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Effective Python.pdf

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    About This eBook
    Effective Python
    Praise for Effective Python
    Contents
    Preface
    What This Book Covers
    Chapter 1: Pythonic Thinking
    Chapter 2: Functions
    Chapter 3: Classes and Inheritance
    Chapter 4: Metaclasses and Attributes
    Chapter 5: Concurrency and Parallelism
    Chapter 6: Built-in Modules
    Chapter 7: Collaboration
    Chapter 8: Production
    Conventions Used in This Book
    Where to Get the Code and Errata
    Acknowledgments
    About the Author
    1. Pythonic Thinking
    Item 1: Know Which Version of Python You’re Using
    Things to Remember
    Item 2: Follow the PEP 8 Style Guide
    Things to Remember
    Item 3: Know the Differences Between bytes, str, and unicode
    Things to Remember
    Item 4: Write Helper Functions Instead of Complex Expressions
    Things to Remember
    Item 5: Know How to Slice Sequences
    Things to Remember
    Item 6: Avoid Using start, end, and stride in a Single Slice
    Things to Remember
    Item 7: Use List Comprehensions Instead of map and filter
    Things to Remember
    Item 8: Avoid More Than Two Expressions in List Comprehensions
    Things to Remember
    Item 9: Consider Generator Expressions for Large Comprehensions
    Things to Remember
    Item 10: Prefer enumerate Over range
    Things to Remember
    Item 11: Use zip to Process Iterators in Parallel
    Things to Remember
    Item 12: Avoid else Blocks After for and while Loops
    Things to Remember
    Item 13: Take Advantage of Each Block in try/except/else/finally
    Finally Blocks
    Else Blocks
    Everything Together
    Things to Remember
    2. Functions
    Item 14: Prefer Exceptions to Returning None
    Things to Remember
    Item 15: Know How Closures Interact with Variable Scope
    Getting Data Out
    Scope in Python 2
    Things to Remember
    Item 16: Consider Generators Instead of Returning Lists
    Things to Remember
    Item 17: Be Defensive When Iterating Over Arguments
    Things to Remember
    Item 18: Reduce Visual Noise with Variable Positional Arguments
    Things to Remember
    Item 19: Provide Optional Behavior with Keyword Arguments
    Things to Remember
    Item 20: Use None and Docstrings to Specify Dynamic Default Arguments
    Things to Remember
    Item 21: Enforce Clarity with Keyword-Only Arguments
    Keyword-Only Arguments in Python 2
    Things to Remember
    3. Classes and Inheritance
    Item 22: Prefer Helper Classes Over Bookkeeping with Dictionaries and Tuples
    Refactoring to Classes
    Things to Remember
    Item 23: Accept Functions for Simple Interfaces Instead of Classes
    Things to Remember
    Item 24: Use @classmethod Polymorphism to Construct Objects Generically
    Things to Remember
    Item 25: Initialize Parent Classes with super
    Things to Remember
    Item 26: Use Multiple Inheritance Only for Mix-in Utility Classes
    Things to Remember
    Item 27: Prefer Public Attributes Over Private Ones
    Things to Remember
    Item 28: Inherit from collections.abc for Custom Container Types
    Things to Remember
    4. Metaclasses and Attributes
    Item 29: Use Plain Attributes Instead of Get and Set Methods
    Things to Remember
    Item 30: Consider @property Instead of Refactoring Attributes
    Things to Remember
    Item 31: Use Descriptors for Reusable @property Methods
    Things to Remember
    Item 32: Use __getattr__, __getattribute__, and __setattr__ for Lazy Attributes
    Things to Remember
    Item 33: Validate Subclasses with Metaclasses
    Things to Remember
    Item 34: Register Class Existence with Metaclasses
    Things to Remember
    Item 35: Annotate Class Attributes with Metaclasses
    Things to Remember
    5. Concurrency and Parallelism
    Item 36: Use subprocess to Manage Child Processes
