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Intro; Table of Contents; About the Authors; About the Technical Reviewer; Acknowledgments; Introduction; Chapter 1: Principles and Philosophy; The Zen of Python; Beautiful Is Better Than Ugly; Explicit Is Better Than Implicit; Simple Is Better Than Complex; Complex Is Better Than Complicated; Flat Is Better Than Nested; Sparse Is Better Than Dense; Readability Counts; Special Cases Aren't Special Enough to Break the Rules; Practicality Beats Purity; Errors Should Never Pass Silently; Unless Explicitly Silenced; In the Face of Ambiguity, Refuse the Temptation to Guess
There Should Be One-and Preferably Only One-Obvious Way to Do ItAlthough That Way May Not Be Obvious at First, Unless You're Dutch; Now Is Better Than Never; Although Never Is Often Better Than Right Now; If the Implementation Is Hard to Explain, It's a Bad Idea; If the Implementation Is Easy to Explain, It May Be a Good Idea; Namespaces Are One Honking Great Idea: Let's Do More of Those!; Don't Repeat Yourself; Loose Coupling; The Samurai Principle; The Pareto Principle; The Robustness Principle; Backward Compatibility; Taking It With You; Chapter 2: Advanced Basics; General Concepts
IterationCaching; Transparency; Control Flow; Catching Exceptions; Exception Chains; When Everything Goes Right; Proceeding Regardless of Exceptions; Optimizing Loops; The with Statement; Conditional Expressions; Iteration; Sequence Unpacking; List Comprehensions; Generator Expressions; Set Comprehensions; Dictionary Comprehensions; Chaining Iterables Together; Zipping Iterables Together; Collections; Sets; Named Tuples; Ordered Dictionaries; Dictionaries with Defaults; Importing Code; Fallback Imports; Importing from the Future; Using __all__ to Customize Imports; Relative Imports
The __import__() FunctionThe importlib Module; Exciting Python Extensions: Random Number Beacon at NIST; How to Install the NIST Beacon Library; Simple Example to Get a Value; Example to Simulate Rolling Coin Flipping a Certain # Times and Display Heads or Tails; Taking It With You; Chapter 3: Functions; Arguments; Planning for Flexibility; Variable Positional Arguments; Variable Keyword Arguments; Combining Different Kinds of Arguments; Invoking Functions with Variable Arguments; Passing Arguments; Introspection; Example: Identifying Argument Values; Example: A More Concise Version
Example: Validating ArgumentsDecorators; Closures; Wrappers; Decorators with Arguments; Decorators with-or without-Arguments; Example: Memoization; Example: A Decorator to Create Decorators; Function Annotations; Example: Type Safety; Factoring Out the Boilerplate; Example: Type Coercion; Annotating with Decorators; Example: Type Safety as a Decorator; Generators; Lambdas; Introspection; Identifying Object Types; Modules and Packages; Docstrings; Exciting Python Extensions: Statistics; Install Pandas and Matplotlib; Make a Text File of Data; Use Pandas to Display Data
There Should Be One-and Preferably Only One-Obvious Way to Do ItAlthough That Way May Not Be Obvious at First, Unless You're Dutch; Now Is Better Than Never; Although Never Is Often Better Than Right Now; If the Implementation Is Hard to Explain, It's a Bad Idea; If the Implementation Is Easy to Explain, It May Be a Good Idea; Namespaces Are One Honking Great Idea: Let's Do More of Those!; Don't Repeat Yourself; Loose Coupling; The Samurai Principle; The Pareto Principle; The Robustness Principle; Backward Compatibility; Taking It With You; Chapter 2: Advanced Basics; General Concepts
IterationCaching; Transparency; Control Flow; Catching Exceptions; Exception Chains; When Everything Goes Right; Proceeding Regardless of Exceptions; Optimizing Loops; The with Statement; Conditional Expressions; Iteration; Sequence Unpacking; List Comprehensions; Generator Expressions; Set Comprehensions; Dictionary Comprehensions; Chaining Iterables Together; Zipping Iterables Together; Collections; Sets; Named Tuples; Ordered Dictionaries; Dictionaries with Defaults; Importing Code; Fallback Imports; Importing from the Future; Using __all__ to Customize Imports; Relative Imports
The __import__() FunctionThe importlib Module; Exciting Python Extensions: Random Number Beacon at NIST; How to Install the NIST Beacon Library; Simple Example to Get a Value; Example to Simulate Rolling Coin Flipping a Certain # Times and Display Heads or Tails; Taking It With You; Chapter 3: Functions; Arguments; Planning for Flexibility; Variable Positional Arguments; Variable Keyword Arguments; Combining Different Kinds of Arguments; Invoking Functions with Variable Arguments; Passing Arguments; Introspection; Example: Identifying Argument Values; Example: A More Concise Version
Example: Validating ArgumentsDecorators; Closures; Wrappers; Decorators with Arguments; Decorators with-or without-Arguments; Example: Memoization; Example: A Decorator to Create Decorators; Function Annotations; Example: Type Safety; Factoring Out the Boilerplate; Example: Type Coercion; Annotating with Decorators; Example: Type Safety as a Decorator; Generators; Lambdas; Introspection; Identifying Object Types; Modules and Packages; Docstrings; Exciting Python Extensions: Statistics; Install Pandas and Matplotlib; Make a Text File of Data; Use Pandas to Display Data