How can I analyze Python code to identify problematic areas?
PythonStatic AnalysisCyclomatic ComplexityPython Problem Overview
I have a large source repository split across multiple projects. I would like to produce a report about the health of the source code, identifying problem areas that need to be addressed.
Specifically, I'd like to call out routines with a high cyclomatic complexity, identify repetition, and perhaps run some lint-like static analysis to spot suspicious (and thus likely erroneous) constructs.
How might I go about constructing such a report?
Python Solutions
Solution 1 - Python
For measuring cyclomatic complexity, there's a nice tool available at traceback.org. The page also gives a good overview of how to interpret the results.
+1 for pylint. It is great at verifying adherence to coding standards (be it PEP8 or your own organization's variant), which can in the end help to reduce cyclomatic complexity.
Solution 2 - Python
For cyclomatic complexity you can use radon: https://github.com/rubik/radon
(Use pip to install it: pip install radon)
Additionally it also has these features:
- raw metrics (these include SLOC, comment lines, blank lines, &c.)
- Halstead metrics (all of them)
- Maintainability Index (the one used in Visual Studio)
Solution 3 - Python
For static analysis there is pylint and pychecker. Personally I use pylint as it seems to be more comprehensive than pychecker.
For cyclomatic complexity you can try this perl program, or this article which introduces a python program to do the same
Solution 4 - Python
Pycana works like charm when you need to understand a new project! > PyCAna (Python Code Analyzer) is > a fancy name for a simple code > analyzer for python that creates a > class diagram after executing your > code.
See how it works: http://pycana.sourceforge.net/
output:
Solution 5 - Python
Thanks to Pydev, you can integrate pylint in the Eclipse IDE really easily and get a code report each time you save a modified file.
Solution 6 - Python
Use flake8, which provides pep8, pyflakes, and cyclomatic complexity analysis in one tool
Solution 7 - Python
There is a tool called CloneDigger that helps you find similar code snippets.
Solution 8 - Python
For checking cyclomatic complexity, there is of course the mccabe package.
Installation:
$ pip install --upgrade mccabe
Usage:
$ python -m mccabe --min=6 path/to/myfile.py
Note the threshold of 6 above. Per this answer, scores >5 probably should be simplified.
Sample output with --min=3:
68:1: 'Fetcher.fetch' 3
48:1: 'Fetcher._read_dom_tag' 3
103:1: 'main' 3
It can optionally also be used via pylint-mccabe or pytest-mccabe, etc.