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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

Revisiting programming paradigms


Before solving a problem, we should always try to understand where it came from, then break the problem into the steps that we will perform to solve it. We should make sure that we consider all the scenarios and the agents that will be involved in solving the problem.

The programming paradigm refers to the breaking up of the programming activity into a structure of thoughts. It is an approach towards a problem and the orientation of sub-tasks. Although a problem can be approached using different paradigms, one paradigm may be more suited to solving it than another.

There are many programming paradigms, so we will only be discussing a few of them here:

  • Imperative
  • Logical
  • Functional
  • Object-oriented

Understanding the programming paradigm is recommended, as one programming language may be more suited to one particular paradigm. For example, C is suited to imperative programming, Haskell is suited to functional programming, and Smalltalk is for object-oriented programming...

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