Brett Slatkin

Effective Python

125 Specific Ways to Write Better Python

• Broschiertes Buch

Produktbeschreibung

Master the art of Python programming with 125 actionable best practices to write more efficient, readable, and maintainable code.   Python is a versatile and powerful language, but leveraging its full potential requires more than just knowing the syntax. Effective Python: 125 Specific Ways to Write Better Python, 3rd Edition is your comprehensive guide to mastering Python's unique strengths and avoiding its hidden pitfalls. This updated edition builds on the acclaimed second edition, expanding from 90 to 125 best practices that are essential for writing high-quality Python code.   Drawing on years of experience at Google, Brett Slatkin offers clear, concise, and practical advice for both new and experienced Python developers. Each item in the book provides insight into the "Pythonic" way of programming, helping you understand how to write code that is not only effective but also elegant and maintainable. Whether you're building web applications, analyzing data, writing automation scripts, or training AI models, this book will equip you with the skills to make a significant impact using Python.   Key Features of the 3rd Edition: Expanded Content: Now with 125 actionable guidelines, including 35 entirely new items. Updated Best Practices: Reflects the latest features in Python releases up to version 3.13. New Chapters: Additional chapters on how to build robust programs that achieve high performance. Advanced Topics: In-depth coverage of creating C-extension modules and interfacing with native shared libraries. Practical Examples: Realistic code examples that illustrate each best practice.

Produktdetails

• Effective Software Development Series
• Verlag: Pearson Education (US)
• 3 ed
• Seitenzahl: 672
• Erscheinungstermin: 30. November 2024
• Englisch
• Abmessung: 231mm x 178mm x 37mm
• Gewicht: 1228g
• ISBN-13: 9780138172183
• ISBN-10: 0138172188
• Artikelnr.: 69484044

Autorenporträt

Brett Slatkin is a Principal Software Engineer at Google in the Office of the CTO, focusing on emerging technologies. He co-founded Google Surveys, launched Google Clouds first product (App Engine), and co-created the PubSubHubbub protocolall using Python. Brett has been writing Python code professionally for the past 19 years and has made numerous contributions to open-source projects.

Inhaltsangabe

Preface     xvii
Acknowledgments     xxiii
About the Author     xxv
 
Chapter 1: Pythonic Thinking     1
     Item 1: Know Which Version of Python Youre Using     1
     Item 2: Follow the PEP 8 Style Guide     3
     Item 3: Never Expect Python to Detect Errors at Compile Time     6
     Item 4: Write Helper Functions Instead of Complex Expressions     8
     Item 5: Prefer Multiple-Assignment Unpacking Over Indexing     11
     Item 6: Always Surround Single-Element Tuples with Parentheses     16
     Item 7: Consider Conditional Expressions for Simple Inline Logic
    19
     Item 8: Prevent Repetition with Assignment Expressions     24
     Item 9: Consider match for Destructuring in Flow Control; Avoid When
if Statements Are Sufficient     30
 
Chapter 2: Strings and Slicing     41
     Item 10: Know the Differences Between bytes and str     41
     Item 11: Prefer Interpolated F-Strings over C-Style Format Strings and
str.format     47
     Item 12: Understand the Difference Between  repr and str when Printing
Objects     58
     Item 13: Prefer Explicit String Concatenation over Implicit,
Especially in Lists     62
     Item 14: Know How to Slice Sequences     67
     Item 15: Avoid Striding and Slicing in a Single Expression     70
     Item 16: Prefer Catch-All Unpacking Over Slicing     72
 
Chapter 3: Loops and Iterators     77
     Item 17: Prefer enumerate over range     77
     Item 18: Use zip to Process Iterators in Parallel     79
     Item 19: Avoid else Blocks After for and while Loops     82
     Item 20: Never Use for Loop Variables After the Loop Ends     85
     Item 21: Be Defensive when Iterating over Arguments     87
     Item 22: Never Modify Containers While Iterating over Them; Use Copies
or Caches Instead     92
     Item 23: Pass Iterators to any and all for Efficient Short-Circuiting
Logic     98
     Item 24: Consider itertools for Working with Iterators and Generators
    102
 
