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Effective Python: 90 Specific Ways to Write Better Python, 2nd Edition

by Brett Slatkin

November 2019

Intermediate to advanced

480 pages

13h 56m

English

Addison-Wesley Professional

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Item 1: Know Which Version of Python You’re UsingItem 2: Follow the PEP 8 Style GuideItem 3: Know the Differences Between bytes and strItem 4: Prefer Interpolated F-Strings Over C-style Format Strings and str.formatItem 5: Write Helper Functions Instead of Complex ExpressionsItem 6: Prefer Multiple Assignment Unpacking Over IndexingItem 7: Prefer enumerate Over rangeItem 8: Use zip to Process Iterators in ParallelItem 9: Avoid else Blocks After for and while LoopsItem 10: Prevent Repetition with Assignment Expressions
Item 11: Know How to Slice SequencesItem 12: Avoid Striding and Slicing in a Single ExpressionItem 13: Prefer Catch-All Unpacking Over SlicingItem 14: Sort by Complex Criteria Using the key ParameterItem 15: Be Cautious When Relying on dict Insertion OrderingItem 16: Prefer get Over in and KeyError to Handle Missing Dictionary KeysItem 17: Prefer defaultdict Over setdefault to Handle Missing Items in Internal StateItem 18: Know How to Construct Key-Dependent Default Values with __missing__
Item 19: Never Unpack More Than Three Variables When Functions Return Multiple ValuesItem 20: Prefer Raising Exceptions to Returning NoneItem 21: Know How Closures Interact with Variable ScopeItem 22: Reduce Visual Noise with Variable Positional ArgumentsItem 23: Provide Optional Behavior with Keyword ArgumentsItem 24: Use None and Docstrings to Specify Dynamic Default ArgumentsItem 25: Enforce Clarity with Keyword-Only and Positional-Only ArgumentsItem 26: Define Function Decorators with functools.wraps
Item 27: Use Comprehensions Instead of map and filterItem 28: Avoid More Than Two Control Subexpressions in ComprehensionsItem 29: Avoid Repeated Work in Comprehensions by Using Assignment ExpressionsItem 30: Consider Generators Instead of Returning ListsItem 31: Be Defensive When Iterating Over ArgumentsItem 32: Consider Generator Expressions for Large List ComprehensionsItem 33: Compose Multiple Generators with yield fromItem 34: Avoid Injecting Data into Generators with sendItem 35: Avoid Causing State Transitions in Generators with throwItem 36: Consider itertools for Working with Iterators and Generators
Item 37: Compose Classes Instead of Nesting Many Levels of Built-in TypesItem 38: Accept Functions Instead of Classes for Simple InterfacesItem 39: Use @classmethod Polymorphism to Construct Objects GenericallyItem 40: Initialize Parent Classes with superItem 41: Consider Composing Functionality with Mix-in ClassesItem 42: Prefer Public Attributes Over Private OnesItem 43: Inherit from collections.abc for Custom Container Types
Item 44: Use Plain Attributes Instead of Setter and Getter MethodsItem 45: Consider @property Instead of Refactoring AttributesItem 46: Use Descriptors for Reusable @property MethodsItem 47: Use __getattr__, __getattribute__, and __setattr__ for Lazy AttributesItem 48: Validate Subclasses with __init_subclass__Item 49: Register Class Existence with __init_subclass__Item 50: Annotate Class Attributes with __set_name__Item 51: Prefer Class Decorators Over Metaclasses for Composable Class Extensions
Item 52: Use subprocess to Manage Child ProcessesItem 53: Use Threads for Blocking I/O, Avoid for ParallelismItem 54: Use Lock to Prevent Data Races in ThreadsItem 55: Use Queue to Coordinate Work Between ThreadsItem 56: Know How to Recognize When Concurrency Is NecessaryItem 57: Avoid Creating New Thread Instances for On-demand Fan-outItem 58: Understand How Using Queue for Concurrency Requires RefactoringItem 59: Consider ThreadPoolExecutor When Threads Are Necessary for ConcurrencyItem 60: Achieve Highly Concurrent I/O with CoroutinesItem 61: Know How to Port Threaded I/O to asyncioItem 62: Mix Threads and Coroutines to Ease the Transition to asyncioItem 63: Avoid Blocking the asyncio Event Loop to Maximize ResponsivenessItem 64: Consider concurrent.futures for True Parallelism
Item 65: Take Advantage of Each Block in try/except/else/finallyItem 66: Consider contextlib and with Statements for Reusable try/finally BehaviorItem 67: Use datetime Instead of time for Local ClocksItem 68: Make pickle Reliable with copyregItem 69: Use decimal When Precision Is ParamountItem 70: Profile Before OptimizingItem 71: Prefer deque for Producer–Consumer QueuesItem 72: Consider Searching Sorted Sequences with bisectItem 73: Know How to Use heapq for Priority QueuesItem 74: Consider memoryview and bytearray for Zero-Copy Interactions with bytes
Item 75: Use repr Strings for Debugging OutputItem 76: Verify Related Behaviors in TestCase SubclassesItem 77: Isolate Tests from Each Other with setUp, tearDown, setUpModule, and tearDownModuleItem 78: Use Mocks to Test Code with Complex DependenciesItem 79: Encapsulate Dependencies to Facilitate Mocking and TestingItem 80: Consider Interactive Debugging with pdbItem 81: Use tracemalloc to Understand Memory Usage and Leaks
Item 82: Know Where to Find Community-Built ModulesItem 83: Use Virtual Environments for Isolated and Reproducible DependenciesItem 84: Write Docstrings for Every Function, Class, and ModuleItem 85: Use Packages to Organize Modules and Provide Stable APIsItem 86: Consider Module-Scoped Code to Configure Deployment EnvironmentsItem 87: Define a Root Exception to Insulate Callers from APIsItem 88: Know How to Break Circular DependenciesItem 89: Consider warnings to Refactor and Migrate UsageItem 90: Consider Static Analysis via typing to Obviate Bugs

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Effective Python: 125 Specific Ways to Write Better Python, 3rd Edition

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ISBN: 9780134854717

Effective Python: 90 Specific Ways to Write Better Python, 2nd Edition

by Brett Slatkin

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