Modern Python Cookbook

封面

版权信息

Why subscribe?

About the author

About the reviewers

Preface

1 Numbers Strings and Tuples

Working with large and small integers

Choosing between float decimal and fraction

Choosing between true pision and floor pision

Rewriting an immutable string

String parsing with regular expressions

Building complex strings with f-strings

Building complicated strings from lists of characters

Using the Unicode characters that aren't on our keyboards

Encoding strings – creating ASCII and UTF-8 bytes

Decoding bytes – how to get proper characters from some bytes

Using tuples of items

Using NamedTuples to simplify item access in tuples

2 Statements and Syntax

Writing Python script and module files – syntax basics

Writing long lines of code

Including descriptions and documentation

Writing better RST markup in docstrings

Designing complex if...elif chains

Saving intermediate results with the := "walrus"

Avoiding a potential problem with break statements

Leveraging exception matching rules

Avoiding a potential problem with an except: clause

Concealing an exception root cause

Managing a context using the with statement

3 Function Definitions

Function parameters and type hints

Designing functions with optional parameters

Designing type hints for optional parameters

Using super flexible keyword parameters

Forcing keyword-only arguments with the * separator

Defining position-only parameters with the / separator

Writing hints for more complex types

Picking an order for parameters based on partial functions

Writing clear documentation strings with RST markup

Designing recursive functions around Python's stack limits

Writing testable scripts with the script-library switch

4 Built-In Data Structures Part 1: Lists and Sets

Choosing a data structure

Building lists – literals appending and comprehensions

Slicing and dicing a list

Deleting from a list – deleting removing popping and filtering

Writing list-related type hints

Reversing a copy of a list

Building sets – literals adding comprehensions and operators

Removing items from a set – remove() pop() and difference

Writing set-related type hints

5 Built-In Data Structures Part 2: Dictionaries

Creating dictionaries – inserting and updating

Removing from dictionaries – the pop() method and the del statement

Controlling the order of dictionary keys

Writing dictionary-related type hints

Understanding variables references and assignment

Making shallow and deep copies of objects

Avoiding mutable default values for function parameters

6 User Inputs and Outputs

Using the features of the print() function

Using input() and getpass() for user input

Debugging with f"{value=}" strings

Using argparse to get command-line input

Using cmd to create command-line applications

Using the OS environment settings

7 Basics of Classes and Objects

Using a class to encapsulate data and processing

Essential type hints for class definitions

Designing classes with lots of processing

Using typing.NamedTuple for immutable objects

Using dataclasses for mutable objects

Using frozen dataclasses for immutable objects

Optimizing small objects with __slots__

Using more sophisticated collections

Extending a built-in collection – a list that does statistics

Using properties for lazy attributes

Creating contexts and context managers

Managing multiple contexts with multiple resources

8 More Advanced Class Design

Choosing between inheritance and composition – the "is-a" question

Separating concerns via multiple inheritance

Leveraging Python's duck typing

Managing global and singleton objects

Using more complex structures – maps of lists

Creating a class that has orderable objects

Improving performance with an ordered collection

Deleting from a list of complicated objects

9 Functional Programming Features

Introduction

Writing generator functions with the yield statement

Applying transformations to a collection

Using stacked generator expressions

Picking a subset – three ways to filter

Summarizing a collection – how to reduce

Combining the map and reduce transformations

Implementing "there exists" processing

Creating a partial function