Static code analysis tools can provide a rich summary of information on the static properties of your code, which can provide insights into aspects like complexity and modifiability/readability of the code.
Python has a lot of third-party tool support, which helps in measuring the static aspects of Python code such as these:
Conformance to coding standards like PEP-8
Code complexity metrics like the McCabe metric
Errors in code such as syntax errors, indentation issues, missing imports, variable overwrites, and others
Logic issues in code
Code smells
The following are some of the most popular tools in the Python ecosystem which can perform such static analysis:
Pylint: Pylint is a static checker for Python code, which can detect a range of coding errors, code smells, and style errors. Pylint uses a style close to PEP-8. The newer versions of Pylint also provide statistics about code complexity, and can print reports. Pylint requires the code to be executed before...