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Functional Python Programming - Third Edition

Name: Functional Python Programming - Third Edition
Author: Steven F. Lott
ISBN: 9781803232577

by Steven F. Lott

December 2022

Beginner

576 pages

11h 19m

English

Packt Publishing

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Preface
Chapter 1: Understanding Functional Programming
1.1 The functional style of programming1.2 Comparing and contrasting procedural and functional styles1.3 A classic example of functional programming1.4 Exploratory data analysis1.5 Summary1.6 ExercisesJoin our community Discord space
Chapter 2: Introducing Essential Functional Concepts
2.1 Functions as first-class objects2.2 Immutable data2.3 Strict and non-strict evaluation2.4 Lazy and eager evaluation2.5 Recursion instead of an explicit loop state2.6 Functional type systems2.7 Familiar territory2.8 Learning some advanced concepts2.9 Summary2.10 ExercisesJoin our community Discord space
Chapter 3: Functions, Iterators, and Generators
3.1 Writing pure functions3.2 Functions as first-class objects3.3 Using strings3.4 Using tuples and named tuples3.5 Using generator expressions3.6 Cleaning raw data with generator functions3.7 Applying generators to built-in collections3.8 Summary3.9 ExercisesJoin our community Discord space
Chapter 4: Working with Collections
4.1 An overview of function varieties4.2 Working with iterables4.3 Using any() and all() as reductions4.4 Using len() and sum() on collections4.5 Using zip() to structure and flatten sequences4.6 Using sorted() and reversed() to change the order4.7 Using enumerate() to include a sequence number4.8 Summary4.9 ExercisesJoin our community Discord space
Chapter 5: Higher-Order Functions
5.1 Using max() and min() to find extrema5.2 Using the map() function to apply a function to a collection5.3 Using the filter() function to pass or reject data5.4 The iter() function with a sentinel value5.5 Using sorted() to put data in order5.6 Overview of writing higher-order functions5.7 Writing higher-order mappings and filters5.8 Building higher-order functions with callables5.9 Review of some design patterns5.10 Summary5.11 ExercisesJoin our community Discord space
Chapter 6: Recursions and Reductions
6.1 Simple numerical recursions6.2 Reductions and folding a collection from many items to one6.3 Group-by reduction from many items to fewer6.4 Summary6.5 ExercisesJoin our community Discord space
Chapter 7: Complex Stateless Objects
7.1 Using tuples to collect data7.2 Using NamedTuple to collect data7.3 Using frozen dataclasses to collect data7.4 Complicated object initialization and property computations7.5 Using pyrsistent to collect data7.6 Avoiding stateful classes by using families of tuples7.7 Polymorphism and type pattern matching7.8 Summary7.9 ExercisesJoin our community Discord space
Chapter 8: The Itertools Module
8.1 Working with the infinite iterators8.2 Using the finite iterators8.3 Cloning iterators with tee()8.4 The itertools recipes8.5 Summary8.6 ExercisesJoin our community Discord space
Chapter 9: Itertools for Combinatorics – Permutations and Combinations
9.1 Enumerating the Cartesian product9.2 Reducing a product9.3 Performance improvements9.4 Permuting a collection of values9.5 Generating all combinations9.6 Recipes9.7 Summary9.8 ExercisesJoin our community Discord space

Chapter 10: The Functools Module
10.1 Function tools10.2 Memoizing previous results with cache10.3 Defining classes with total ordering10.4 Applying partial arguments with partial()10.5 Reducing sets of data with the reduce() function10.6 Handling multiple types with singledispatch10.7 Summary10.8 ExercisesJoin our community Discord space
Chapter 11: The Toolz Package
11.1 The itertools star map function11.2 Reducing with operator module functions11.3 Using the toolz package11.4 Summary11.5 Exercises
Chapter 12: Decorator Design Techniques
12.1 Decorators as higher-order functions12.2 Cross-cutting concerns12.3 Composite design12.4 Adding a parameter to a decorator12.5 Implementing more complex decorators12.6 Complicated design considerations12.7 Summary12.8 Exercises
Chapter 13: The PyMonad Library
13.1 Downloading and installing13.2 Functional composition and currying13.3 Functors – making everything a function13.4 Monad bind() function13.5 Implementing simulation with monads13.6 Additional PyMonad features13.7 Summary13.8 ExercisesJoin our community Discord space
Chapter 14: The Multiprocessing, Threading, and Concurrent.Futures Modules
14.1 Functional programming and concurrency14.2 What concurrency really means14.3 Using multiprocessing pools and tasks14.4 Using a multiprocessing pool for concurrent processing14.5 Summary14.6 Exercises
Chapter 15: A Functional Approach to Web Services
15.1 The HTTP request-response model15.2 The WSGI standard15.3 Defining web services as functions15.4 Tracking usage15.5 Summary15.6 ExercisesJoin our community Discord space
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Index

Content preview from Functional Python Programming - Third Edition

3 Functions, Iterators, and Generators

The core of functional programming is the use of pure functions to map values from the input domain to the output range. Avoiding side effects reduces any dependence on variable assignment to maintain the state of a computation. We can’t purge the assignment statement from the Python language, but we can reduce our dependence on stateful objects. This means choosing among the available Python built-in functions and data structures to select those that don’t require stateful operations.

This chapter will present several Python features from a functional viewpoint, as follows:

Pure functions, free of side effects
Functions as objects that can be passed as arguments or returned as results
The use of Python’s ...

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Functional Python Programming - Third Edition

by Steven F. Lott

3 Functions, Iterators, and Generators

Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.