This is my submission to the GitHub data challenge. Take a look at the live demo for a description of the project and a view of what the results look like.
To run the analysis, you'll need Redis and a running redis-server.
You'll also need FLANN including
the Python bindings installed on your Python path. Then, install the other requirements
using:
pip install -r requirements.txt
Download all the data by running:
python fetch.py
And then analyse the data by running:
python process.py data/*.json.gz
This will accumulate stats in the redis database.
Finally, you can build the K-nearest neighbors index by running:
python osrc/build_index.py
The web app is a Flask app that is defined in osrc/__init__.py.
The Open Source Report Card was created by Dan Foreman-Mackey and it is made available under the MIT License.