Modern Python Cookbook - Second Edition

Spis treści książki

• Preface
  • What you need for this book
  • Who this book is for
  • What this book covers
  • To get the most out of this book
  • Get in touch
• Numbers, Strings, and Tuples
  • Working with large and small integers
  • Choosing between float, decimal, and fraction
  • Choosing between true division and floor division
  • 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 arent 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
• 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
• 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
• 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
• 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
• 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
• 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
• 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
• 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
  • Simplifying complex algorithms with immutable data structures
  • Writing recursive generator functions with the yield from statement
• Input/Output, Physical Format, and Logical Layout
  • Using pathlib to work with filenames
  • Replacing a file while preserving the previous version
  • Reading delimited files with the CSV module
  • Using dataclasses to simplify working with CSV files
  • Reading complex formats using regular expressions
  • Reading JSON and YAML documents
  • Reading XML documents
  • Reading HTML documents
  • Refactoring a .csv DictReader as a dataclass reader
• Testing
  • Test tool setup
  • Using docstrings for testing
  • Testing functions that raise exceptions
  • Handling common doctest issues
  • Unit testing with the unittest module
  • Combining unittest and doctest tests
  • Unit testing with the pytest module
  • Combining pytest and doctest tests
  • Testing things that involve dates or times
  • Testing things that involve randomness
  • Mocking external resources
• Web Services
  • Defining the card model
  • Using the Flask framework for RESTful APIs
  • Parsing the query string in a request
  • Making REST requests with urllib
  • Parsing the URL path
  • Parsing a JSON request
  • Implementing authentication for web services
• Application Integration: Configuration
  • Finding configuration files
  • Using YAML for configuration files
  • Using Python for configuration files
  • Using class-as-namespace for configuration
  • Designing scripts for composition
  • Using logging for control and audit output
• Application Integration: Combination
  • Combining two applications into one
  • Combining many applications using the Command Design Pattern
  • Managing arguments and configuration in composite applications
  • Wrapping and combining CLI applications
  • Wrapping a program and checking the output
  • Controlling complex sequences of steps
• Statistical Programming and Linear Regression
  • Using the built-in statistics library
  • Average of values in a counter
  • Computing the coefficient of a correlation
  • Computing regression parameters
  • Computing an autocorrelation
  • Confirming that the data is random the null hypothesis
  • Locating outliers
  • Analyzing many variables in one pass
• Index
• Other Books You May Enjoy
• Index

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