$ show krzemienski/awesome-video
Awesome Video is a curated resource catalog for streaming video technologies, maintained as structured JSON (contents.json) and rendered into both a README and a static documentation site (MkDocs Material) deployed to awesome.video. The catalog spans ~50 hierarchical categories covering HLS, DASH, FFmpeg, codecs (HEVC/VP9/AV1), transport protocols (RIST/SRT/RTMP), players, DRM, QoE, testing, CDN, HDR, subtitles, and learning resources. It is not a runtime application — it is a content curation pipeline: contents.json is the source of truth, convert.rb generates the README, database.json feeds the site's lunr search index, and loader.py imports bookmarks from Raindrop.io. The repo is hybrid in nature: primarily a curated data catalog with a static-site build system around it, rather than a software application or research pipeline. The build pipeline (GitHub Actions) validates the JSON against schema.json, checks external links with awesome_bot, and deploys to GitHub Pages. The curation quality is strong — entries include authoritative references (Netflix TechBlog, DASH-IF specs, Apple WWDC sessions, Xiph test media) — but the supporting code is simple utility scripting with notable weaknesses: hardcoded Raindrop.io credentials in loader.py, inconsistent category identifiers and malformed tag entries in the data, and aging CI dependencies (Python 3.7, jinja2 3.0.3). The repo is actively maintained and the data model (hierarchical categories + multi-tagged project records) is a clean, portable schema for any awesome-list-style content site.
The LLM identified 3 files worth highlighting for reuse:
A self-contained Ruby script that transforms a flat JSON catalog (contents.json) into a hierarchical markdown README with parent/child/grandchild category nesting. It filters projects by category presence and generates a structured table of contents. The pattern is directly adaptable to any curated-list project that needs to render structured JSON as nested markdown documentation, with no internal module dependencies.
A JSON Schema document that enforces the structure of the curated catalog — required fields (title, description, homepage, category), type constraints, and category hierarchy rules. It is used in CI to validate contents.json before README generation. The schema-driven validation pattern is reusable for any project maintaining a structured resource catalog with automated quality gates.
A Python script that ingests bookmarks from the Raindrop.io API, merges them with the existing catalog, and sanitizes metadata. It demonstrates an external-API-to-JSON-catalog ingestion pattern with deduplication and merge logic. Caveat: it contains hardcoded credentials (cookie-based auth token and collection ID), so it must be refactored to use environment variables before reuse in another project.