Search Results for "open personal data"

Gitlogue provides a fun and creative command-line tool that turns your Git commit history into an animated replay, displaying your commits as if someone were typing the changes in real time with cinematic flair. When you run this tool in the terminal, it visually replays diffs line by line, highlights syntax, and shows changes evolving in a way that feels like watching a code story unfold, which can be entertaining and useful for reviewing history or showcasing progress. It builds on typical...

GitFive is an open-source OSINT tool for investigating GitHub users and connecting publicly discoverable identity information. It can examine a username or email address and search for related GitHub accounts and identities. The tool analyzes repositories to uncover names, email addresses, local identities, and historical identity changes. It can generate possible email combinations and test them for matches. GitFive also identifies potential secondary accounts and can extract public SSH...

This VM is created for 2 reasons: 1. Very little initial setup work required to make a GIT Server live, within minutes. 2. This system should keep running for Years, without requiring Updates / Breakages. If you are new to Virtual Machines, then please watch the Video below ( taken from my other project. just replace td with gi wherever mentioned ) After starting this VM, please login to its administration panel with: Website Address: https://gi.local/ ( Accept Any Warnings due to...

GitHub Rater is a web application that analyzes a GitHub user’s public profile and computes a composite “rating” or score based on various activity indicators fetched from the GitHub API. It’s designed to help developers assess and improve the quality and completeness of their GitHub presence by highlighting strengths and weaknesses such as follower count, repository descriptions, star counts, and bio information. Users can search for any public GitHub user and receive a breakdown of scores...

Albedo is an open-source recommender system aimed at helping developers discover GitHub repositories by learning from activity signals. It treats repositories and developers as a graph of interactions and applies large-scale matrix factorization to model affinities, with Apache Spark providing the distributed data processing. The project focuses on implicit feedback—stars, watches, and other engagement metrics—so it can build useful recommendations without explicit ratings. ...