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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 FREE CHAPTER 2. Introducing Some Functional Features 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 an immutable namedtuple as a record

In Chapter 3, Functions, Iterators, and Generators, we showed two common techniques to work with tuples. We've also hinted at a third way to handle complex structures. We can do any of the following, depending on the circumstances:

  • Use lambdas (or functions) to select a named item using the index
  • Use lambdas (or functions) with *parameter to select an item by parameter name, which maps to an index
  • Use namedtuples to select an item by attribute name or index

Our trip data, introduced in Chapter 4, Working with Collections, has a rather complex structure. The data started as an ordinary time series of position reports. To compute the distances covered, we transposed the data into a sequence of legs with a start position, end position, and distance as a nested three-tuple.

Each item in the sequence of legs looks as follows as a three-tuple:

first_leg= ((37.54901619777347, -76.33029518659048), (37.840832, -76.273834), 17.7246)

This is a short trip between...

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