Clean Code in Python - Second Edition

Table of contents

1. Preface
   1. Who this book is for?
   2. What this book covers
   3. To get the most out of this book
      1. Download the example code files
      2. Download the color images
      3. Conventions used
   4. Get in touch
      1. Reviews
2. Introduction, Code Formatting, and Tools
   1. Introduction
      1. The meaning of clean code
      2. The importance of having clean code
      3. Some exceptions
   2. Code formatting
      1. Adhering to a coding style guide on your project
   3. Documentation
      1. Code comments
      2. Docstrings
      3. Annotations
      4. Do annotations replace docstrings?
   4. Tooling
      1. Checking type consistency
      2. Generic validations in code
      3. Automatic formatting
      4. Setup for automatic checks
   5. Summary
   6. References
3. Pythonic Code
   1. Indexes and slices
      1. Creating your own sequences
   2. Context managers
      1. Implementing context managers
   3. Comprehensions and assignment expressions
   4. Properties, attributes, and different types of methods for objects
      1. Underscores in Python
      2. Properties
      3. Creating classes with a more compact syntax
      4. Iterable objects
         1. Creating iterable objects
         2. Creating sequences
      5. Container objects
      6. Dynamic attributes for objects
      7. Callable objects
      8. Summary of magic methods
   5. Caveats in Python
      1. Mutable default arguments
      2. Extending built-in types
   6. A brief introduction to asynchronous code
   7. Summary
   8. References
4. General Traits of Good Code
   1. Design by contract
      1. Preconditions
      2. Postconditions
      3. Pythonic contracts
      4. Design by contract – conclusions
   2. Defensive programming
      1. Error handling
         1. Value substitution
         2. Exception handling
      2. Using assertions in Python
   3. Separation of concerns
      1. Cohesion and coupling
   4. Acronyms to live by
      1. DRY/OAOO
      2. YAGNI
      3. KIS
      4. EAFP/LBYL
   5. Inheritance in Python
      1. When inheritance is a good decision
      2. Anti-patterns for inheritance
      3. Multiple inheritance in Python
         1. Method Resolution Order (MRO)
         2. Mixins
   6. Arguments in functions and methods
      1. How function arguments work in Python
         1. How arguments are copied to functions
         2. Variable number of arguments
         3. Positional-only parameters
         4. Keyword-only arguments
      2. The number of arguments in functions
         1. Function arguments and coupling
         2. Compact function signatures that take too many arguments
   7. Final remarks on good practices for software design
      1. Orthogonality in software
      2. Structuring the code
   8. Summary
   9. References
5. The SOLID Principles
   1. The single responsibility principle
      1. A class with too many responsibilities
      2. Distributing responsibilities
   2. The open/closed principle
      1. Example of maintainability perils for not following the OCP
      2. Refactoring the events system for extensibility
      3. Extending the events system
      4. Final thoughts about the OCP
   3. Liskov's substitution principle
      1. Detecting LSP issues with tools
         1. Using mypy to detect incorrect method signatures
         2. Detecting incompatible signatures with pylint
      2. More subtle cases of LSP violations
      3. Remarks on the LSP
   4. Interface segregation
      1. An interface that provides too much
      2. The smaller the interface, the better
      3. How small should an interface be?
   5. Dependency inversion
      1. A case of rigid dependencies
      2. Inverting the dependencies
      3. Dependency injection
   6. Summary
   7. References
6. Using Decorators to Improve Our Code
   1. What are decorators in Python?
      1. Function decorators
      2. Decorators for classes
      3. Other types of decorator
   2. More advanced decorators
      1. Passing arguments to decorators
         1. Decorators with nested functions
         2. Decorator objects
      2. Decorators with default values
      3. Decorators for coroutines
      4. Extended syntax for decorators
   3. Good uses for decorators
      1. Adapting function signatures
      2. Validating parameters
      3. Tracing code
   4. Effective decorators – avoiding common mistakes
      1. Preserving data about the original wrapped object
      2. Dealing with side effects in decorators
         1. Incorrect handling of side effects in a decorator
         2. Requiring decorators with side effects
      3. Creating decorators that will always work
   5. Decorators and clean code
