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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

Chapter 7. Additional Tuple Techniques

Many of the examples we've looked at have either been scalar functions, or relatively simple structures built from small tuples. We can often exploit Python's immutable namedtuple as a way to build complex data structures. We'll look at how we use and how we create namedtuples. We'll also look at ways that immutable namedtuples can be used instead of stateful object classes.

One of the beneficial features of object-oriented programming is the ability to create complex data structures incrementally. In some respects, an object is simply a cache for results of functions; this will often fit well with functional design patterns. In other cases, the object paradigm provides for property methods that include sophisticated calculations. This is an even better fit for functional design ideas.

In some cases, however, object class definitions are used statefully to create complex objects. We'll look at a number of alternatives...

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