如何分析 Python 代码以识别有问题的区域？

我有一个跨多个项目的大型源代码存储库。我想生成一个关于源代码健康状况的报告，确定需要解决的问题领域。

具体来说，我希望调出具有高循环复杂度的例程，识别重复，或者运行一些 lint-like 静态分析来发现可疑的(因此可能是错误的)结构。

我该如何着手编写这样一份报告呢？

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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

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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.

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最佳答案

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.

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There is a tool called CloneDigger that helps you find similar code snippets.

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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:

alt text

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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)
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Use flake8, which provides pep8, pyflakes, and cyclomatic complexity analysis in one tool

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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.


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