GitLit 🔥

[ALPHA VERSION]

GitLit is a social network exclusively for the Open-Source developers, which works by connecting enthusiastic developers to the most interesting and relevant projects to them, and forming new communities of like-minded passionate developers.

🤔 Why GitLit?

1. Its hard to find contributable projects - What if you can get a dashboard full of project and issues suggestions, which are relevant to you - both skill and interest wise?

Target Users

We have found two primary use-cases for GitLit, one for the developers to discover interesting projects and the other is for people in the industry to find talented and enthusiastic developers.

Project Discovery

• Students & Beginners: GitLit can be used by students and beginners to get started into the world of Open Source. It helps them to break-the-ice, and kick-start their FOSS journey without essentially going into deeper level.

• Developers GitLit can also be used by amateur as well as professional developers to discover innovate, interesting and relevant projects to contribute to, based on their skill level.

Developer Discovery

• Developer Advocates: GitLit can be used by developer advocates to identify enthusiastic and talented contributors, who are interested in their organization, and connect with them. It can be also used by them to analyse their projects, and monitor community members.

• College Clubs: College based computer clubs like amFOSS, can use GitLit to identify enthusiastic and talented students out of a large pool, effectively monitor them and check their progress.

• Corporate Recruiters: Corporate companies can discover developers, with the required talent and passion using credible metrics of GitLit

🔌 How it Works?

Suggestion Panel to help developers

1. Fetches all data about a developer, once a developer signs-up.
2. After analysing his previous contribution pattern, an complex algorithm rates the developer using smart metrics, and classifies him into interest groups.
3. Based on his interests, and his skill in the given topic of interest, an ML-based matching algorithm matches it with most relevant projects
4. The developer recieves relevant and interesting suggestions for projects, and issues.

Discovery Panel to help projects

Some Screenshots

Technical Details

Rating Metrics

User Metrics:

• Base Score : General cliche’ metrics
• Creation : How good the developer’s own project are?
• Contribution : How active is the developer in contributing to other repositories?
• Community : How large is the network of the repository?
• Activity : How frequently does the user contribute?
• Topic-wise Metrics -
  • Skill Score : represents the skill a user has for a topic?
  • Interest Score: how interested the user is in the topic?

Repo Metrics:

• Merit: How valuable is the community to FOSS?
• Activity: How engaging and active is the community?
• Popularity: How popular is the community?
• Inclusivity : How likely is the community open to new contributors?

Scores for each of the above mentioned trait for user and repo are calculated, and matching is performed.

Data Sourcing

View GitHub API-related documentation at /api

💻 Algorithms

View algorithm documentation at /algorithms

🔩 Tech Stack

• Language: Python 3.6
• Framework (full-stack): Django
• API: GraphQL (Github API 4), Rest API (Github API 3)
• Frontend Frameworks: Bootstrap 4
• Javascript Libraries: jQuery
• Stylesheet Pre-processors: Sass

👥 Contributors

1. Venu Vardhan Reddy
2. Akhil K Gangadharan
3. Ashwin S Shenoy

Contributors are welcome! <3

✒️ License

GNU General Public License v3.0