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Functional Python Programming

You're reading from   Functional Python Programming Create succinct and expressive implementations with functional programming in Python

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Product type Paperback
Published in Jan 2015
Publisher
ISBN-13 9781784396992
Length 360 pages
Edition 1st Edition
Languages
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Author (1):
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Steven F. Lott Steven F. Lott
Author Profile Icon Steven F. Lott
Steven F. Lott
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Table of Contents (18) Chapters Close

Preface 1. Introducing Functional Programming 2. Introducing Some Functional Features FREE CHAPTER 3. Functions, Iterators, and Generators 4. Working with Collections 5. Higher-order Functions 6. Recursions and Reductions 7. Additional Tuple Techniques 8. The Itertools Module 9. More Itertools Techniques 10. The Functools Module 11. Decorator Design Techniques 12. The Multiprocessing and Threading Modules 13. Conditional Expressions and the Operator Module 14. The PyMonad Library 15. A Functional Approach to Web Services 16. Optimizations and Improvements Index

Using Python lambda forms

In many cases, the definition of a helper function requires too much code. Often, we can digest the key function to a single expression. It can seem wasteful to have to write both def and return statements to wrap a single expression.

Python offers the lambda form as a way to simplify using higher-order functions. A lambda form allows us to define a small, anonymous function. The function's body is limited to a single expression.

The following is an example of using a simple lambda expression as the key:

long, short = max(trip, key=lambda leg: leg[2]), min(trip, key=lambda leg: leg[2])
print(long, short)

The lambda we've used will be given an item from the sequence; in this case, each leg three tuple will be given to the lambda. The lambda argument variable, leg, is assigned and the expression, leg[2], is evaluated, plucking the distance from the three tuple.

In the rare case that a lambda is never reused, this form is ideal. It's common, however, to...

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