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Learning Julia

You're reading from   Learning Julia Build high-performance applications for scientific computing

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Product type Paperback
Published in Nov 2017
Publisher Packt
ISBN-13 9781785883279
Length 316 pages
Edition 1st Edition
Languages
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Authors (2):
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Rahul Lakhanpal Rahul Lakhanpal
Author Profile Icon Rahul Lakhanpal
Rahul Lakhanpal
Anshul Joshi Anshul Joshi
Author Profile Icon Anshul Joshi
Anshul Joshi
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Table of Contents (11) Chapters Close

Preface 1. Understanding Julia's Ecosystem FREE CHAPTER 2. Programming Concepts with Julia 3. Functions in Julia 4. Understanding Types and Dispatch 5. Working with Control Flow 6. Interoperability and Metaprogramming 7. Numerical and Scientific Computation with Julia 8. Data Visualization and Graphics 9. Connecting with Databases 10. Julia’s Internals

Expressions and macros

Metaprogramming is fun, and Julia definitely has one of the best metaprogramming features compared with some of its rivals. The initial cues and inspiration have been taken from Lisp, and similarly to Lisp, Julia is written in Julia itself—or in other words, Julia is homoiconic.

To explain how Julia interprets a code, here is a small code snippet:

julia> code = "println(\"hello world \")"
"println(\"hello world \")"

julia> expression = parse(code)
:(println("hello world "))

julia> typeof(expression)
Expr

Here, we have simply passed a normal Julia code println("hello world") as a string to the function parse. This function, in turn, takes this piece of string and converts it into a data type called Expr, which is evident from the preceding code.

To see what&apos...

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