#### Overview of this book

The release of Julia 1.0 is now ready to change the technical world by combining the high productivity and ease of use of Python and R with the lightning-fast speed of C++. Julia 1.0 programming gives you a head start in tackling your numerical and data problems. You will begin by learning how to set up a running Julia platform, before exploring its various built-in types. With the help of practical examples, this book walks you through two important collection types: arrays and matrices. In addition to this, you will be taken through how type conversions and promotions work. In the course of the book, you will be introduced to the homo-iconicity and metaprogramming concepts in Julia. You will understand how Julia provides different ways to interact with an operating system, as well as other languages, and then you'll discover what macros are. Once you have grasped the basics, you’ll study what makes Julia suitable for numerical and scientific computing, and learn about the features provided by Julia. By the end of this book, you will also have learned how to run external programs. This book covers all you need to know about Julia in order to leverage its high speed and efficiency for your applications.
Title Page
Packt Upsell
Contributors
Preface
Free Chapter
Installing the Julia Platform
Variables, Types, and Operations
Functions
Control Flow
Collection Types
More on Types, Methods, and Modules
Metaprogramming in Julia
I/O, Networking, and Parallel Computing
Running External Programs
The Standard Library and Packages
Other Books You May Enjoy
Index

## Floating point numbers

Floating point numbers follow the IEEE 754 standard and represent numbers with a decimal point, such as `3.14`, or an exponent notation, such as `4e-14`, and come in the types `Float16` up to `Float64`, the last one being used for double precision.

Single precision is achieved through the use of the `Float32` type. Single precision float literals must be written in scientific notation, such as `3.14f0`, but with `f`, where one normally uses `e`. That is, `2.5f2` indicates `2.5*10^2` with single precision, while `2.5e2` indicates `2.5*10^2` in double precision. Julia also has a `BigFloat` type for arbitrary-precision floating numbers computations.

A built-in type promotion system takes care of all the numeric types that can work together seamlessly, so that there is no explicit conversion needed. Special values exist: `Inf` and `-Inf` are used for infinity, and `NaN` is used for "not a number" values such as the result of `0/0` or `Inf - Inf`.

Floating point arithmetic in all programming languages is often...