Understanding, and interacting with, the Open-Source community is, nowadays, a vital part of the Software Engineering profession. This project is proposing to create a sophisticated AI Application capable to ingest large amount of activity logs, publicly available, from the various Open-Source portals and use Natural Language Understanding and Analytics tools/techniques provide aggregated insights on trends, dynamics and facts behind the Community.
In order to run NL analysis, add IBM Watson NLU API key & url into keys.txt.
Enter a GitHub Access Token and enter the name and owner of the repo you want to gather data from.
Finally, specify whether you want to get issue or pull requests.
If the comments are already in the database, you will be asked whether you want to use the existing data.
JSON files with extracted information will be stored in cwd/fetched_data folder.
To run API Queries independently from NL processing, open query.py and run the main function.
In order to deoply this program using Docker :
- Create an account on dockerHub .
- Build docker image :
docker build -t /SwEng-app .
- Run docker image :
docker run -it /SwEng-app
- Push docker image to dockerHub :
docker login -u -p docker push /SwEng-app
- Refer to deploy.sh file for more information : Docker.sh