Fluent Python. 2nd Edition

Spis treści ebooka

• Preface
  • Who This Book Is For
  • Who This Book Is Not For
  • Five Books in One
    • How the Book Is Organized
  • Hands-On Approach
  • Soapbox: My Personal Perspective
  • Companion Website: fluentpython.com
  • Conventions Used in This Book
  • Using Code Examples
  • OReilly Online Learning
  • How to Contact Us
  • Acknowledgments
    • Acknowledgments for the First Edition
• I. Data Structures
• 1. The Python Data Model
  • Whats New in This Chapter
  • A Pythonic Card Deck
  • How Special Methods Are Used
    • Emulating Numeric Types
    • String Representation
    • Boolean Value of a Custom Type
    • Collection API
  • Overview of Special Methods
  • Why len Is Not a Method
  • Chapter Summary
  • Further Reading
• 2. An Array of Sequences
  • Whats New in This Chapter
  • Overview of Built-In Sequences
  • List Comprehensions and Generator Expressions
    • List Comprehensions and Readability
    • Listcomps Versus map and filter
    • Cartesian Products
    • Generator Expressions
  • Tuples Are Not Just Immutable Lists
    • Tuples as Records
    • Tuples as Immutable Lists
    • Comparing Tuple and List Methods
  • Unpacking Sequences and Iterables
    • Using * to Grab Excess Items
    • Unpacking with * in Function Calls and Sequence Literals
    • Nested Unpacking
  • Pattern Matching with Sequences
    • Pattern Matching Sequences in an Interpreter
      • Alternative patterns for lambda
      • Shortcut syntax for function definition
  • Slicing
    • Why Slices and Ranges Exclude the Last Item
    • Slice Objects
    • Multidimensional Slicing and Ellipsis
    • Assigning to Slices
  • Using + and * with Sequences
    • Building Lists of Lists
    • Augmented Assignment with Sequences
    • A += Assignment Puzzler
  • list.sort Versus the sorted Built-In
  • When a List Is Not the Answer
    • Arrays
    • Memory Views
    • NumPy
    • Deques and Other Queues
  • Chapter Summary
  • Further Reading
• 3. Dictionaries and Sets
  • Whats New in This Chapter
  • Modern dict Syntax
    • dict Comprehensions
    • Unpacking Mappings
    • Merging Mappings with |
  • Pattern Matching with Mappings
  • Standard API of Mapping Types
    • What Is Hashable
    • Overview of Common Mapping Methods
    • Inserting or Updating Mutable Values
  • Automatic Handling of Missing Keys
    • defaultdict: Another Take on Missing Keys
    • The __missing__ Method
    • Inconsistent Usage of __missing__ in the Standard Library
  • Variations of dict
    • collections.OrderedDict
    • collections.ChainMap
    • collections.Counter
    • shelve.Shelf
    • Subclassing UserDict Instead of dict
  • Immutable Mappings
  • Dictionary Views
  • Practical Consequences of How dict Works
  • Set Theory
    • Set Literals
    • Set Comprehensions
  • Practical Consequences of How Sets Work
    • Set Operations
  • Set Operations on dict Views
  • Chapter Summary
  • Further Reading
• 4. Unicode Text Versus Bytes
  • Whats New in This Chapter
  • Character Issues
  • Byte Essentials
  • Basic Encoders/Decoders
  • Understanding Encode/Decode Problems
    • Coping with UnicodeEncodeError
    • Coping with UnicodeDecodeError
    • SyntaxError When Loading Modules with Unexpected Encoding
    • How to Discover the Encoding of a Byte Sequence
    • BOM: A Useful Gremlin
  • Handling Text Files
    • Beware of Encoding Defaults
  • Normalizing Unicode for Reliable Comparisons
    • Case Folding
    • Utility Functions for Normalized Text Matching
    • Extreme Normalization: Taking Out Diacritics
  • Sorting Unicode Text
    • Sorting with the Unicode Collation Algorithm
  • The Unicode Database
    • Finding Characters by Name
    • Numeric Meaning of Characters
  • Dual-Mode str and bytes APIs
