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Learning Jupyter 5

You're reading from   Learning Jupyter 5 Explore interactive computing using Python, Java, JavaScript, R, Julia, and JupyterLab

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Product type Paperback
Published in Aug 2018
Publisher
ISBN-13 9781789137408
Length 282 pages
Edition 2nd Edition
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Author (1):
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Dan Toomey Dan Toomey
Author Profile Icon Dan Toomey
Dan Toomey
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Table of Contents (14) Chapters Close

Preface 1. Introduction to Jupyter FREE CHAPTER 2. Jupyter Python Scripting 3. Jupyter R Scripting 4. Jupyter Julia Scripting 5. Jupyter Java Coding 6. Jupyter JavaScript Coding 7. Jupyter Scala 8. Jupyter and Big Data 9. Interactive Widgets 10. Sharing and Converting Jupyter Notebooks 11. Multiuser Jupyter Notebooks 12. What's Next? 13. Other Books You May Enjoy

Scala higher-order functions


A higher-order function either takes other functions as arguments or returns a function as its result.

We can use this example script:

def squared(x: Int): Int = x * x
def cubed(x: Int): Int = x * x * x

def process(a: Int, processor: Int => Int): Int = {processor(a) }

val fiveSquared = process(5, squared)
val sevenCubed = process(7, cubed)

We define two functions: one squares the number passed, and the other cubes the number passed.

Next, we define a higher-order function that takes a number to work on and a processor to apply.

Lastly, we call each function. For example, we call process() with 5 and the squared function. The process() function passes 5 to the squared() function and returns the result:

We take advantage of Scala's engine automatically printing out variable values to see the  expected result.

These functions are not doing very much. When I ran them, it took a few seconds for the results to display. I think there is a big performance hit using higher...

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