complexipy

An extremely fast Python library to calculate the cognitive complexity of python files, written in Rust.

Documentation: https://rohaquinlop.github.io/complexipy/

Source Code: https://github.com/rohaquinlop/complexipy

PyPI: https://pypi.org/project/complexipy/

Requirements

Python >= 3.11
You also need to install git in your computer if you want to analyze a git repository.

Installation

pip install complexipy

Usage

To run complexipy you can use the following command:

complexipy .                         # Use complexipy to analyze the current directory and any subdirectories
complexipy path/to/directory         # Use complexipy to analyze a specific directory and any subdirectories
complexipy git_repository_url        # Use complexipy to analyze a git repository
complexipy path/to/file.py           # Use complexipy to analyze a specific file
complexipy path/to/file.py -c 20     # Use the -c option to set the maximum congnitive complexity, default is 15
complexipy path/to/directory -c 0    # Set the maximum cognitive complexity to 0 to disable the exit with error
complexipy path/to/directory -o      # Use the -o option to output the results to a CSV file, default is False
complexipy path/to/directory -d low  # Use the -d option to set detail level, default is "normal". If set to "low" will show only files with complexity greater than the maximum complexity

If the cognitive complexity of a file is greater than the maximum cognitive, then the return code will be 1 and exit with error, otherwise it will be 0.

Example

Analyzing a file

For example, given the following file:

def a_decorator(a, b):
    def inner(func):
        return func
    return inner

def b_decorator(a, b):
    def inner(func):
        if func:
            return None
        return func
    return inner

The cognitive complexity of the file is 1, and the output of the command complexipy path/to/file.py will be:

─────────────────────── complexipy 0.2.2 🐙 ───────────────────────
- Finished analysis in test_decorator.py
──────────────────── 🎉 Analysis completed!🎉 ─────────────────────
                       Summary
┏━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━┓
┃ Path              ┃ File              ┃ Complexity ┃
┡━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━┩
│ test_decorator.py │ test_decorator.py │ 1          │
└───────────────────┴───────────────────┴────────────┘
🧠 Total Cognitive Complexity in ./tests/test_decorator.py: 1
1 files analyzed in 0.0005 seconds

Output to a CSV file

If you want to output the results to a CSV file, you can use the -o option, this is really useful if you want to integrate complexipy with other tools, for example, a CI/CD pipeline. You will get the output in the console and will create a CSV file with the results of the analysis.

The filename will be complexipy.csv and will be saved in the current directory.

$ complexipy path/to/file.py -o

The output will be:

Path,File Name,Cognitive Complexity
test_decorator.py,test_decorator.py,1

Analyzing a directory

You can also analyze a directory, for example:

$ complexipy .

And complexipy will analyze all the files in the current directory and any subdirectories.

Analyzing a git repository

You can also analyze a git repository, for example:

$ complexipy https://github.com/rohaquinlop/complexipy

And to generate the output to a CSV file:

$ complexipy https://github.com/rohaquinlop/complexipy -o

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

Thanks to G. Ann Campbell for publishing the paper "Cognitive Complexity a new way to measure understandability".
This project is inspired by the Sonar way to calculate the cognitive complexity.

References

Cognitive Complexity

korneevm / complexipy