    • str Versus bytes in Regular Expressions
    • str Versus bytes in os Functions
  • Chapter Summary
  • Further Reading
• 5. Data Class Builders
  • Whats New in This Chapter
  • Overview of Data Class Builders
    • Main Features
      • Mutable instances
      • Class statement syntax
      • Construct dict
      • Get field names and default values
      • Get field types
      • New instance with changes
      • New class at runtime
  • Classic Named Tuples
  • Typed Named Tuples
  • Type Hints 101
    • No Runtime Effect
    • Variable Annotation Syntax
    • The Meaning of Variable Annotations
      • Inspecting a typing.NamedTuple
      • Inspecting a class decorated with dataclass
  • More About @dataclass
    • Field Options
    • Post-init Processing
    • Typed Class Attributes
    • Initialization Variables That Are Not Fields
    • @dataclass Example: Dublin Core Resource Record
  • Data Class as a Code Smell
    • Data Class as Scaffolding
    • Data Class as Intermediate Representation
  • Pattern Matching Class Instances
    • Simple Class Patterns
    • Keyword Class Patterns
    • Positional Class Patterns
  • Chapter Summary
  • Further Reading
• 6. Object References, Mutability, and Recycling
  • Whats New in This Chapter
  • Variables Are Not Boxes
  • Identity, Equality, and Aliases
    • Choosing Between == and is
    • The Relative Immutability of Tuples
  • Copies Are Shallow by Default
    • Deep and Shallow Copies of Arbitrary Objects
  • Function Parameters as References
    • Mutable Types as Parameter Defaults: Bad Idea
    • Defensive Programming with Mutable Parameters
  • del and Garbage Collection
  • Tricks Python Plays with Immutables
  • Chapter Summary
  • Further Reading
• II. Functions as Objects
• 7. Functions as First-Class Objects
  • Whats New in This Chapter
  • Treating a Function Like an Object
  • Higher-Order Functions
    • Modern Replacements for map, filter, and reduce
  • Anonymous Functions
  • The Nine Flavors of Callable Objects
  • User-Defined Callable Types
  • From Positional to Keyword-Only Parameters
    • Positional-Only Parameters
  • Packages for Functional Programming
    • The operator Module
    • Freezing Arguments with functools.partial
  • Chapter Summary
  • Further Reading
• 8. Type Hints in Functions
  • Whats New in This Chapter
  • About Gradual Typing
  • Gradual Typing in Practice
    • Starting with Mypy
    • Making Mypy More Strict
    • A Default Parameter Value
    • Using None as a Default
  • Types Are Defined by Supported Operations
  • Types Usable in Annotations
    • The Any Type
      • Subtype-of versus consistent-with
    • Simple Types and Classes
    • Optional and Union Types
    • Generic Collections
    • Tuple Types
      • Tuples as records
      • Tuples as records with named fields
      • Tuples as immutable sequences
    • Generic Mappings
    • Abstract Base Classes
      • The fall of the numeric tower
    • Iterable
      • abc.Iterable versus abc.Sequence
    • Parameterized Generics and TypeVar
      • Restricted TypeVar
      • Bounded TypeVar
      • The AnyStr predefined type variable
    • Static Protocols
    • Callable
      • Variance in Callable types
    • NoReturn
  • Annotating Positional Only and Variadic Parameters
  • Imperfect Typing and Strong Testing
  • Chapter Summary
  • Further Reading
• 9. Decorators and Closures
  • Whats New in This Chapter
  • Decorators 101
  • When Python Executes Decorators
  • Registration Decorators
  • Variable Scope Rules
  • Closures
  • The nonlocal Declaration
    • Variable Lookup Logic
  • Implementing a Simple Decorator
    • How It Works
  • Decorators in the Standard Library
    • Memoization with functools.cache
    • Using lru_cache
    • Single Dispatch Generic Functions