    Things to Remember
    Item 37: Use Threads for Blocking I/O, Avoid for Parallelism
    Things to Remember
    Item 38: Use Lock to Prevent Data Races in Threads
    Things to Remember
    Item 39: Use Queue to Coordinate Work Between Threads
    Queue to the Rescue
    Things to Remember
    Item 40: Consider Coroutines to Run Many Functions Concurrently
    The Game of Life
    Coroutines in Python 2
    Things to Remember
    Item 41: Consider concurrent.futures for True Parallelism
    Things to Remember
    6. Built-in Modules
    Item 42: Define Function Decorators with functools.wraps
    Things to Remember
    Item 43: Consider contextlib and with Statements for Reusable try/finally Behavior
    Using with Targets
    Things to Remember
    Item 44: Make pickle Reliable with copyreg
    Default Attribute Values
    Versioning Classes
    Stable Import Paths
    Things to Remember
    Item 45: Use datetime Instead of time for Local Clocks
    The time Module
    The datetime Module
    Things to Remember
    Item 46: Use Built-in Algorithms and Data Structures
    Double-ended Queue
    Ordered Dictionary
    Default Dictionary
    Heap Queue
    Bisection
    Iterator Tools
    Things to Remember
    Item 47: Use decimal When Precision Is Paramount
    Things to Remember
    Item 48: Know Where to Find Community-Built Modules
    Things to Remember
    7. Collaboration
    Item 49: Write Docstrings for Every Function, Class, and Module
    Documenting Modules
    Documenting Classes
    Documenting Functions
    Things to Remember
    Item 50: Use Packages to Organize Modules and Provide Stable APIs
    Namespaces
    Stable APIs
    Things to Remember
    Item 51: Define a Root Exception to Insulate Callers from APIs
    Things to Remember
    Item 52: Know How to Break Circular Dependencies
    Reordering Imports
    Import, Configure, Run
    Dynamic Import
    Things to Remember
    Item 53: Use Virtual Environments for Isolated and Reproducible Dependencies
    The pyvenv Command
    Reproducing Dependencies
    Things to Remember
    8. Production
    Item 54: Consider Module-Scoped Code to Configure Deployment Environments
    Things to Remember
    Item 55: Use repr Strings for Debugging Output
    Things to Remember
    Item 56: Test Everything with unittest
    Things to Remember
    Item 57: Consider Interactive Debugging with pdb
    Things to Remember
    Item 58: Profile Before Optimizing
    Things to Remember
    Item 59: Use tracemalloc to Understand Memory Usage and Leaks
    Things to Remember
    Index
    Symbols
    A
    B
    C
    D
    E
    F
    G
    H
    I
    J
    K
    L
    M
    N
    O
    P
    Q
    R
    S
    T
    U
    V
    W
    Y
    Z
    Code Snippets
    About This eBook ePUB is an open, industry-standard format for eBooks. However, support of ePUB and its many features varies across reading devices and applications. Use your device or app settings to customize the presentation to your liking. Settings that you can customize often include font, font size, single or double column, landscape or portrait mode, and figures that you can click or tap to enlarge. For additional information about the settings and features on your reading device or app, visit the device manufacturer’s Web site. Many titles include programming code or configuration examples. To optimize the presentation of these elements, view the eBook in single- column, landscape mode and adjust the font size to the smallest setting. In addition to presenting code and configurations in the reflowable text format, we have included images of the code that mimic the presentation found in the print book; therefore, where the reflowable format may compromise the presentation of the code listing, you will see a “Click here to view code image” link. Click the link to view the print-fidelity code image. To return to the previous page viewed, click the Back button on your device or app.
