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“Each item in Slatkin’s Effective Python teaches a self-contained lesson with its own source code. This makes the book random-access: Items are easy to browse and study in whatever order the reader needs. I will be recommending Effective Python to students as an admirably compact source of mainstream advice on a very broad range of topics for the intermediate Python programmer.”

—Brandon Rhodes, software engineer at Dropbox and chair of PyCon 2016-2017

It’s easy to start coding with Python, which is why the language is so popular. However, Python’s unique strengths, charms, and expressiveness can be hard to grasp, and there are hidden pitfalls that can easily trip you up.

Effective Python will help you master a truly “Pythonic” approach to programming, harnessing Python’s full power to write exceptionally robust and well-performing code. Using the concise, scenario-driven style pioneered in Scott Meyers’ best-selling Effective C++, Brett Slatkin brings together 59 Python best practices, tips, and shortcuts, and explains them with realistic code examples.

Drawing on years of experience building Python infrastructure at Google, Slatkin uncovers little-known quirks and idioms that powerfully impact code behavior and performance. You’ll learn the best way to accomplish key tasks, so you can write code that’s easier to understand, maintain, and improve.

Key features include

• Actionable guidelines for all major areas of Python 3.x and 2.x development, with detailed explanations and examples
• Best practices for writing functions that clarify intention, promote reuse, and avoid bugs
• Coverage of how to accurately express behaviors with classes and objects
• Guidance on how to avoid pitfalls with metaclasses and dynamic attributes
• More efficient approaches to concurrency and parallelism
• Better techniques and idioms for using Python’s built-in modules
• Tools and best practices for collaborative development
• Solutions for debugging, testing, and optimization in order to improve quality and performance

정보제공 :

Preface	p. xiii
Acknowledgments	p. xvii
About the Author	p. xix
Chapter 1	Pythonic Thinking	p. 1
Item 1	    Know Which Version of Python You''re Using	p. 1
Item 2	    Follow the PEP 8 Style Guide	p. 2
Item 3	    Know the Differences Between bytes, str, and unicode	p. 5
Item 4	    Write Helper Functions Instead of Complex Expressions	p. 8
Item 5	    Know How to Slice Sequences	p. 10
Item 6	    Avoid Using start, end, and stride in a Single Slice	p. 13
Item 7	    Use List Comprehensions Instead of map and filter	p. 15
Item 8	    Avoid More Than Two Expressions in List Comprehensions	p. 16
Item 9	    Consider Generator Expressions for Large Comprehensions	p. 18
Item 10	    Prefer enumerate Over range	p. 20
Item 11	    Use zip to Process Iterators in Parallel	p. 21
Item 12	    Avoid else Blocks After for and while Loops	p. 23
Item 13	    Take Advantage of Each Block in try/except/else/finally	p. 26
Chapter 2	Functions	p. 29
Item 14	    Prefer Exceptions to Returning None	p. 29
Item 15	    Know How Closures Interact with Variable Scope	p. 31
Item 16	    Consider Generators Instead of Returning Lists	p. 36
Item 17	    Be Defensive When Iterating Over Arguments	p. 38
Item 18	    Reduce Visual Noise with Variable Positional Arguments	p. 43
Item 19	    Provide Optional Behavior with Keyword Arguments	p. 45
Item 20	    Use None and Docstrings to Specify Dynamic Default Arguments	p. 48
Item 21	    Enforce Clarity with Keyword-Only Arguments	p. 51
Chapter 3	Classes and Inheritance	p. 55
Item 22	    Prefer Helper Classes Over Bookkeeping with Dictionaries and Tuples	p. 55
Item 23	    Accept Functions for Simple Interfaces Instead of Classes	p. 61
Item 24	    Use @classmethod Polymorphism to Construct Objects Generically	p. 64
Item 25	    Initialize Parent Classes with super	p. 69
Item 26	    Use Multiple Inheritance Only for Mix-in Utility Classes	p. 73
Item 27	    Prefer Public Attributes Over Private Ones	p. 78
Item 28	    Inherit from collections.abc for Custom Container Types	p. 83
Chapter 4	Metaclasses and Attributes	p. 87
Item 29	    Use Plain Attributes Instead of Get and Set Methods	p. 87
Item 30	    Consider @property Instead of Refactoring Attributes	p. 91
Item 31	    Use Descriptors for Reusable @property Methods	p. 95
Item 32	    Use getattr, getattribute, and setattr for Lazy Attributes	p. 100
Item 33	    Validate Subclasses with Metaclasses	p. 105
Item 34	    Register Class Existence with Metaclasses	p. 108
Item 35	    Annotate Class Attributes with Metaclasses	p. 112
Chapter 5	Concurrency and Parallelism	p. 117
Item 36	    Use subprocess to Manage Child Processes	p. 118
Item 37	    Use Threads for Blocking I/O, Avoid for Parallelism	p. 122
Item 38	    Use Lock to Prevent Data Races in Threads	p. 126
Item 39	    Use Queue to Coordinate Work Between Threads	p. 129
Item 40	    Consider Coroutines to Run Many Functions Concurrently	p. 136
Item 41	    Consider concurrent, futures for True Parallelism	p. 145
Chapter 6	Built-in Modules	p. 151
Item 42	    Define Function Decorators with functools.wraps	p. 151
Item 43	    Consider contextlib and with Statements for Reusable try/finally Behavior	p. 153
Item 44	    Make pickle Reliable with copyreg	p. 157
Item 45	    Use datetime Instead of time for Local Clocks	p. 162
Item 46	    Use Built-in Algorithms and Data Structures	p. 166
Item 47	    Use decimal When Precision Is Paramount	p. 171
Item 48	    Know Where to Find Community-Built Modules	p. 173
Chapter 7	Collaboration	p. 175
Item 49	    Write Docstrings for Every Function, Class, and Module	p. 175
Item 50	    Use Packages to Organize Modules and Provide Stable APIs	p. 179
Item 51	    Define a Root Exception to Insulate Callers from APIs	p. 184
Item 52	    Know How to Break Circular Dependencies	p. 187
Item 53	    Use Virtual Environments for Isolated and Reproducible Dependencies	p. 192
Chapter 8	Production	p. 199
Item 54	    Consider Module-Scoped Code to Configure Deployment Environments	p. 199
Item 55	    Use repr Strings for Debugging Output	p. 202
Item 56	    Test Everything with unittest	p. 204
Item 57	    Consider Interactive Debugging with pdb	p. 208
Item 58	    Profile Before Optimizing	p. 209
Item 59	    Use tracemalloc to Understand Memory Usage and Leaks	p. 214
Index	p. 217