Cobalt is a privacy-focused media downloader web application with a SvelteKit frontend and Node.js/Express API backend. Users paste a URL from supported platforms (YouTube, TikTok, Instagram, Twitter/X, Vimeo, Reddit, SoundCloud, Twitch, Bilibili, and 15+ others) and receive a downloadable media file. The architecture is a monorepo with three packages: @imput/cobalt-web (static frontend), @imput/cobalt-api (processing backend), and @imput/version-info (build-time version helper). The API acts as a fancy proxy - it fetches media streams from source platforms, optionally remuxes/transcodes via FFmpeg (server-side or client-side via libav.js WebAssembly), and streams results back without ever writing to disk. The frontend handles URL input, settings management (localStorage with migration), a processing queue with Web Workers for client-side FFmpeg, i18n (EN/RU), and PWA features. Key data flows: user submits URL → API validates/matches service → extracts stream URLs → returns tunnel/redirect/picker response → frontend either streams directly, proxies via API, or processes locally via Web Workers. External dependencies: FFmpeg (via ffmpeg-static), youtubei.js for YouTube, hls-parser, undici for HTTP, Redis (optional for rate limiting), Cloudflare Turnstile (optional bot protection).
This repository contains ASFFreeGames, a plugin for ArchiSteamFarm (ASF) that automatically collects free Steam games from Reddit and Redlib sources. The plugin monitors the ASFinfo Reddit user for posts containing "!addlicense asf" commands, extracts game identifiers from these posts, and uses ASF's addlicense command to claim those games for all logged-in bots. It operates on a configurable schedule (default 30 minutes) and can also be triggered manually via the "freegames" command. The architecture follows a plugin pattern with clear separation of concerns: core plugin logic handles ASF integration and scheduling, command processing manages user interactions, strategy objects encapsulate different data source approaches (Reddit vs Redlib), and specialized parsers handle the extraction of game information from HTML/JSON responses. The plugin maintains a persistent cache of already-claimed games to prevent duplicates and supports configuration options for filtering results (e.g., skipping free-to-play games or DLC). Notably, the project contains several high-quality, reusable utility components in the Maxisoft.Utils namespace. These include BitSpan (a high-performance bit array using span<long>), SpanDict (a dictionary implementation using spans with linear probing), OrderedDictionary (a dictionary that preserves insertion order), and RandomUtils (a Gaussian random number generator using the Box-Muller transform). These utilities demonstrate advanced .NET span usage and algorithmic implementation skills, with minimal dependencies making them suitable for extraction to other projects. The project is actively maintained with recent commits, comprehensive CI/CD workflows, and targets the latest .NET 9.0 framework. Dependencies appear current, and the codebase shows no significant technical debt or use of deprecated APIs. The plugin properly handles edge cases like rate limiting, network failures, and invalid responses while providing configurable logging options.
This is a mature, actively maintained AI agent skill called 'last30days' that enables agents (Claude Code, Codex, Grok, Gemini CLI, MCP hosts) to research any topic by aggregating content from 20+ social and news platforms (Reddit, X, YouTube, TikTok, Instagram, Hacker News, Polymarket, GitHub, arXiv, Techmeme, Digg, and more) over a rolling 30-day window. The system is primarily a CLI engine (Python) with a companion Go MCP server for Claude Desktop. It employs a sophisticated pipeline: query planning by intent, parallel retrieval from multiple backends (keyless APIs, paid scrapers, CLI tools, LLM-based search), source-specific normalization, engagement-weighted relevance scoring, cross-source clustering, and deterministic fusion (weighted RRF) with per-author caps and diversity floors. Output is rendered as structured JSON, compact text, or self-contained HTML with optional publishing and Atom feeds. The codebase emphasizes security (credential hygiene, no browser cookie reads in unattended mode), determinism (fixture-based evaluation harness with grounding/recency/coherence scores), and graceful degradation (per-source fallback chains, never-raise error envelopes). While classified as an application (it's a skill/plugin for agent hosts), it exhibits strong data engineering traits: source adapters, normalization pipelines, scoring models, and an offline evaluation framework.
