Serious Python

Table of contents

1. Cover Page
2. Title Page
3. Copyright Page
4. About the Author
5. About the Technical Reviewer
6. BRIEF CONTENTS
7. CONTENTS IN DETAIL
8. ACKNOWLEDGMENTS
9. INTRODUCTION
   1. Who Should Read This Book and Why
   2. About This Book
10. 1 STARTING YOUR PROJECT
    1. Versions of Python
    2. Laying Out Your Project
    3. Version Numbering
    4. Coding Style and Automated Checks
    5. Joshua Harlow on Python
11. 2 MODULES, LIBRARIES, AND FRAMEWORKS
    1. The Import System
    2. Useful Standard Libraries
    3. External Libraries
    4. Package Installation: Getting More from pip
    5. Using and Choosing Frameworks
    6. Doug Hellmann, Python Core Developer, on Python Libraries
12. 3 DOCUMENTATION AND GOOD API PRACTICE
    1. Documenting with Sphinx
    2. Summary
    3. Christophe de Vienne on Developing APIs
13. 4 HANDLING TIMESTAMPS AND TIME ZONES
    1. The Problem of Missing Time Zones
    2. Building Default datetime Objects
    3. Time Zone–Aware Timestamps with dateutil
    4. Serializing Time Zone–Aware datetime Objects
    5. Solving Ambiguous Times
    6. Summary
14. 5 DISTRIBUTING YOUR SOFTWARE
    1. A Bit of setup.py History
    2. Packaging with setup.cfg
    3. The Wheel Format Distribution Standard
    4. Sharing Your Work with the World
    5. Entry Points
    6. Summary
    7. Nick Coghlan on Packaging
15. 6 UNIT TESTING
    1. The Basics of Testing
    2. Virtual Environments
    3. Testing Policy
    4. Robert Collins on Testing
16. 7 METHODS AND DECORATORS
    1. Decorators and When to Use Them
    2. How Methods Work in Python
    3. Static Methods
    4. Class Methods
    5. Abstract Methods
    6. Mixing Static, Class, and Abstract Methods
    7. Summary
17. 8 FUNCTIONAL PROGRAMMING
    1. Creating Pure Functions
    2. Generators
    3. List Comprehensions
    4. Functional Functions Functioning
    5. Summary
18. 9 THE ABSTRACT SYNTAX TREE, HY, AND LISP-LIKE ATTRIBUTES
    1. Looking at the AST
    2. Extending flake8 with AST Checks
    3. A Quick Introduction to Hy
    4. Summary
    5. Paul Tagliamonte on the AST and Hy
19. 10 PERFORMANCES AND OPTIMIZATIONS
    1. Data Structures
    2. Understanding Behavior Through Profiling
    3. Defining Functions Efficiently
    4. Ordered Lists and bisect
    5. namedtuple and Slots
    6. Memoization
    7. Faster Python with PyPy
    8. Achieving Zero Copy with the Buffer Protocol
    9. Summary
    10. Victor Stinner on Optimization
20. 11 SCALING AND ARCHITECTURE
    1. Multithreading in Python and Its Limitations
    2. Multiprocessing vs. Multithreading
    3. Event-Driven Architecture
    4. Other Options and asyncio
    5. Service-Oriented Architecture
    6. Interprocess Communication with ZeroMQ
    7. Summary
21. 12 MANAGING RELATIONAL DATABASES
    1. RDBMSs, ORMs, and When to Use Them
    2. Database Backends
    3. Streaming Data with Flask and PostgreSQL
    4. Dimitri Fontaine on Databases
22. 13 WRITE LESS, CODE MORE
    1. Using six for Python 2 and 3 Support
    2. Using Python Like Lisp to Make a Single Dispatcher
    3. Context Managers
    4. Less Boilerplate with attr
    5. Summary
23. INDEX