Puppeteer is a high-level Node.js library for browser automation, primarily targeting Chrome/Chromium and Firefox. It provides a rich API to control browsers programmatically via the Chrome DevTools Protocol (CDP) and WebDriver BiDi, supporting both headless and headed modes. The library is organized as a monorepo with multiple packages: `puppeteer` (full library with browser management), `puppeteer-core` (core automation API without browser download), `@puppeteer/browsers` (browser download and CLI), `@puppeteer/ng-schematics` (Angular integration), and a test server. The architecture features abstract API classes (Page, Browser, ElementHandle) with separate CDP and BiDi implementations, a custom event system, and extensive use of TypeScript generics and resource management patterns. Puppeteer is widely used for end-to-end testing, web scraping, and automation tasks, with a strong emphasis on cross-browser compatibility and modern web platform features.
MockServer is a highly sophisticated, multi-protocol HTTP(S) mock server and proxy for testing, written in Java with Netty. It supports HTTP/1.1, HTTP/2, HTTP/3 (QUIC), gRPC, WebSockets, DNS, TCP, and binary protocols on a single port. The core engine provides expectation-based request matching, response generation, forwarding, proxying, recording, verification, and chaos engineering (latency, connection drops, error injection). It also includes built-in LLM mocking (OpenAI, Anthropic, Gemini, etc.), OIDC/OAuth2/SAML identity providers, SCIM provisioning, WASM custom rules, and drift detection. The repository is a monorepo containing the Java server, multi-language client libraries (Java, Node, Python, Ruby, Go, .NET, Rust, PHP), a React dashboard UI, IDE plugins (JetBrains, VS Code), Helm charts, Docker images, and extensive CI/CD pipelines via Buildkite. The architecture is modular with clear separation of concerns: core model/matcher/serialization in `mockserver-core`, Netty transport in `mockserver-netty`, language-specific clients in `mockserver-client-*`, and a React UI in `mockserver-ui`. The codebase demonstrates strong engineering practices including DTO patterns with Jackson serializers, a matcher hierarchy with compiled-once validators, bounded caches, constant-time equality checks, and extensive test coverage with integration tests across multiple environments.
NSFWJS is a client-side JavaScript library for detecting NSFW (Not Safe For Work) content in images using TensorFlow.js. It provides a simple API to load pre-trained models (MobileNetV2, MobileNetV2Mid, InceptionV3) and classify images into five categories: Drawing, Hentai, Neutral, Porn, and Sexy. The library is designed for both browser and Node.js environments, with backend selection guidance for optimal performance (WebGL, WebGPU, WASM, CPU). The core architecture consists of a lightweight `NSFWJS` class that handles model loading, inference, classification, and disposal, with support for tree-shaking via separate model imports. The repository also includes several demo applications: a full-featured React + Vite demo with Web Worker offloading, camera support, and file drop; a Node.js Express server example; and a minimal HTML/script tag demo. While primarily an application library, it is hybrid in nature as it bundles pre-trained model weights (quantized and base64-encoded) and includes model conversion scripts, making it both a software tool and a model distribution package. The library relies on TensorFlow.js as a peer dependency and uses IndexedDB for model caching in the browser.