杜斯提·，Dusty Phillips is a Canadian software developer and author currently living in Seattle, Washington. He has been active in the open source community for a decade and a half and programming in Python for nearly all of it. He cofounded the popular Puget Sound Programming Python meetup group; drop by and say hi if you're in the area.
目录
Preface Chapter 1: Object-oriented Desiqn Introducing object-oriented Objects and classes Specifying attributes and behaviors Data describes objects Behaviors are actions Hiding details and creating the public interface Composition Inheritance Inheritance provides abstraction Multiple inheritance Case study Exercises Summary Chapter 2: Objects in Python Creating Python classes Adding attributes Making it do something Talking to yourself More arguments Initializing the object Explaining yourself Modules and packages Organizing the modules Absolute imports Relative imports Organizing module contents Who can access my data? Third-party libraries Case study Exercises Summary Chapter 3: When Objects Are Alike Basic inheritance Extending built-ins Overriding and super Multiple inheritance The diamond problem Different sets of arguments Polymorphism Abstract base classes Using an abstract base class Creating an abstract base class Demystifying the magic Case study Exercises Summary Chapter 4: Expecting the Unexpected Raising exceptions Raising an exception The effects of an exception Handling exceptions The exception hierarchy Defining our own exceptions Case study Exercises Summary Chapter 5: When to Use Object-oriented Programming Treat objects as objects Adding behavior to class data with properties Properties in detail Decorators - another way to create properties Deciding when to use properties Manager objects Removing duplicate code In practice Case study Exercises Summary Chapter 6: Python Data Structures Empty objects Tuples and named tuples Named tuples Dictionaries Dictionary use cases Using defaultdict Counter Lists Sorting lists Sets Extending built-ins Queues FIFO queues LIFO queues Priority queues Case study Exercises Summary Chapter 7: Python Object-oriented Shortcuts Python built-in functions The len() function Reversed Enumerate File I/O Placing it in context An alternative to method overloading Default arguments Variable argument lists Unpacking arguments Functions are objects too Using functions as attributes Callable objects Case study Exercises Summary Chapter 8: Strings and Serialization Strings String manipulation String formatting Escaping braces Keyword arguments Container Iookups Object Iookups Making it look right Strings are Unicode Converting bytes to text Converting text to bytes Mutable byte strings Regular expressions Matching patterns Matching a selection of characters Escaping characters Matching multiple characters Grouping patterns together Getting information from regular expressions Making repeated regular expressions efficient Serializing objects Customizing pickles Serializing web objects Case study Exercises Summary Chapter 9: The Iterator Pattern Design patterns in brief Iterators The iterator protocol Comprehensions List comprehensions Set and dictionary comprehensions Generator expressions Generators Yield items from another iterable Coroutines Back to log parsing Closing coroutines and throwing exceptions The relationship between coroutines, generators, and functions Case study Exercises Summary Chapter 10: Python Design Patterns I The decorator pattern A decorator example Decorators in Python The observer pattern An observer example The strategy pattern A strategy example Strategy in Python The state pattern A state example State versus strategy State transition as coroutines The singleton pattern Singleton implementation The template pattern A template example Exercises Summary Chapter 11: Python Design Patterns II The adapter pattern The facade pattern The flyweight pattern The command pattern The abstract factory pattern The composite pattern Exercises Summary Chapter 12: Testing Object-oriented Programs Why test? Test-driven development Unit testing Assertion methods Reducing boilerplate and cleaning up Organizing and running tests Ignoring broken tests Testing with py.test One way to do setup and cleanup A completely different way to set up variables Skipping tests with py.test Imitating expensive objects How much testing is enough? Case study Implementing it Exercises Summary Chapter 13: Concurrency Threads The many problems with threads Shared memory The global interpreter lock Thread overhead Multiprocessing Multiprocessing pools Queues The problems with multiprocessing Futures AsynclO AsynclO in action Reading an AsynclO future AsynclO for networking Using executors to wrap blocking code Streams Executors Case study Exercises Summary Index
