Functional Python Programming

Book Description

Create succinct and expressive implementations with functional programming in Python

About This Book

• Implement common functional programming design patterns and techniques in Python
• Learn how to choose between imperative and functional approaches based on expressiveness, clarity, and performance
• Apply functional Python to common Exploratory Data Analysis (EDA) programming problems

Who This Book Is For

This book is for developers who want to use Python to write programs that lean heavily on functional programming design patterns. You should be comfortable with Python programming, but no knowledge of functional programming paradigms is needed.

In Detail

Python is an easy-to-learn and extensible programming language that offers a number of functional programming features. It’s ideally suited to a number of applications in the broad space of data science.

This practical guide demonstrates the Python implementation of a number of functional programming techniques and design patterns. Starting with a general overview of functional programming concepts, you will explore common functional features such as first-class and higher-order functions, pure functions and more, and how these are accomplished in Python. Additionally, you will cover how common functional optimizations can be handled in Python. You’ll also explore data preparation techniques and data exploration in depth. Moving on, you will learn how the Python standard library fits the functional programming model. The book concludes with a look at the PyMonad project and some larger examples.

By the end of this book, you will be able to understand what functional programming is all about, its impact on the programming workflow, why it’s important, and how to implement it in Python.

Table of Contents

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

中文：

书名：函数式Python编程

使用Python中的函数式编程创建简洁且富有表现力的实现

关于本书

• 用Python语言实现常用的函数式编程设计模式和技术
• 了解如何根据表现力、清晰度和性能在命令式方法和函数式方法之间进行选择
• 函数式Python在常见探索性数据分析(EDA)编程问题中的应用

这本书是为谁写的

这本书是为那些想要使用Python编写严重依赖函数式编程设计模式的程序的开发人员编写的。您应该熟悉Python编程，但不需要了解函数式编程范例。

详细地说

Python是一种易于学习和可扩展的编程语言，它提供了许多函数式编程功能。它非常适合在数据科学的广阔空间中的许多应用。

本实用指南演示了许多函数式编程技术和设计模式的Python实现。从函数式编程概念的一般概述开始，您将探索常见的函数功能，如一类函数和高阶函数、纯函数等，以及如何在Python中实现这些功能。此外，您还将介绍如何在Python中处理常见的函数优化。您还将深入探讨数据准备技术和数据探索。接下来，您将了解到Python标准库如何适应函数式编程模型。本书最后介绍了PyMonad项目和一些更大的例子。

到本书结束时，您将能够理解函数式编程的全部内容，它对编程工作流的影响，为什么它很重要，以及如何用Python语言实现它。

目录表

第1章：介绍函数式编程
第2章：介绍一些功能特性
第3章：函数、迭代器和生成器
Chapter 4: Working with Collections
Chapter 5: Higher-Order Functions
Chapter 6: Recursions and Reductions
Chapter 7: Additional Tuple Techniques
Chapter 8: The Itertools Module
Chapter 9: More Itertools Techniques
Chapter 10: The Functools Module
Chapter 11: Decorator Design Techniques
Chapter 12: The Multiprocessing and Threading Modules
第13章：条件表达式和运算符模块
Chapter 14: The PyMonad Library
第15章：Web服务的功能方法
第16章：优化和改进