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Utility for examining python source files to ensure proper documentation. Lists missing docstrings, and calculates overall docstring coverage percentage rating

Project description

Docstr-Coverage

If the health of your documentation is in dire straits, docstr-coverage will see you now.

docstr-coverage is a simple tool that lets you measure your Python source code's docstring coverage. It can show you which of your functions, classes, methods, and modules don't have docstrings. It also provide statistics about overall docstring coverage for individual files, and for your entire project.

Example

>>> HunterMcGushion$ docstr-coverage /docstr_coverage/

File: "docstr_coverage/setup.py"
 - No module docstring
 - No docstring for `readme`
 Needed: 2; Found: 0; Missing: 2; Coverage: 0.0%

File: "docstr_coverage/docstr_coverage/__init__.py"
 - No module docstring
 Needed: 1; Found: 0; Missing: 1; Coverage: 0.0%

File: "docstr_coverage/docstr_coverage/coverage.py"
 - No docstring for `DocStringCoverageVisitor.__init__`
 Needed: 11; Found: 10; Missing: 1; Coverage: 90.9%


Overall statistics for 3 files:
Docstrings needed: 14; Docstrings found: 10; Docstrings missing: 4
Total docstring coverage: 71.4%;  Grade: Very good

How Do I Use It?

Command-line Tool

General usage is: docstr-coverage <path to dir or module> [options]

To test a single module, named some_module.py, run:

$ docstr-coverage some_module.py

To test a directory (recursively), just supply the directory some_project/src instead:

$ docstr-coverage some_project/src
Options:
  • --skipmagic, -m - Ignore all magic methods (like __init__, and __str__)

  • --skipfiledoc, -f - Ignore module docstrings (at the top of files)

  • --exclude=<regex>, -e <regex> - Filepath pattern to exclude from analysis

    • To exclude the contents of a virtual environment env and your tests directory, run:
      $ docstr-coverage some_project/ -e "env/*|tests/*"
  • --verbose=<level>, -v <level> - Set verbosity level (0-3)

    • 0 - Silence
    • 1 - Print overall statistics
    • 2 - Also print individual statistics for each file
    • 3 - Also print missing docstrings (function names, class names, etc.)
  • --docstr-ignore-file=, -d - Filepath containing list of patterns to ignore. Patterns are (file-pattern, name-pattern) pairs

  • --failunder=<int|float>, -F <int|float> - Fail if under a certain percentage of coverage (default: 100.0)

    • File content example:
    SomeFile method_to_ignore1 method_to_ignore2 method_to_ignore3
    FileWhereWeWantToIgnoreAllSpecialMethods __.+__
    .* method_to_ignore_in_all_files
    a_very_important_view_file ^get$ ^set$ ^post$
    detect_.* get_val.*
    

Package in Your Project

You can also use docstr-coverage as a part of your project by importing it thusly:

from docstr_coverage import get_docstring_coverage
my_coverage = get_docstring_coverage(['some_dir/file_0.py', 'some_dir/file_1.py'])
Arguments:
  • Required arg: filenames <list of string filenames>
  • Optional kwargs: skip_magic <bool>, skip_file_docstring <bool>, verbose <int (0-3)>
    • For more info on get_docstring_coverage and its parameters, please see its documentation
Results:

get_docstring_coverage returns two dicts: 1) stats for each file, and 2) total stats. For more info, please see the get_docstring_coverage documentation

Why Should I Use It?

  • Thorough documentation is important to help others (and even yourself) understand your code
  • As a developer, improve your code's maintainability for when you need to make updates and fix bugs
  • As a user, instantly know how easy it's going to be to understand a new library
    • If its documentation coverage is low, you may need to figure a lot out for yourself

Installation

pip install docstr-coverage

If you like being on the cutting-edge, and you want all the latest developments, run:

pip install git+https://github.com/HunterMcGushion/docstr_coverage.git

Special Thanks

Thank you to Alexey "DataGreed" Strelkov, and James Harlow for doing all the hard work. docstr-coverage simply revives and brings their efforts to Python 3. See 'THANKS.txt' for more information.

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