Awesome GitHub RepositoriesDeclarative Visualization Languages

This project is a client-side rendering engine that transforms declarative, text-based syntax into visual diagrams directly within the browser. By utilizing a domain-specific language, it allows users to define complex structures—such as software architectures, process flows, and system behaviors—without the need for manual layout configuration. The library functions as a browser-based runtime that parses these definitions into intermediate abstract syntax trees, which are then processed by specialized engines to generate high-fidelity, resolution-independent graphics. The system distinguishe

This project is a diagram-as-code tool that transforms declarative text scripts into professional visual representations. It functions as a technical documentation generator, allowing users to define nodes, connections, and hierarchical relationships through a domain-specific modeling language that integrates directly into version-controlled developer workflows. The tool distinguishes itself through a highly modular architecture that decouples diagram definitions from spatial positioning. It features a pluggable layout engine that supports multiple arrangement algorithms, alongside a styling

This project is a declarative visualization library and geospatial framework designed for rendering large-scale data sets within web browsers. It functions as a high-performance graphics engine that leverages hardware acceleration to display complex 2D and 3D visual layers, enabling the visualization of millions of data points through a structured, component-based syntax. The framework distinguishes itself through its ability to synchronize custom data visualizations with third-party mapping platforms. By managing camera states and coordinate systems, it allows developers to overlay high-perf

Vega is a reactive visualization engine that translates structured specifications into interactive, browser-based graphical representations. It functions as a declarative grammar for data visualization, allowing users to define complex charts and maps through a JSON-based configuration format rather than imperative code. The system operates on a dataflow-based reactive graph that automatically propagates updates through the visualization whenever input data or user interactions change. By integrating a modular transformation pipeline, the engine handles data filtering, sorting, and aggregatio

Altair is a declarative data visualization library for Python that generates Vega-Lite specifications. It functions as a tool for mapping data to graphical marks using a high-level syntax, allowing users to describe the desired visual outcome instead of writing imperative drawing commands. The framework enables the creation of interactive charts and graphics, including linked views and filtered displays that respond to user input in real time. It supports the design of multi-view dashboards by combining visualizations into layered or faceted layouts. The library provides capabilities for sta

Altair is a declarative data visualization library for Python based on the Vega-Lite grammar. It allows users to create statistical visualizations by mapping data fields to visual properties rather than writing imperative drawing code. The library focuses on interactive charting through a system of linked selections and filters that update multiple visualizations based on user input. It renders charts as JSON and HTML for display in web browsers and interactive notebooks. The project covers statistical data analysis and interactive data exploration, providing capabilities to export visuals a

Polynote este un mediu de notebook poliglot și un sistem de documente interactive conceput pentru executarea codului în mai multe limbaje în cadrul aceluiași document. Funcționează ca un instrument de analiză a datelor cross-language și un IDE pentru limbaje JVM, permițând utilizatorilor să combine cod executabil, text îmbogățit și vizualizări de date pentru a prototipa și documenta fluxuri de lucru tehnice. Sistemul se distinge prin capacitatea de a partaja date și variabile între diferite runtime-uri de limbaj, cum ar fi Python și JVM. Utilizează conversia de obiecte între limbaje și wrapping-ul de date pentru a transmite obiecte între runtime-uri, permițând fluxuri de lucru cu date multilingve. În plus, se integrează cu Apache Spark pentru a executa sarcini de procesare distribuită a datelor prin trimiteri către clustere locale sau remote. Platforma oferă o suită cuprinzătoare de capabilități pentru analiza și vizualizarea datelor, inclusiv un tabel de simboluri în timp real pentru monitorizarea runtime-ului și suport pentru randarea specificațiilor Vega. Gestionează dependențele pentru runtime-urile JVM și Python folosind rezoluția bazată pe coordonate și oferă editare îmbunătățită de tip IDE cu autocompletare și evidențierea erorilor. Funcțiile de gestionare a documentelor includ un cuprins dinamic, căutarea conținutului în mai multe notebook-uri și recuperarea backup-urilor bazată pe browser pentru a preveni pierderea datelor din fișiere corupte.