Functional Python Programming

封面

Title Page

Copyright and Credits

Functional Python Programming Second Edition

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Contributors

About the author

About the reviewer

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Preface

Who this book is for

What this book covers

To get the most out of this book

Download the example code files

Conventions used

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Reviews

Understanding Functional Programming

Identifying a paradigm

Subdividing the procedural paradigm

Using the functional paradigm

Using a functional hybrid

Looking at object creation

The stack of turtles

A classic example of functional programming

Exploratory data analysis

Summary

Introducing Essential Functional Concepts

First-class functions

Pure functions

Higher-order functions

Immutable data

Strict and non-strict evaluation

Recursion instead of an explicit loop state

Functional type systems

Familiar territory

Learning some advanced concepts

Summary

Functions Iterators and Generators

Writing pure functions

Functions as first-class objects

Using strings

Using tuples and named tuples

Using generator expressions

Exploring the limitations of generators

Combining generator expressions

Cleaning raw data with generator functions

Using lists dicts and sets

Using stateful mappings

Using the bisect module to create a mapping

Using stateful sets

Summary

Working with Collections

An overview of function varieties

Working with iterables

Parsing an XML file

Parsing a file at a higher level

Pairing up items from a sequence

Using the iter() function explicitly

Extending a simple loop

Applying generator expressions to scalar functions

Using any() and all() as reductions

Using len() and sum()

Using sums and counts for statistics

Using zip() to structure and flatten sequences

Unzipping a zipped sequence

Flattening sequences

Structuring flat sequences

Structuring flat sequences – an alternative approach

Using reversed() to change the order

Using enumerate() to include a sequence number

Summary

Higher-Order Functions

Using max() and min() to find extrema

Using Python lambda forms

Lambdas and the lambda calculus

Using the map() function to apply a function to a collection

Working with lambda forms and map()

Using map() with multiple sequences

Using the filter() function to pass or reject data

Using filter() to identify outliers

The iter() function with a sentinel value

Using sorted() to put data in order

Writing higher-order functions

Writing higher-order mappings and filters

Unwrapping data while mapping

Wrapping additional data while mapping

Flattening data while mapping

Structuring data while filtering

Writing generator functions

Building higher-order functions with callables

Assuring good functional design

Review of some design patterns

Summary

Recursions and Reductions

Simple numerical recursions

Implementing tail-call optimization

Leaving recursion in place