      • Function singledispatch
  • Parameterized Decorators
    • A Parameterized Registration Decorator
    • The Parameterized Clock Decorator
    • A Class-Based Clock Decorator
  • Chapter Summary
  • Further Reading
• 10. Design Patterns with First-Class Functions
  • Whats New in This Chapter
  • Case Study: Refactoring Strategy
    • Classic Strategy
    • Function-Oriented Strategy
    • Choosing the Best Strategy: Simple Approach
    • Finding Strategies in a Module
  • Decorator-Enhanced Strategy Pattern
  • The Command Pattern
  • Chapter Summary
  • Further Reading
• III. Classes and Protocols
• 11. A Pythonic Object
  • Whats New in This Chapter
  • Object Representations
  • Vector Class Redux
  • An Alternative Constructor
  • classmethod Versus staticmethod
  • Formatted Displays
  • A Hashable Vector2d
  • Supporting Positional Pattern Matching
  • Complete Listing of Vector2d, Version 3
  • Private and Protected Attributes in Python
  • Saving Memory with __slots__
    • Simple Measure of __slot__ Savings
    • Summarizing the Issues with __slots__
  • Overriding Class Attributes
  • Chapter Summary
  • Further Reading
• 12. Special Methods for Sequences
  • Whats New in This Chapter
  • Vector: A User-Defined Sequence Type
  • Vector Take #1: Vector2d Compatible
  • Protocols and Duck Typing
  • Vector Take #2: A Sliceable Sequence
    • How Slicing Works
    • A Slice-Aware __getitem__
  • Vector Take #3: Dynamic Attribute Access
  • Vector Take #4: Hashing and a Faster ==
  • Vector Take #5: Formatting
  • Chapter Summary
  • Further Reading
• 13. Interfaces, Protocols, and ABCs
  • The Typing Map
  • Whats New in This Chapter
  • Two Kinds of Protocols
  • Programming Ducks
    • Python Digs Sequences
    • Monkey Patching: Implementing a Protocol at Runtime
    • Defensive Programming and Fail Fast
  • Goose Typing
    • Subclassing an ABC
    • ABCs in the Standard Library
    • Defining and Using an ABC
    • ABC Syntax Details
    • Subclassing an ABC
    • A Virtual Subclass of an ABC
    • Usage of register in Practice
    • Structural Typing with ABCs
  • Static Protocols
    • The Typed double Function
    • Runtime Checkable Static Protocols
    • Limitations of Runtime Protocol Checks
    • Supporting a Static Protocol
    • Designing a Static Protocol
    • Best Practices for Protocol Design
    • Extending a Protocol
    • The numbers ABCs and Numeric Protocols
  • Chapter Summary
  • Further Reading
• 14. Inheritance: For Better or for Worse
  • Whats New in This Chapter
  • The super() Function
  • Subclassing Built-In Types Is Tricky
  • Multiple Inheritance and Method Resolution Order
  • Mixin Classes
    • Case-Insensitive Mappings
  • Multiple Inheritance in the Real World
    • ABCs Are Mixins Too
    • ThreadingMixIn and ForkingMixIn
    • Django Generic Views Mixins
    • Multiple Inheritance in Tkinter
  • Coping with Inheritance
    • Favor Object Composition over Class Inheritance
    • Understand Why Inheritance Is Used in Each Case
    • Make Interfaces Explicit with ABCs
    • Use Explicit Mixins for Code Reuse
    • Provide Aggregate Classes to Users
    • Subclass Only Classes Designed for Subclassing
    • Avoid Subclassing from Concrete Classes
    • Tkinter: The Good, the Bad, and the Ugly
  • Chapter Summary
  • Further Reading
• 15. More About Type Hints
  • Whats New in This Chapter
  • Overloaded Signatures
    • Max Overload
      • Arguments implementing SupportsLessThan, but key and default not provided
      • Argument key provided, but no default
      • Argument default provided, but no key
      • Arguments key and default provided
    • Takeaways from Overloading max
  • TypedDict
  • Type Casting
  • Reading Type Hints at Runtime
    • Problems with Annotations at Runtime
