Python Development Tools

[ad_1]

The modules described in this chapter help you write software. For example, the pydoc module takes a module and generates documentation based on the module’s contents. The doctest and unittest modules contains frameworks for writing unit tests that automatically exercise code and verify that the expected output is produced. 2to3 can translate Python 2.x source code into valid Python 3.x code.

The list of modules described in this chapter is:

  • typing — Support for type hints
    • Type aliases
    • NewType
    • Callable
    • Generics
    • User-defined generic types
    • The Any type
    • Nominal vs structural subtyping
    • Classes, functions, and decorators
  • pydoc — Documentation generator and online help system
  • doctest — Test interactive Python examples
    • Simple Usage: Checking Examples in Docstrings
    • Simple Usage: Checking Examples in a Text File
    • How It Works
      • Which Docstrings Are Examined?
      • How are Docstring Examples Recognized?
      • What’s the Execution Context?
      • What About Exceptions?
      • Option Flags
      • Directives
      • Warnings
    • Basic API
    • Unittest API
    • Advanced API
      • DocTest Objects
      • Example Objects
      • DocTestFinder objects
      • DocTestParser objects
      • DocTestRunner objects
      • OutputChecker objects
    • Debugging
    • Soapbox
  • unittest — Unit testing framework
    • Basic example
    • Command-Line Interface
      • Command-line options
    • Test Discovery
    • Organizing test code
    • Re-using old test code
    • Skipping tests and expected failures
    • Distinguishing test iterations using subtests
    • Classes and functions
      • Test cases
        • Deprecated aliases
      • Grouping tests
      • Loading and running tests
        • load_tests Protocol
    • Class and Module Fixtures
      • setUpClass and tearDownClass
      • setUpModule and tearDownModule
    • Signal Handling
  • unittest.mock — mock object library
    • Quick Guide
    • The Mock Class
      • Calling
      • Deleting Attributes
      • Mock names and the name attribute
      • Attaching Mocks as Attributes
    • The patchers
      • patch
      • patch.object
      • patch.dict
      • patch.multiple
      • patch methods: start and stop
      • patch builtins
      • TEST_PREFIX
      • Nesting Patch Decorators
      • Where to patch
      • Patching Descriptors and Proxy Objects
    • MagicMock and magic method support
      • Mocking Magic Methods
      • Magic Mock
    • Helpers
      • sentinel
      • DEFAULT
      • call
      • create_autospec
      • ANY
      • FILTER_DIR
      • mock_open
      • Autospeccing
      • Sealing mocks
  • unittest.mock — getting started
    • Using Mock
      • Mock Patching Methods
      • Mock for Method Calls on an Object
      • Mocking Classes
      • Naming your mocks
      • Tracking all Calls
      • Setting Return Values and Attributes
      • Raising exceptions with mocks
      • Side effect functions and iterables
      • Mocking asynchronous iterators
      • Mocking asynchronous context manager
      • Creating a Mock from an Existing Object
    • Patch Decorators
    • Further Examples
      • Mocking chained calls
      • Partial mocking
      • Mocking a Generator Method
      • Applying the same patch to every test method
      • Mocking Unbound Methods
      • Checking multiple calls with mock
      • Coping with mutable arguments
      • Nesting Patches
      • Mocking a dictionary with MagicMock
      • Mock subclasses and their attributes
      • Mocking imports with patch.dict
      • Tracking order of calls and less verbose call assertions
      • More complex argument matching
  • 2to3 – Automated Python 2 to 3 code translation
    • Using 2to3
    • Fixers
    • lib2to3 – 2to3’s library
  • test — Regression tests package for Python
    • Writing Unit Tests for the test package
    • Running tests using the command-line interface
  • test.support — Utilities for the Python test suite
  • test.support.script_helper — Utilities for the Python execution tests

All the development tools mentioned above are explain in great detail as individual course on the platform. To know more about any of these tools, simply search for them in our education section.

This article has been published from the source link without modifications to the text. Only the headline has been changed.

[ad_2]

 

Most Popular