Historical GitHub contributions chart

Read more about script usage and examples in a blog post.

Use

Getting data

1. Clone repo

   $ git clone git@github.com:velimir0xff/contributions.git && cd contributions
   

2. Install dependencies:

   $ pip install -r ./requirements.txt
   

3. Set GITHUB_TOKEN environment variable. It's required to talk to GraphQL endpoint. You can get token on token page.

   $ export GITHUB_TOKEN=<token>
   

4. Run script:

   $ ./contributions.py > stats.json
   

For additional configuration options see script usage:

$ ./contributions.py -h
usage: contributions.py [-h] [-g URL] [-u USERNAME] [-o OWNERS] [-v] [-n] [-m MAX_CONCURRENCY]
                        [-c MAX_CONTRIBUTORS] [--out OUT]

List projects to which user have contributed to. Script requires valid GitHub token set via GITHUB_TOKEN environment variables.

optional arguments:
  -h, --help            show this help message and exit
  -g URL, --url URL     GitHub base url (default: https://api.github.com)
  -u USERNAME, --username USERNAME
                        Contributor username
  -o OWNERS, --owner OWNERS
                        Owners to check
  -v, --verbose         Verbose mode (default: False)
  -n, --no-progress     Do not show progress bar (default: False)
  -m MAX_CONCURRENCY, --max-concurrency MAX_CONCURRENCY
                        Maximum # of concurrent requests to GitHub (default: 20)
  -c MAX_CONTRIBUTORS, --max-contributors MAX_CONTRIBUTORS
                        Maximum # of concurrent requests to GitHub contributors endpoint (default:
                        20)
  --out OUT             output file with contributions (default=stdout)

Data visualization

In order to generate chart use contributions.ipynb jupyter notebook in the repo root directory. Configure filename variable to point to stats data generated by script (example: filename = 'examples/uwiger.json') and run all cells.

To save pictures just add the following line at the end of the notebook:

fig.savefig('my-stats.png', dpi=300, bbox_inches='tight')

or if you want a transparent version:

fig.savefig('my-stats.png', dpi=300, bbox_inches='tight', transparent=True)

Contribute

Please feel free to submit pull requests to this repository or open an issue.