Machine Learning based Community Health and Communication

Augur is a Python library, REST server and Flask web application which is used to collect free and open source data and provide meaningful insights around it. The data is collected across various sources like open source repos, mailing lists and other communication systems. Augur uses categorised workers to collect specific data. Currently CHAOSS provides metrics by dividing them into working groups. Few of such metrics are frequency of contributions, types of contributions, time frame between opening and closing a pull request, diversity and inclusion, leadership, efficiency and effectiveness of mentorship programs. This project will play an important role in analysing the open source community health. It provides an efficient way to compute and visualise the metrics through an API. Using this API will provide a more accessible way to understand and visualise various metrics. Deliverables: 1. Create an API for visualising the metrics provided by various machine learning workers and improve their performance. 2. Work on implementing new metrics within the augur machine learning workers and test the performance of newly added metrics with the optimised model to see if the optimised model works for new metrics added. 3. Work on augur_view to provide a customised and accessible dashboard to the user.