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Effective Python : 125 Specific Ways to Write Better Python
Effective Python : 125 Specific Ways to Write Better Python
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Author(s): Slatkin, Brett
ISBN No.: 9780138172183
Pages: 672
Year: 202501
Format: Trade Paper
Price: $ 78.85
Dispatch delay: Dispatched between 7 to 15 days
Status: Available (Forthcoming)

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


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