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rubik / radon

Various code metrics for Python code
http://radon.readthedocs.org/
MIT License
1.72k stars 115 forks source link
cli code-analysis python quality-assurance static-analysis

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Radon

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Radon is a Python tool that computes various metrics from the source code. Radon can compute:

Requirements

Radon will run from Python 2.7 to Python 3.10 (except Python versions from 3.0 to 3.3) with a single code base and without the need of tools like 2to3 or six. It can also run on PyPy without any problems (currently PyPy 3.5 v7.3.1 is used in tests).

Radon depends on as few packages as possible. Currently only mando is strictly required (for the CLI interface). colorama is also listed as a dependency but if Radon cannot import it, the output simply will not be colored.

Note: Python 2.6 was supported until version 1.5.0. Starting from version 2.0, it is not supported anymore.

Installation

With Pip:

.. code-block:: sh

$ pip install radon

If you want to configure Radon from pyproject.toml and you run Python <3.11, you'll need the extra toml dependency:

.. code-block:: sh

$ pip install radon[toml]

Or download the source and run the setup file:

.. code-block:: sh

$ python setup.py install

Usage

Radon can be used either from the command line or programmatically. Documentation is at https://radon.readthedocs.org/.

Cyclomatic Complexity Example

Quick example:

.. code-block:: sh

$ radon cc sympy/solvers/solvers.py -a -nc
sympy/solvers/solvers.py
    F 346:0 solve - F
    F 1093:0 _solve - F
    F 1434:0 _solve_system - F
    F 2647:0 unrad - F
    F 110:0 checksol - F
    F 2238:0 _tsolve - F
    F 2482:0 _invert - F
    F 1862:0 solve_linear_system - E
    F 1781:0 minsolve_linear_system - D
    F 1636:0 solve_linear - D
    F 2382:0 nsolve - C

11 blocks (classes, functions, methods) analyzed.
Average complexity: F (61.0)

Explanation:

Actually it's even better: it's got colors!

.. image:: https://cloud.githubusercontent.com/assets/238549/3707477/5793aeaa-1435-11e4-98fb-00e0bd8137f5.png :alt: A screen of Radon's cc command

Note about file encoding

On some systems, such as Windows, the default encoding is not UTF-8. If you are using Unicode characters in your Python file and want to analyze it with Radon, you'll have to set the RADONFILESENCODING environment variable to UTF-8.

On a Continuous Integration server

If you are looking to use radon on a CI server you may be better off with xenon <https://github.com/rubik/xenon>_. Although still experimental, it will fail (that means exiting with a non-zero exit code) when various thresholds are surpassed. radon is more of a reporting tool, while xenon is a monitoring one.

If you are looking for more complete solutions, read the following sections.

Codacy ++++++++++++

Codacy <https://www.codacy.com/> uses Radon by default <https://support.codacy.com/hc/en-us/articles/213632009-Engines#other-tools> to calculate metrics from the source code.

Code Climate ++++++++++++

Radon is available as a Code Climate Engine <https://docs.codeclimate.com/docs/list-of-engines>_. To understand how to add Radon's checks to your Code Climate Platform, head over to their documentation: https://docs.codeclimate.com/v1.0/docs/radon

coala Analyzer ++++++++++++++

Radon is also supported in coala <http://coala.io/>_. To add Radon's checks to coala, simply add the RadonBear to one of the sections in your .coafile.

CodeFactor ++++++++++++

CodeFactor <https://www.codefactor.io/> uses Radon out-of-the-box <https://support.codefactor.io/i24-analysis-tools-open-source> to calculate Cyclomatic Complexity.

Usage with Jupyter Notebooks

Radon can be used with .ipynb files to inspect code metrics for Python cells. Any % macros will be ignored in the metrics.

.. note::

Jupyter Notebook support requires the optional nbformat package. To install, run pip install nbformat.

To enable scanning of Jupyter notebooks, add the --include-ipynb flag.

To enable reporting of individual cells, add the --ipynb-cells flag.

Quick example:

.. code-block:: sh

$ radon raw --include-ipynb --ipynb-cells .
example.ipynb
    LOC: 63
    LLOC: 37
    SLOC: 37
    Comments: 3
    Single comments: 2
    Multi: 10
    Blank: 14
    - Comment Stats
        (C % L): 5%
        (C % S): 8%
        (C + M % L): 21%
example.ipynb:[0]
    LOC: 0
    LLOC: 0
    SLOC: 0
    Comments: 0
    Single comments: 0
    Multi: 0
    Blank: 0
    - Comment Stats
        (C % L): 0%
        (C % S): 0%
        (C + M % L): 0%
example.ipynb:[1]
    LOC: 2
    LLOC: 2
    SLOC: 2
    Comments: 0
    Single comments: 0
    Multi: 0
    Blank: 0
    - Comment Stats
        (C % L): 0%
        (C % S): 0%
        (C + M % L): 0%

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