deanonymizer is a command-line tool designed for privacy self-audits. It collects public data from platforms like Reddit, Hacker News, GitHub, and Stack Overflow for specified usernames, then analyzes this data to identify personally identifiable information (PII) and other linkable information. The analysis combines a configurable LLM backend (Anthropic, OpenAI, or Claude Code) for inferring soft signals (location, employer, etc.) with a deterministic regex pass for hard identifiers (emails, social handles). The tool outputs a detailed report highlighting findings with confidence levels and remediation suggestions, enabling users to reduce their online footprint. The architecture is modular, separating concerns into CLI handling, platform-specific data fetching, analysis orchestration, LLM abstraction, and report generation.
Reddit Enhancement Suite (RES) is a browser extension that enhances the Reddit browsing experience. It injects a content script into Reddit pages and provides dozens of modular features such as inline media expansion, keyboard navigation, user tagging, account switching, night mode, content filtering, and comment tools. The architecture is modular: each feature is a self-contained Module with lifecycle hooks, and media support is extensible via a Host plugin system. The extension communicates between foreground (content script) and background (service worker) using a custom messaging abstraction built on browser runtime ports. Persistent configuration and user data are stored via a storage wrapper layer that supports key-value, prefix, and blob modes with atomic compare-and-set semantics. The build pipeline uses esbuild with Flow type stripping, and the project includes integration tests via Nightwatch and unit tests via ava. The codebase is mature and well-organized, though it relies on older patterns (Flow, jQuery, lodash) and is tightly coupled to Reddit's DOM and API, which introduces maintenance risk when Reddit changes. There are no data analysis or research components; it is purely a client-side enhancement application.
The Social Media Hacker List repository primarily maintains a curated markdown list of tools and applications for enhancing social media experiences across various platforms (Facebook, Instagram, Twitter, etc.). The list is organized by platform and includes entries such as alternative clients, analytics tools, bots, and content creation utilities. Each entry is manually curated and must meet specific inclusion criteria, such as being created by unaffiliated developers and having recent activity. To ensure the list remains accurate and free of broken or inactive links, the repository includes a Rust-based URL checker application. This tool is executed weekly via a GitHub Actions workflow (check.yaml) to validate every URL in the README.md. For standard URLs, it performs HEAD and GET requests, treating certain HTTP status codes as success (200, 403, 406) with special handling for known edge cases (e.g., 502 for reddit.com, 429 for apps.apple.com). For GitHub repository URLs, it uses the GitHub API to check if the repository is archived or has not been pushed to in the last 365 days, flagging such entries as invalid. The checker application is designed as a standalone, concurrent command-line tool. It reads input from stdin, extracts URLs using a regular expression, and processes them asynchronously with the tokio runtime. The application is containerized via a multi-stage Dockerfile and published to GitHub Container Registry through another workflow (publish.yaml), allowing it to be reused in other contexts. The code demonstrates solid Rust practices, including proper error handling, asynchronous I/O, and modular function design, making its core URL and GitHub checking logic potentially reusable in other projects with minimal adaptation.
iKy (I Know You) is a modular OSINT (Open Source Intelligence) aggregation platform built with FastAPI, Celery, Redis, and an Angular frontend. The system ingests a username or email and concurrently executes 26+ parallel tasks across social media, data breaches, search engines, and dark web sources, returning a structured JSON contract (module, param, validation, raw, graphic, profile, timeline, tasks) consumed by a visual graph/timeline UI. Key architectural patterns include a dynamic module registry that maps route names to Celery task paths, a decorator-based task wrapper (@iky_task) that centralizes dev-mode golden-file bypass, error classification, and performance logging, and a pluggable search provider orchestration layer. The codebase demonstrates a strong separation of concerns between API routing, task execution, and data enrichment, but suffers from fragile scraping logic (LinkedIn RSC parsing, TikTok SSR regex), heavy reliance on browser session cookies, and several deprecated external APIs (Twitter v1.1, FullContact). The project is actively maintained with an extensive test suite (~4K lines) and Docker Compose deployment, though many tests are heavily mocked and may not detect real API drift.
