How can I analyze Python code to identify problematic areas?

Solution 1:

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:

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:

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:

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:

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Solution 5:

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.