Chapter 4: Dictionaries     109
     Item 25: Be Cautious when Relying on Dictionary Insertion Ordering
    109
     Item 26: Prefer get over in and KeyError to Handle Missing Dictionary
Keys     117
     Item 27: Prefer defaultdict over setdefault to Handle Missing Items in
Internal State     122
     Item 28: Know How to Construct Key-Dependent Default Values with
__missing__     124
     Item 29: Compose Classes Instead of Deeply Nesting Dictionaries,
Lists, and Tuples     127
 
Chapter 5: Functions     135
     Item 30: Know That Function Arguments Can Be Mutated     135
     Item 31: Return Dedicated Result Objects Instead of Requiring Function
Callers to Unpack More Than Three Variables     138
     Item 32: Prefer Raising Exceptions to Returning None     142
     Item 33: Know How Closures Interact with Variable Scope and nonlocal
    145
     Item 34: Reduce Visual Noise with Variable Positional Arguments
    150
     Item 35: Provide Optional Behavior with Keyword Arguments     153
     Item 36: Use None and Docstrings to Specify Dynamic Default Arguments
    157
     Item 37: Enforce Clarity with Keyword-Only and Positional-Only
Arguments     161
     Item 38: Define Function Decorators with functools.wraps     166
     Item 39: Prefer functools.partial over lambda Expressions for Glue
Functions     169
 
Chapter 6: Comprehensions and Generators     173
     Item 40: Use Comprehensions Instead of map and filter     173
     Item 41: Avoid More Than Two Control Subexpressions in Comprehensions
    176
     Item 42: Reduce Repetition in Comprehensions with Assignment
Expressions     178
     Item 43: Consider Generators Instead of Returning Lists     182
     Item 44: Consider Generator Expressions for Large List Comprehensions
    184
     Item 45: Compose Multiple Generators with yield from     186
     Item 46: Pass Iterators into Generators as Arguments Instead of
Calling the send Method     188
     Item 47: Manage Iterative State Transitions with a Class Instead of
the Generator throw Method     195
 
Chapter 7: Classes and Interfaces     201
     Item 48: Accept Functions Instead of Classes for Simple Interfaces
    201
     Item 49: Prefer Object-Oriented Polymorphism over Functions with
isinstance Checks     205
     Item 50: Consider functools.singledispatch for Functional-Style
Programming Instead of Object-Oriented Polymorphism     210
     Item 51: Prefer dataclasses for Defining Lightweight Classes     217
     Item 52: Use @classmethod Polymorphism to Construct Objects
Generically     230
     Item 53: Initialize Parent Classes with super     235
     Item 54: Consider Composing Functionality with Mix-in Classes     240
     Item 55: Prefer Public Attributes over Private Ones     245
     Item 56: Prefer dataclasses for Creating Immutable Objects     250
     Item 57: Inherit from collections.abc Classes for Custom Container
Types     260
 
Chapter 8: Metaclasses and Attributes     265
     Item 58: Use Plain Attributes Instead of Setter and Getter Methods
    265
     Item 59: Consider @property Instead of Refactoring Attributes     270
     Item 60: Use Descriptors for Reusable @property Methods     274
     Item 61: Use __getattr__, __getattribute__, and __setattr__ for Lazy
Attributes     279
     Item 62: Validate Subclasses with __init_subclass__     285
     Item 63: Register Class Existence with __init_subclass__     293
     Item 64: Annotate Class Attributes with __set_name__     299
     Item 65: Consider Class Body Definition Order to Establish
Relationships Between Attributes     303
     Item 66: Prefer Class Decorators over Metaclasses for Composable Class
Extensions     310
 
Chapter 9: Concurrency and Parallelism     319
     Item 67: Use subprocess to Manage Child Processes     320
     Item 68: Use Threads for Blocking I/O; Avoid for Parallelism     324
     Item 69: Use Lock to Prevent Data Races in Threads     330
     Item 70: Use Queue to Coordinate Work Between Threads     333
     Item 71: Know How to Recognize When Concurrency Is Necessary     344
     Item 72: Avoid Creating New Thread Instances for On-Demand Fan-out
    349
     Item 73: Understand How Using Queue for Concurrency Requires
Refactoring     353
     Item 74: Consider ThreadPoolExecutor When Threads Are Necessary for
Concurrency     361
     Item 75: Achieve Highly Concurrent I/O with Coroutines     364
     Item 76: Know How to Port Threaded I/O to asyncio     368
     Item 77: Mix Threads and Coroutines to Ease the Transition to asyncio
    381
     Item 78: Maximize Responsiveness of asyncio Event Loops with
async-friendly Worker Threads     389
     Item 79: Consider concurrent.futures for True Parallelism     393
 
