provide programming tips on how to ensure top performance of your Julia code.
My main criticism of this book is you won't find detailed examples highlighting what makes Julia superior, which is its multiple dispatch and use of LLVM-JIT compiler. There are also no examples related to technical computing (e.g. numerical algorithms) which I think is necessary to convince traditional user of Python/Matlab and C/Fortran to adapt Julia as part of their toolbox. Overall this is a nice quick introduction to a very promising language and is worth reading if you prefer not to start with the Julia manual.
9 of 10 people found the following review helpful.
More than enough to get started
By Christian S.
Before reading this book I was not familiar with Julia. I knew it was a new language, but I didn’t have the opportunity to learn it before.
The book does a good job explaining the fundamentals of Julia.
If you are familiar with Ruby you will find the syntax very familiar.
The first 4 chapters explain the basic parts of the language.
I wish the authors had added the complete installation steps for IPython.
At least this line would had helped: pip install "ipython[all]"
The interesting part of the book, at least for me, starts on Chapter 5 with the collection types and basic data structures available in the language. If you already know Matlab and R, you will enjoy it comparing Julia with them.
I really liked Chapter 7, Metaprogramming in Julia. I can imagine a lot of interesting programs you can build with this. I don’t know if this is possible with Matlab at all, but in Julia it is very clean and simple.
It is very nice that there is a chapter dedicated to networking and parallelism. Usually this is not something you will find in an entry level book neither in Matlab or R. No doubt Julia is powerful language.
I feel that some of the diagrams and code examples should have been edited better (I have the ebook).
In particular the Chapter 3 (Functions) , the indentation in several examples is off. It is not a big deal, but it impacts readability. The diagram in Chapter 6 that shows the type’s tree, but has some types underlined by Word!
The screenshots from the Windows command line are explanatory, but the default font is terrible. I would not use that font in a book.
I’m giving 4 stars, the content was pretty good and the examples run as expected, but those minor edition issues put me off several times while working the examples.
8 of 9 people found the following review helpful.
First Book on Julia Programming Language
By Oleg Okun
What is Julia? Julia is a fairly new programming language (borne in 2012) that aims at reaching two objectives: 1) quick solution prototyping like in MATLAB, R or Python and 2) fast computational time and efficient memory management like in FORTRAN, C or C++. Thus, one could say that Julia tries to bridge the gap between programming languages of two types - high-level but slow and fast but low-level.
As such, Julia is a primal competitor to MATLAB, R, and Python. However, competition does not completely exclude collaboration; this is the case for Julia that has packages for calling code written in these and some other languages like Java. Needless to say, Julia is open source and free with a liberal MIT license, which is important for wide adoption. To date, there are 549 external packages that can be found at http://pkg.julialang.org/ .
Chapter 1 explains how to install Julia for Windows, Ubuntu and OS X, shows example of work in Julia shell, and lists IDEs like Juno that can be used. Chapter 2 describes Julia's types of variables (numbers, characters, strings, ranges, arrays) that are the key for its performance, while Chapter 3 discusses functions (their definition and types). Control flow operators (if, for, while, break, continue) and exception handling are introduced in Chapter 3. As the extensions of Chapter 2, Chapter 5 talks about matrices (multidimensional arrays), tuples, sets and dictionaries, while Chapter 6 goes into detail of type annotation and conversion, type hierarchy, abstract, parametric, and user-defined types. The concept of metaprogramming (which can even generate code) is explained in Chapter 7. Chapter 8 explores I/O (file reading from and writing to several formats such as CSV, JSON, XML, HDF5, DataFrames for tabular data representation), networking, interacting with databases, and parallel computing. How to call from within Julia the code written in another programming language like C, FORTRAN and Python as well as performance recommendations are explained in Chapter 9. Chapter 10 looks at the standard library of functions and packages and provides guidelines how to use a package manager and visualize data.
One may say that everything abovementioned can be found in Julia's documentation, but to have these topics in one place such as this book is certainly a must for new converts and seasonable experts alike.
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