Module 3: Mastering Python

• chapter 1: Getting Started – One Environment per Project
  • 1.1 Creating a virtual Python environment using venv
    • 1.1.1 Linux
  • 1.2 Bootstrapping pip using ensurepip
  • 1.3 Installing C/C++ packages
  • 1.4 Summary
• chapter 2: Pythonic Syntax, Common Pitfalls, and Style Guide
  • 2.1 ode style – or what is Pythonic code?
    • 2.1.1 Linux
  • 2.2 Common pitfalls
  • 2.3 Summary
• chapter 3: Containers and Collections – Storing Data the Right Way
  • 3.1 Time complexity – the big O notation
    • 3.1.1 Linux
  • 3.2 Core collections
  • 3.3 Advanced collections
  • 3.4 Summary
• chapter 4: Functional Programming – Readability Versus Brevity
  • 4.1 Functional programming
    • 4.1.1 Linux
  • 4.2 list comprehensions
  • 4.3 dict comprehensions
  • 4.4 set comprehensions
  • 4.5 lambda functions
  • 4.6 functools
  • 4.7 itertools
  • 4.8 Summary
• chapter 5: Decorators – Enabling Code Reuse by Decorating
  • 5.1 Decorating functions
    • 5.1.1 Linux
  • 5.2 Decorating class functions
  • 5.3 Decorating classes
  • 5.4 Useful decorators
  • 5.5 Summary
• chapter 6: Generators and Coroutines – Infinity, One Step at a Time
  • 6.1 What are generators?
    • 6.1.1 Linux
  • 6.2 Coroutines
  • 6.3 Summary
• chapter 7: Async IO – Multithreading without Threads
  • 7.1 Introducing the asyncio library
    • 7.1.1 Linux
  • 7.2 Summary
• chapter 8: Metaclasses – Making Classes (Not Instances) Smarter
  • 8.1 Dynamically creating classes
    • 8.1.1 Linux
  • 8.2 Abstract classes using collections.abc
  • 8.3 Automatically registering a plugin system
  • 8.4 Order of operations when instantiating classes
  • 8.5 Storing class attributes in definition order
  • 8.6 Summary
• chapter 9: Documentation – How to Use Sphinx and reStructuredText
  • 9.1 The reStructuredText syntax
    • 9.1.1 Linux
  • 9.2 The Sphinx documentation generator
  • 9.3 Documenting code
  • 9.4 Summary
• chapter 10: Testing and Logging – Preparing for Bugs
  • 10.1 Using examples as tests with doctest
    • 10.1.1 Linux
  • 10.2 Testing with py.test
  • 10.3 Mock objects
  • 10.4 Logging
  • 10.5 Summary
• chapter 11: Debugging – Solving the Bugs
  • 11.1 Non-interactive debugging
    • 11.1.1 Linux
  • 11.2 Interactive debugging
  • 11.3 Summary
• chapter 12: Performance – Tracking and Reducing Your Memory and CPU Usage
  • 12.1 What is performance?
    • 12.1.1 Linux
  • 12.2 Timeit – comparing code snippet performance
  • 12.3 cProfile – finding the slowest components
  • 12.4 Line profiler
  • 12.5 Improving performance
  • 12.6 Memory usage
  • 12.7 Performance monitoring
  • 12.8 Summary
• chapter 13: Multiprocessing – When a Single CPU Core Is Not Enough
  • 13.1 Multithreading versus multiprocessing
    • 13.1.1 Linux
  • 13.2 Hyper-threading versus physical CPU cores
  • 13.3 Creating a pool of workers
  • 13.4 Sharing data between processes
  • 13.5 Remote processes
  • 13.6 Summary
• chapter 14: Extensions in C/C++, System Calls, and C/C++ Libraries
  • 14.1 Introduction
    • 14.1.1 Linux
  • 14.2 Calling C/C++ with ctypes
  • 14.3 CFFI
  • 14.4 Native C/C++ extensions
  • 14.5 Summary
• chapter 15: Packaging – Creating Your Own Libraries or Applications
  • 15.1 Installing packages
    • 15.1.1 Linux
  • 15.2 Setup parameters
  • 15.3 Packages
  • 15.4 Entry points
  • 15.5 Package data
  • 15.6 Testing packages
  • 15.7 C/C++ extensions
  • 15.8 Wheels – the new eggs
  • 15.9 Summary