Upvote RSS is a monolithic PHP web application that generates RSS feeds from social aggregation platforms including Reddit, Hacker News, Lemmy, Lobsters, PieFed, Mbin, and GitHub. The system features a modular architecture with separate classes for authentication, community-specific APIs, post processing, content parsing, and AI summarization. Users configure feeds through a web interface built with vanilla JavaScript web components, and the application employs sophisticated caching (Redis, APCu, filesystem) to optimize performance. The platform supports optional features like AI-generated summaries, content extraction, comment inclusion, and NSFW filtering.
Glance is a self-hostable web application designed as a customizable dashboard (startpage) that aggregates information from various sources into widgets. Built in Go, it features a modular widget architecture where each widget type (e.g., RSS, weather, clock) implements a common interface, allowing users to create personalized pages with multiple columns and widgets. The application serves HTML pages with embedded static assets (CSS, JS, images) and uses Go templates for server-side rendering, enhanced by a comprehensive set of template functions. Client-side JavaScript adds interactivity for dynamic updates, masonry layouts, and popovers. The system relies on a YAML-driven configuration (`glance.yml`) that supports variable substitution, file includes, and defines pages, columns, and widget settings. Data fetching is handled by centralized HTTP utilities with caching and user-agent rotation to avoid blocking external services. A theming system generates CSS variables from HSL-based configuration, enabling light/dark modes and custom themes. Optional authentication secures the dashboard, and the application includes diagnostic and CLI tools for maintenance. While the project demonstrates strong engineering in areas like request deduplication (singleflight), flexible configuration, and reusable template functions, it faces challenges due to its extensive widget proliferation (30+ types), coupling between frontend and backend logic, and reliance on an outdated Go version (1.26.6) which is no longer supported, indicating moderate technical drift. Despite these issues, Glance remains a popular and functional solution for personal dashboards.
CoexistAI is a research assistant framework implemented as a FastAPI application that provides a suite of API endpoints for web search, YouTube and Reddit retrieval, geospatial mapping, git repository analysis, text-to-speech/podcast generation, and knowledge base creation from local files or crawled websites. It integrates with an MCP server for agentic workflows and supports pluggable LLMs (Google, OpenAI, Ollama, local) and embedders (Google, HuggingFace, Infinity). The architecture is monolithic with modular utility functions, containerized via Docker with a companion SearxNG instance for privacy-respecting search. The codebase demonstrates a hybrid nature: while primarily an application with explicit API entry points, its core purpose is to support research and data-gathering tasks, making it equally relevant for data research scenarios. Configuration is centralized, and the system includes a web-based admin UI for runtime parameter changes. Active development is evident from recent commits and numerous utility modules, though some global mutable state and fallback-heavy code indicate where the system has evolved rapidly.
This repository contains the original open-source codebase for reddit, the social news aggregation and discussion platform. It is a monolithic web application built on the Pylons framework (Python 2), serving both a server-rendered frontend (Mako templates, jQuery, Backbone) and a REST-like API. The architecture relies on multiple data stores: PostgreSQL for core entities (things), Cassandra for high-write data (votes, comments trees, view counts), Memcached/McRouter for caching, and RabbitMQ for asynchronous job processing. It includes a full advertising system, user awards/gold, moderation tools, a wiki, and traffic analytics. While the codebase is archived and relies on heavily outdated dependencies (Python 2, Pylons, pycassa), it showcases several well-designed internal patterns such as a pluggable provider system, a layered cache chain with stale-while-revalidate, and a feature flag framework for A/B testing. These components demonstrate non-trivial engineering skill and could be extracted for reuse. However, the vast majority of the codebase is tightly coupled to reddit-specific models and global state, limiting reusability without significant adaptation.