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?
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.
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
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.
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.