    Effective Python 59 SPECIFIC WAYS TO WRITE BETTER PYTHON Brett Slatkin Upper Saddle River, NJ • Boston • Indianapolis • San Francisco New York • Toronto • Montreal • London • Munich • Paris • Madrid Capetown • Sydney • Tokyo • Singapore • Mexico City
    Many of the designations used by manufacturers and sellers to distinguish their products are claimed as trademarks. Where those designations appear in this book, and the publisher was aware of a trademark claim, the designations have been printed with initial capital letters or in all capitals. The author and publisher have taken care in the preparation of this book, but make no expressed or implied warranty of any kind and assume no responsibility for errors or omissions. No liability is assumed for incidental or consequential damages in connection with or arising out of the use of the information or programs contained herein. For information about buying this title in bulk quantities, or for special sales opportunities (which may include electronic versions; custom cover designs; and content particular to your business, training goals, marketing focus, or branding interests), please contact our corporate sales department at corpsales@pearsoned.com or (800) 382-3419. For government sales inquiries, please contact governmentsales@pearsoned.com. For questions about sales outside the United States, please contact international@pearsoned.com. Visit us on the Web: informit.com/aw Library of Congress Cataloging-in-Publication Data Slatkin, Brett, author. Effective Python : 59 specific ways to write better Python / Brett Slatkin. pages cm Includes index. ISBN 978-0-13-403428-7 (pbk. : alk. paper)—ISBN 0-13-403428-7 (pbk. : alk. paper) 1. Python (Computer program language) 2. Computer programming. I. Title. QA76.73.P98S57 2015 005.13’3—dc23 2014048305 Copyright © 2015 Pearson Education, Inc. All rights reserved. Printed in the United States of America. This publication is protected by copyright, and permission must be obtained from the publisher prior to any prohibited reproduction, storage in a retrieval system, or transmission in any form or by any means, electronic, mechanical, photocopying, recording, or likewise. To obtain permission to use material from this work, please submit a written request to Pearson Education, Inc., Permissions Department, One Lake Street, Upper Saddle River, New Jersey 07458, or you may fax your request to (201) 236-3290. ISBN-13: 978-0-13-403428-7 ISBN-10: 0-13-403428-7 Text printed in the United States on recycled paper at RR Donnelley in Crawfordsville, Indiana. First printing, March 2015 Editor-in-Chief Mark L. Taub Senior Acquisitions Editor Trina MacDonald Managing Editor John Fuller Full-Service Production Manager Julie B. Nahil Copy Editor Stephanie Geels Indexer Jack Lewis Proofreader Melissa Panagos Technical Reviewers Brett Cannon Tavis Rudd Mike Taylor Editorial Assistant Olivia Basegio Cover Designer Chuti Prasertsith Compositor LaurelTech
    Praise for “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 “I’ve been programming in Python for years and thought I knew it pretty well. Thanks to this treasure trove of tips and techniques, I realize there’s so much more I could be doing with my Python code to make it faster (e.g., using built-in data structures), easier to read (e.g., enforcing keyword- only arguments), and much more Pythonic (e.g., using zip to iterate over lists in parallel).” —Pamela Fox, educationeer, Khan Academy “If I had this book when I first switched from Java to Python, it would have saved me many months of repeated code rewrites, which happened each time I realized I was doing particular things ‘non-Pythonically.’ This book collects the vast majority of basic Python ‘must-knows’ into one place, eliminating the need to stumble upon them one-by-one over the course of months or years. The scope of the book is impressive, starting with the importance of PEP8 as well as that of major Python idioms, then reaching through function, method and class design, effective standard library use, quality API design, testing, and performance measurement—this book really has it all. A fantastic introduction to what it really means to be a Python programmer for both the novice and the experienced developer.” —Mike Bayer, creator of SQLAlchemy “Effective Python will take your Python skills to the next level with clear guidelines for improving Python code style and function.” —Leah Culver, developer advocate, Dropbox “This book is an exceptionally great resource for seasoned developers in other languages who are looking to quickly pick up Python and move beyond the basic language constructs into more Pythonic code. The organization of the book is clear, concise, and easy to digest, and each item and chapter can stand on its own as a meditation on a particular topic. The book covers the breadth of language constructs in pure Python without confusing the reader with the complexities of the broader Python ecosystem. For more seasoned developers the book provides in-depth examples of language constructs they may not have previously encountered, and provides examples of less commonly used language features. It is clear that the author is exceptionally facile with Python, and he uses his professional experience to alert the reader to common subtle bugs and common failure modes. Furthermore, the book does an excellent job of pointing out subtleties between Python 2.X and Python 3.X and could serve as a refresher course as one transitions between variants of Python.” —Katherine Scott, software lead, Tempo Automation “This is a great book for both novice and experienced programmers. The code examples and explanations are well thought out and explained concisely and thoroughly.” —C. Titus Brown, associate professor, UC Davis “This is an immensely useful resource for advanced Python usage and building cleaner, more maintainable software. Anyone looking to take their Python skills to the next level would benefit from putting the book’s advice into practice.” —Wes McKinney, creator of pandas; author of Python for Data Analysis; and software engineer at Cloudera
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