    • Dealing with the Problem
  • Implementing a Generic Class
    • Basic Jargon for Generic Types
  • Variance
    • An Invariant Dispenser
    • A Covariant Dispenser
    • A Contravariant Trash Can
    • Variance Review
      • Invariant types
      • Covariant types
      • Contravariant types
      • Variance rules of thumb
  • Implementing a Generic Static Protocol
  • Chapter Summary
  • Further Reading
• 16. Operator Overloading
  • Whats New in This Chapter
  • Operator Overloading 101
  • Unary Operators
  • Overloading + for Vector Addition
  • Overloading * for Scalar Multiplication
  • Using @ as an Infix Operator
  • Wrapping-Up Arithmetic Operators
  • Rich Comparison Operators
  • Augmented Assignment Operators
  • Chapter Summary
  • Further Reading
• IV. Control Flow
• 17. Iterators, Generators, and Classic Coroutines
  • Whats New in This Chapter
  • A Sequence of Words
  • Why Sequences Are Iterable: The iter Function
    • Using iter with a Callable
  • Iterables Versus Iterators
  • Sentence Classes with __iter__
    • Sentence Take #2: A Classic Iterator
    • Dont Make the Iterable an Iterator for Itself
    • Sentence Take #3: A Generator Function
    • How a Generator Works
  • Lazy Sentences
    • Sentence Take #4: Lazy Generator
    • Sentence Take #5: Lazy Generator Expression
  • When to Use Generator Expressions
  • An Arithmetic Progression Generator
    • Arithmetic Progression with itertools
  • Generator Functions in the Standard Library
  • Iterable Reducing Functions
  • Subgenerators with yield from
    • Reinventing chain
    • Traversing a Tree
  • Generic Iterable Types
  • Classic Coroutines
    • Example: Coroutine to Compute a Running Average
    • Returning a Value from a Coroutine
    • Generic Type Hints for Classic Coroutines
  • Chapter Summary
  • Further Reading
• 18. with, match, and else Blocks
  • Whats New in This Chapter
  • Context Managers and with Blocks
    • The contextlib Utilities
    • Using @contextmanager
  • Pattern Matching in lis.py: A Case Study
    • Scheme Syntax
    • Imports and Types
    • The Parser
    • The Environment
    • The REPL
    • The Evaluator
      • Evaluating numbers
      • Evaluating symbols
      • (quote )
      • (if )
      • (lambda )
      • (define )
      • (set! )
      • Function call
      • Catch syntax errors
    • Procedure: A Class Implementing a Closure
    • Using OR-patterns
  • Do This, Then That: else Blocks Beyond if
  • Chapter Summary
  • Further Reading
• 19. Concurrency Models in Python
  • Whats New in This Chapter
  • The Big Picture
  • A Bit of Jargon
    • Processes, Threads, and Pythons Infamous GIL
  • A Concurrent Hello World
    • Spinner with Threads
    • Spinner with Processes
    • Spinner with Coroutines
      • Experiment: Break the spinner for an insight
    • Supervisors Side-by-Side
  • The Real Impact of the GIL
    • Quick Quiz
      • 1. Answer for multiprocessing
      • 2. Answer for threading
      • 3. Answer for asyncio
  • A Homegrown Process Pool
    • Process-Based Solution
    • Understanding the Elapsed Times
    • Code for the Multicore Prime Checker
    • Experimenting with More or Fewer Processes
    • Thread-Based Nonsolution
  • Python in the Multicore World
    • System Administration
    • Data Science
    • Server-Side Web/Mobile Development
    • WSGI Application Servers
    • Distributed Task Queues
  • Chapter Summary
  • Further Reading
    • Concurrency with Threads and Processes
    • The GIL
    • Concurrency Beyond the Standard Library
    • Concurrency and Scalability Beyond Python
• 20. Concurrent Executors
  • Whats New in This Chapter
  • Concurrent Web Downloads
    • A Sequential Download Script
    • Downloading with concurrent.futures
    • Where Are the Futures?
