Python Tools To Write Better Code

Overview

Python community maintains a set of tools that are helpful in every project. They provide quick feedback of your code health and how much it sticks to standards and better practices.

These tools are:

pep8

style checker

pyflakes

checks source code for errors

mccabe

complexity checker

flake8

code checker (pep8, pyflakes, mccabe, and third-party plugins to check the style and quality of some python code)

Pylint

Checks for coding standards, errors and duplicated code.

Coverage

measure effectiveness of tests

Black

The uncompromising Python code formatter

Tools

Python code style (Pep8)

It was formerly called pep8 and it checks Python coding style conventions defined in PEP8.

Project homepage: https://github.com/PyCQA/pycodestyle

It is based in PEP8 style conventions (http://www.python.org/dev/peps/pep-0008/).

The guidelines provided here are intended to improve the readability of code and make it consistent across the wide spectrum of Python code. As PEP 20 says, "Readability counts". A style guide is about consistency. Consistency with this style guide is important. Consistency within a project is more important. Consistency within one module or function is the most important.

McCabe

McCabe is a complexity checker for Python.

Project homepage: https://github.com/PyCQA/mccabe

It is based in the Cyclomatic complexity concept.

Cyclomatic complexity is a software metric (measurement), used to indicate the complexity of a program. It is a quantitative measure of the number of linearly independent paths through a program's source code. It was developed by Thomas J. McCabe, Sr. in 1976.

It is useful for:

• Measuring how much a program is structured
• Determining the number of test cases that are necessary to achieve thorough test coverage of a particular module
• Limiting complexity during development
  • Functions and methods that have the highest complexity tend to also contain the most defects.
• Measure modules cohesion through the analysis of its complexity.

Error checks: Pyflakes

It checks Python source files for errors by parsing source code.

Project homepage: https://github.com/PyCQA/pyflakes

All together: Flake8

Project Homepage: https://gitlab.com/pycqa/flake8

Flake8 runs all the above tools with the flake8 command.

Pylint

Project Homepage: https://www.pylint.org/

Python static code analysis tool with the following features:

• looks for programming errors
• helps enforcing a coding standard
• sniffs for code smells
• offers simple refactoring suggestions.

pip3 install –user pylint

Black

Automatically adjust code formatting using https://github.com/psf/black

Code Coverage

It measures code coverage of Python projects.

Project Homepage: http://coverage.readthedocs.io/en/latest/

It monitors your program, noting which parts of the code have been executed, then analyzes the source to identify code that could have been executed but was not.

Coverage measurement is typically used to gauge the effectiveness of tests. It can show which parts of your code are being exercised by tests, and which are not.

References

• https://mail.python.org/mailman/listinfo/code-quality/
• https://en.wikipedia.org/wiki/Cyclomatic_complexity