This section covers python coding style guidelines followed.
PEP8 covers python code style guide and helps to maintain consistency in code.
A style guide is about consistency. Consistency within a project or module or
function is most important.
Complete specification available at
https://www.python.org/dev/peps/pep-0008/
PEP257 covers semantics and conventions associated with python docstrings.
The aim of PEP257 to standardize the high-level structure of docstrings.
Complete specification available at
https://www.python.org/dev/peps/pep-0257/
PEP484 introduces a provisional module to provide the standard definitions
and tools, along with some conventions for situations where
annotations are not available. More details on PEP484 available at
https://www.python.org/dev/peps/pep-0484/
Flake8 is a Python library wrapper around PyFlakes, pycodestyle and
Ned Batchelder’s McCabe script
PyFlakes:
- A simple program that checks Python source files for errors.
- It is available on PyPI https://pypi.org/project/pyflakes/
Pydcodestyle:
Pycodestyleused to called pep8 is a tool to check your Python code against some of the style conventions in PEP8.- It is available on PyPI https://pypi.org/project/pycodestyle/
McCabe:
- Ned’s script to check for the
McCabecomplexity for Python code. - It is available on PyPI https://pypi.org/project/mccabe/
It is important to validate the classes, methods, and functions we write.
This will help to miniate the core software functionality of the modules.
This is possible by writing a unit test which is the first level of
software functionality validation. The pytest framework helps to
write small test, yet scales to support complex functional testing
for applications and libraries.
Complete features and documentation available at: https://docs.pytest.org/en/latest/contents.html
The mypy tool aims to combine the benefits of dynamic and static typing.
mypy combines a powerful type system and compile-time type checking.
It is an optional static type checker for python.
Mypy type checks standard Python programs; run them using any Python VM
with basically no runtime overhead. More details available at
https://mypy.readthedocs.io/en/stable/