Chapter 10: Robustness     399
     Item 80: Take Advantage of Each Block in try/except/else/finally
    399
     Item 81: assert Internal Assumptions and raise Missed Expectations
    404
     Item 82: Consider contextlib and with Statements for Reusable
try/finally Behavior     408
     Item 83: Always Make try Blocks as Short as Possible     412
     Item 84: Beware of Exception Variables Disappearing     414
     Item 85: Beware of Catching the Exception Class     416
     Item 86: Understand the Difference Between Exception and BaseException
    419
     Item 87: Use traceback for Enhanced Exception Reporting     424
     Item 88: Consider Explicitly Chaining Exceptions to Clarify Tracebacks
    428
     Item 89: Always Pass Resources into Generators and Have Callers Clean
Them Up Outside     436
     Item 90: Never Set __debug__ to False     442
     Item 91: Avoid exec and eval Unless Youre Building a Developer Tool
    445
 
Chapter 11: Performance     447
     Item 92: Profile Before Optimizing     448
     Item 93: Optimize Performance-Critical Code Using timeit
Microbenchmarks     453
     Item 94: Know When and How to Replace Python with Another Programming
Language     458
     Item 95: Consider ctypes to Rapidly Integrate with Native Libraries
    462
     Item 96: Consider Extension Modules to Maximize Performance and
Ergonomics     467
     Item 97: Rely on Precompiled Bytecode and File System Caching to
Improve Startup Time     475
     Item 98: Lazy-Load Modules with Dynamic Imports to Reduce Startup Time
    478
     Item 99: Consider memoryview and bytearray for Zero-Copy Interactions
with bytes     485
 
Chapter 12: Data Structures & Algorithms     493
     Item 100: Sort by Complex Criteria Using the key Parameter     493
     Item 101: Know the Difference Between sort and sorted     499
     Item 102: Consider Searching Sorted Sequences with bisect     501
     Item 103: Prefer deque for Producer-Consumer Queues     504
     Item 104: Know How to Use heapq for Priority Queues     509
     Item 105: Use datetime Instead of time for Local Clocks     519
     Item 106: Use decimal When Precision Is Paramount     523
     Item 107: Make pickle Serialization Maintainable with copyreg     526
 
Chapter 13: Testing and Debugging     533
     Item 108: Verify Related Behaviors in TestCase Subclasses     533
     Item 109: Prefer Integration Tests over Unit Tests     541
     Item 110: Isolate Tests From Each Other with setUp, tearDown,
setUpModule, and tearDownModule     547
     Item 111: Use Mocks to Test Code with Complex Dependencies     550
     Item 112: Encapsulate Dependencies to Facilitate Mocking and Testing
    559
     Item 113: Use assertAlmostEqual to Control Precision in Floating Point
Tests     563
     Item 114: Consider Interactive Debugging with pdb     565
     Item 115: Use tracemalloc to Understand Memory Usage and Leaks     570
 
Chapter 14: Collaboration     575
     Item 116: Know Where to Find Community-Built Modules     575
     Item 117: Use Virtual Environments for Isolated and Reproducible
Dependencies     576
     Item 118: Write Docstrings for Every Function, Class, and Module
    582
     Item 119: Use Packages to Organize Modules and Provide Stable APIs
    588
     Item 120: Consider Module-Scoped Code to Configure Deployment
Environments     593
     Item 121: Define a Root Exception to Insulate Callers from APIs
    595
     Item 122: Know How to Break Circular Dependencies     600
     Item 123: Consider warnings to Refactor and Migrate Usage     605
     Item 124: Consider Static Analysis via typing to Obviate Bugs     613
     Item 125: Prefer Open Source Projects for Bundling Python Programs
over zipimport and zipapp     621
 
Index     627