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Modern Python Cookbook

You're reading from   Modern Python Cookbook The latest in modern Python recipes for the busy modern programmer

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Product type Paperback
Published in Nov 2016
Publisher Packt
ISBN-13 9781786469250
Length 692 pages
Edition 1st Edition
Languages
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Toc

Table of Contents (18) Chapters Close

Title Page
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
1. Numbers, Strings, and Tuples FREE CHAPTER 2. Statements and Syntax 3. Function Definitions 4. Built-in Data Structures – list, set, dict 5. User Inputs and Outputs 6. Basics of Classes and Objects 7. More Advanced Class Design 8. Input/Output, Physical Format, and Logical Layout 9. Testing 10. Web Services 11. Application Integration Index

Creating a partial function


When we look at functions such as reduce(), sorted(), min(), and max(), we see that we'll often have some permanent argument values. For example, we might find a need to write something like this in several places:

    reduce(operator.mul, ..., 1) 

Of the three parameters to reduce(), only one - the iterable to process - actually changes. The operator and the base value arguments are essentially fixed at operator.mul and 1.

Clearly, we can define a whole new function for this:

    def prod(iterable): 
        return reduce(operator.mul, iterable, 1) 

However, Python has a few ways to simplify this pattern so that we don't have to repeat the boilerplate def and return statements.

How can we define a function that has some parameters provided in advance?

Note that the goal here is different from providing default values. A partial function doesn't provide a way to override the defaults. Instead, we want to create as many partial functions as we need, each...

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