This repository provides the `starred` Python CLI tool, which generates and maintains an Awesome-style Markdown list from a GitHub user's starred repositories. The tool queries the GitHub GraphQL API to fetch all starred repos (with pagination), groups them by programming language or repository topic, and outputs a formatted Markdown document. It can optionally sort categories alphabetically, filter by topic popularity, include private repositories, and directly push the generated file to a target GitHub repository using the GitHub REST API. The architecture is a simple single-command CLI with two source modules: `starred/starred.py` (Click CLI entry point and Markdown generation) and `starred/githubgql.py` (a self-contained GraphQL client for fetching starred repos). External dependencies include `click`, `requests`, `github3.py`, `gql`, and `aiohttp`. The code is clean, follows a straightforward functional design, and integrates well with GitHub's APIs. While it lacks unit tests, the CI runs an integration test against the real GitHub API.
This repository is a curated, community-driven directory of open-source iOS, iPadOS, watchOS, tvOS, and visionOS applications. It is not a software application itself but a data curation and documentation project. The single source of truth is `contents.json`, a structured JSON file containing metadata for over 1,600 projects (title, category, source URL, screenshots, tags, stars, etc.). Ruby scripts in `.github/` transform this JSON into multiple markdown documents: `README.md` (the main categorized list), `APPSTORE.md` (apps with App Store links), `ARCHIVE.md` (deprecated projects), and `LATEST.md` (newest and recently updated entries). The pipeline also enriches data via the GitHub API (stars, license) and validates schema and categories in CI (CircleCI and GitHub Actions). While the repo is not a data research pipeline in the ML sense, it exhibits data engineering patterns: a structured data source, automated ETL (extract from JSON, transform to markdown, load to GitHub), validation, and deployment. The primary value is as a reference for developers seeking open-source iOS code to learn from or reuse.
This repository is the canonical community index for Cloudstream extension repositories. It maintains a JSON list of repo URLs (repos-db.json) and uses a Python CI script to validate each repository's manifest and every plugin it exposes. The validation fetches repo.json, asserts required fields (name, manifestVersion, pluginLists), then concurrently checks every plugin URL with HTTP requests, collecting failures across all repos and their plugin lists. If all checks pass, it generates list.md with custom cloudstreamrepo:// deep links and, on the default branch, publishes that markdown to a Rentry page via GitHub Actions. Architecturally it is a small batch validation utility rather than a running service: ci_check.py is the entry point, create_markdown.py provides output rendering, and a GitHub Actions workflow orchestrates execution on every push/PR and publishes the result. External dependencies are httpx for async HTTP and rentry (CI only) for publishing. It relies on the availability of dozens of third-party GitHub/GitLab-hosted repo.json files. Notable implementation details include a JSONC-compatible decoder that strips // comments, asynchronous fan-out with gathered exceptions to validate many URLs quickly, and structured error reporting. The code is simple and readable, but dependency versions are unpinned and the checkout action is outdated, which introduces moderate technical drift.
This repository is a community-driven curated list of Vim9script plugins, utilities, and libraries, hosted primarily on GitHub and Codeberg. Its main output is a generated README.md table that organizes contributions by category with descriptions and star counts. While the heart is the list itself, the repository includes a reusable Python script (`scripts/update_readme.py`) that reads a flat list of repository URLs from `contributions.md`, fetches metadata (description, star count) from the GitHub and Codeberg APIs, sorts and formats the data, and rewrites both `contributions.md` and `README.md`. The script also tracks star milestones and logs them to `congratulations.md`. The architecture is a single-purpose CLI utility. Despite being primarily a directory, the automation script qualifies it as an application with a hybrid nature.