6 repositorios
Extensions that add geospatial indexing capabilities to SQLite3 databases.
Distinct from C Language Extensions: No candidate covers SQLite3 extensions for geospatial indexing; closest candidates are C language extensions or Go extensions, which are unrelated.
Explore 6 awesome GitHub repositories matching data & databases · SQLite3 Extensions. Refine with filters or upvote what's useful.
better-sqlite3 is a high-performance SQLite3 client for Node.js that executes queries synchronously, returning results directly without callbacks or promises. It compiles as a native addon using N-API, binding directly to the SQLite3 C library for immediate query execution and zero-copy result serialization into native JavaScript objects. The library is optimized for Write-Ahead Logging (WAL) mode, enabling faster concurrent reads and writes in web applications. It provides durability level tuning through the synchronous pragma, allowing adjustments between FULL, NORMAL, and OFF modes to bala
The fastest synchronous SQLite3 library for Node.js, executing queries directly without callbacks or promises.
node-sqlite3 is a relational database client and a set of native bindings that allow Node.js applications to interact with SQLite databases. It functions as a C++ native addon, linking JavaScript to the SQLite C library to manage data stored in local files or in-memory stores. The project includes optional support for SQLCipher, enabling page-level encryption to secure local database files. The driver covers a wide range of database management capabilities, including executing SQL queries with parameter binding, managing connections to database files, and preparing statements for repeated ex
Provides native bindings to enable Node.js applications to interact with SQLite databases.
Vuido is a framework for building native desktop applications for Windows, macOS, and Linux using Vue.js components, without requiring Electron or Chromium. It maps Vue components directly to native widgets from the libui library, creating lightweight applications that run on a single-threaded event loop and compile templates at build time for optimized runtime performance. The framework provides a complete Vue.js component-to-native bridge, enabling two-way data binding via v-model, component-based window composition, and platform-specific package generation for distributing executables. It
Provides a Node.js binding to the libui native GUI library for creating cross-platform desktop interfaces.
H3 is an open-source library that provides a hierarchical hexagonal grid system for geospatial indexing. It projects the Earth onto an icosahedron and tiles each face with hexagons to minimize distortion, then encodes each hexagon as a 64-bit integer that stores its resolution and position in the hierarchy. This integer encoding enables fast bitwise operations for grid navigation and spatial analysis. The library offers a comprehensive set of grid topology algorithms for computing neighbor relationships, distances, and paths between cells directly on the hexagonal grid without geographic coor
Provides an SQLite3 extension that wraps the native C library for hexagonal indexing functions.
NodeGit is a native Node.js binding library that wraps the libgit2 C API, providing direct Git repository operations from JavaScript without shelling out to the Git command-line interface. It exposes Git operations such as cloning remote repositories, opening local repositories, reading file contents from specific commits, and walking through commit history, all through a Promise-based asynchronous API that prevents event loop starvation by offloading blocking operations to a worker pool. The library distinguishes itself by bridging the C/JavaScript boundary through N-API, with reference-coun
Provides native Node.js bindings that expose Git repository operations for cloning, committing, and history traversal.
Este proyecto es un recurso educativo integral y un manual de tutoriales para construir, entrenar y desplegar modelos de machine learning usando TensorFlow 2. Sirve como una guía de aprendizaje estructurada que cubre conceptos fundamentales de deep learning, incluyendo arquitecturas de redes neuronales, diferenciación automática y operaciones con tensores. El manual proporciona orientación técnica sobre cómo optimizar la eficiencia de ejecución mediante la gestión de memoria de GPU, entrenamiento distribuido y cuantización de modelos. También incluye guías detalladas para construir pipelines de datos de alto rendimiento y exportar modelos para servidores de producción, dispositivos móviles y navegadores web. El material abarca una amplia gama de capacidades, incluyendo el desarrollo de modelos con redes convolucionales y recurrentes, la implementación de funciones de pérdida y capas personalizadas, y el uso de modelos preentrenados para transfer learning. También aborda estrategias de despliegue para dispositivos edge y el uso de entornos de ejecución en la nube para aceleración por hardware. El recurso está implementado como una colección de Jupyter Notebooks.
Demonstrates how to execute native saved model files in Node.js using C++ bindings for advanced operations.