      1. Composition over inheritance
      2. The DRY principle with decorators
      3. Decorators and separation of concerns
      4. Analysis of good decorators
   6. Summary
   7. References
7. Getting More Out of Our Objects with Descriptors
   1. A first look at descriptors
      1. The machinery behind descriptors
      2. Exploring each method of the descriptor protocol
         1. The get method
         2. The set method
         3. The delete method
         4. The set name method
   2. Types of descriptors
      1. Non-data descriptors
      2. Data descriptors
   3. Descriptors in action
      1. An application of descriptors
         1. A first attempt without using descriptors
         2. The idiomatic implementation
      2. Different forms of implementing descriptors
         1. The issue of shared state
         2. Accessing the dictionary of the object
         3. Using weak references
      3. More considerations about descriptors
         1. Reusing code
         2. An alternative to class decorators
   4. Analysis of descriptors
      1. How Python uses descriptors internally
         1. Functions and methods
         2. Built-in decorators for methods
         3. Slots
      2. Implementing descriptors in decorators
   5. Final remarks about descriptors
      1. Interface of descriptors
      2. Object-oriented design of the descriptors
      3. Type annotations on descriptors
   6. Summary
   7. References
8. Generators, Iterators, and Asynchronous Programming
   1. Technical requirements
   2. Creating generators
      1. A first look at generators
      2. Generator expressions
   3. Iterating idiomatically
      1. Idioms for iteration
         1. The next() function
         2. Using a generator
         3. Itertools
         4. Simplifying code through iterators
         5. The iterator pattern in Python
   4. Coroutines
      1. The methods of the generator interface
         1. close()
         2. throw(ex_type[, ex_value[, ex_traceback]])
         3. send(value)
      2. More advanced coroutines
         1. Returning values in coroutines
         2. Delegating into smaller coroutines – the 'yield from' syntax
   5. Asynchronous programming
      1. Magic asynchronous methods
         1. Asynchronous context managers
         2. Other magic methods
      2. Asynchronous iteration
      3. Asynchronous generators
   6. Summary
   7. References
9. Unit Testing and Refactoring
   1. Design principles and unit testing
      1. A note about other forms of automated testing
      2. Unit testing and agile software development
      3. Unit testing and software design
      4. Defining the boundaries of what to test
   2. Tools for testing
      1. Frameworks and libraries for unit testing
         1. unittest
         2. pytest
         3. Code coverage
         4. Mock objects
   3. Refactoring
      1. Evolving our code
      2. Production code isn't the only one that evolves
   4. More about testing
      1. Property-based testing
      2. Mutation testing
      3. Common themes in testing
         1. Boundaries or limit values
         2. Classes of equivalence
         3. Edge cases
      4. A brief introduction to test-driven development
   5. Summary
   6. References
10. Common Design Patterns
    1. Design pattern considerations in Python
    2. Design patterns in action
       1. Creational patterns
          1. Factories
          2. Singleton and shared state (monostate)
          3. Builder
       2. Structural patterns
          1. Adapter
          2. Composite
          3. Decorator
          4. Facade
       3. Behavioral patterns
          1. Chain of responsibility
          2. The template method
          3. Command
          4. State
    3. The null object pattern
    4. Final thoughts about design patterns
       1. The influence of patterns over the design
       2. Design patterns as theory
       3. Names in our models
    5. Summary
    6. References
11. Clean Architecture
    1. From clean code to clean architecture
       1. Separation of concerns
       2. Monolithic applications and microservices
       3. Abstractions
    2. Software components
       1. Packages
          1. Managing dependencies
          2. Other considerations when managing dependencies
          3. Artifact versions
       2. Docker containers
       3. Use case
          1. The code
          2. Domain models
          3. Calling from the application
          4. Adapters
       4. The services
          1. Analysis
          2. The dependency flow
          3. Limitations
          4. Testability
          5. Intention revealing
    3. Summary
    4. References
    5. Summing it all up
12. Other Books You May Enjoy
13. Index