  • Launching Processes with concurrent.futures
    • Multicore Prime Checker Redux
  • Experimenting with Executor.map
  • Downloads with Progress Display and Error Handling
    • Error Handling in the flags2 Examples
    • Using futures.as_completed
  • Chapter Summary
  • Further Reading
• 21. Asynchronous Programming
  • Whats New in This Chapter
  • A Few Definitions
  • An asyncio Example: Probing Domains
    • Guidos Trick to Read Asynchronous Code
  • New Concept: Awaitable
  • Downloading with asyncio and HTTPX
    • The Secret of Native Coroutines: Humble Generators
    • The All-or-Nothing Problem
  • Asynchronous Context Managers
  • Enhancing the asyncio Downloader
    • Using asyncio.as_completed and a Thread
    • Throttling Requests with a Semaphore
    • Making Multiple Requests for Each Download
  • Delegating Tasks to Executors
  • Writing asyncio Servers
    • A FastAPI Web Service
    • An asyncio TCP Server
  • Asynchronous Iteration and Asynchronous Iterables
    • Asynchronous Generator Functions
      • Experimenting with Pythons async console
      • Implementing an asynchronous generator
      • Asynchronous generators as context managers
      • Asynchronous generators versus native coroutines
    • Async Comprehensions and Async Generator Expressions
      • Defining and using an asynchronous generator expression
      • Asynchronous comprehensions
  • async Beyond asyncio: Curio
  • Type Hinting Asynchronous Objects
  • How Async Works and How It Doesnt
    • Running Circles Around Blocking Calls
    • The Myth of I/O-Bound Systems
    • Avoiding CPU-Bound Traps
  • Chapter Summary
  • Further Reading
• V. Metaprogramming
• 22. Dynamic Attributes and Properties
  • Whats New in This Chapter
  • Data Wrangling with Dynamic Attributes
    • Exploring JSON-Like Data with Dynamic Attributes
    • The Invalid Attribute Name Problem
    • Flexible Object Creation with __new__
  • Computed Properties
    • Step 1: Data-Driven Attribute Creation
    • Step 2: Property to Retrieve a Linked Record
    • Step 3: Property Overriding an Existing Attribute
    • Step 4: Bespoke Property Cache
    • Step 5: Caching Properties with functools
  • Using a Property for Attribute Validation
    • LineItem Take #1: Class for an Item in an Order
    • LineItem Take #2: A Validating Property
  • A Proper Look at Properties
    • Properties Override Instance Attributes
    • Property Documentation
  • Coding a Property Factory
  • Handling Attribute Deletion
  • Essential Attributes and Functions for Attribute Handling
    • Special Attributes that Affect Attribute Handling
    • Built-In Functions for Attribute Handling
    • Special Methods for Attribute Handling
  • Chapter Summary
  • Further Reading
• 23. Attribute Descriptors
  • Whats New in This Chapter
  • Descriptor Example: Attribute Validation
    • LineItem Take #3: A Simple Descriptor
      • Terms to understand descriptors
    • LineItem Take #4: Automatic Naming of Storage Attributes
    • LineItem Take #5: A New Descriptor Type
  • Overriding Versus Nonoverriding Descriptors
    • Overriding Descriptors
    • Overriding Descriptor Without __get__
    • Nonoverriding Descriptor
    • Overwriting a Descriptor in the Class
  • Methods Are Descriptors
  • Descriptor Usage Tips
  • Descriptor Docstring and Overriding Deletion
  • Chapter Summary
  • Further Reading
• 24. Class Metaprogramming
  • Whats New in This Chapter
  • Classes as Objects
  • type: The Built-In Class Factory
  • A Class Factory Function
  • Introducing __init_subclass__
    • Why __init_subclass__ Cannot Configure __slots__
  • Enhancing Classes with a Class Decorator
  • What Happens When: Import Time Versus Runtime
    • Evaluation Time Experiments
  • Metaclasses 101
    • How a Metaclass Customizes a Class
    • A Nice Metaclass Example
    • Metaclass Evaluation Time Experiment
  • A Metaclass Solution for Checked
  • Metaclasses in the Real World
    • Modern Features Simplify or Replace Metaclasses
    • Metaclasses Are Stable Language Features
    • A Class Can Only Have One Metaclass
    • Metaclasses Should Be Implementation Details
  • A Metaclass Hack with __prepare__
  • Wrapping Up
  • Chapter Summary
  • Further Reading
• Afterword
  • Further Reading
• Index

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