Awesome GitHub RepositoriesHierarchical Data Structures

Portia is a containerized scraping platform and visual web scraper that enables no-code data extraction. It serves as a Scrapy visual scraping tool and spider generator, allowing users to design and deploy web scrapers through a graphical interface instead of writing manual selector code. The system distinguishes itself by converting visual web page annotations into executable Scrapy spider code and structured JSON specifications. This visual-to-code mapping allows users to define scraping logic and extraction rules through a point-and-click interface, which can then be exported for use in ex

Elvish is a shell that combines interactive command-line use with a structured scripting language, designed to make both everyday terminal work and automation tasks more predictable and readable. It parses, compiles, and executes code in three phases, catching syntax and variable errors before any code runs, and it aborts execution on command failure by default to prevent silent errors. The shell introduces value-oriented pipelines that pass structured data like lists, maps, and closures between commands, preserving types without serialization. It also mixes traditional byte streams with thes

Pokémon battle simulator.

Poml is a prompt management framework and templating engine designed for authoring, versioning, and rendering structured prompts for large language models. It uses a semantic markup language to organize prompts into reusable templates, combining them with dynamic context and data to generate formatted inputs. The system distinguishes itself by decoupling core prompt logic from final presentation through a stylesheet-based approach. It provides a dedicated JSON schema output generator to enforce strict, machine-parsable model responses and a configuration interface for managing function tool s

This project is a server implementation of the Model Context Protocol designed to function as an AI knowledge retrieval tool. It acts as a semantic search engine and web scraping framework that indexes technical documentation from web sources, local files, and archives, making this information directly accessible to AI coding assistants for context-aware research and querying. The system distinguishes itself through a hybrid search architecture that combines vector-based embeddings with full-text retrieval to improve the accuracy of documentation lookups. It features a modular pipeline for co

Dieses Projekt ist eine hochperformante Data-Grid-Komponente für React-Anwendungen. Es bietet ein deklaratives Framework zum Rendern umfangreicher Datensätze und komplexer tabellarischer Strukturen, indem es eine Canvas-basierte Rendering-Engine anstelle herkömmlicher DOM-Knoten verwendet. Die Bibliothek zeichnet sich durch eine Windowed-Virtualization-Engine aus, die den Speicherverbrauch konstant hält, indem nur der sichtbare Teil des Grids gerendert wird. Sie übersetzt Pointer-Interaktionen durch koordinatenbasiertes Mapping in spezifische Zellreferenzen und unterstützt die Injektion von externem Applikations-State und Themes direkt in die Canvas-Umgebung, um einen konsistenten Datenzugriff über benutzerdefinierte Zell-Renderer hinweg zu gewährleisten. Das Grid unterstützt komplexe Layout-Konfigurationen, einschließlich fixierter Zeilen und Spalten, verbundener Zellen und in der Größe anpassbarer Header. Zudem bietet es Tools zur Organisation von Informationen in hierarchischen, baumbasierten Strukturen, um verschachtelte Datenbeziehungen abzubilden. Die Bibliothek wird als Set von React-Primitives bereitgestellt, die sich in bestehende Webanwendungen integrieren lassen, um den Scroll-Status und das Layout-Reconciliation für komplexe Daten-Interfaces zu verwalten.