Search Results for "lightning"

A reactive library for creating web apps in Rust and WebAssembly. Sycamore harnesses the full power of Rust via WebAssembly, giving you full control over performance. Write code that feels natural. Everything is built on reactive primitives without a cumbersome virtual DOM. No JavaScript. Had enough of JavaScript? So have we. Create apps using Sycamore without touching a single line of JS.

Angular Performance Checklist is a practical resource and “cheatsheet” aimed at helping Angular (or AngularJS/Angular-related) developers optimize web application performance, covering both network/load-time optimizations and runtime performance improvements. It outlines actionable recommendations — from bundling and minification, tree-shaking, lazy loading, ahead-of-time (AoT) compilation, resource prefetching, caching and compression, to runtime strategies like change-detection...

PyTorchVideo is a deep learning library for video understanding, providing modular components and pretrained models for tasks like action recognition, video classification, detection, and self-supervised learning. It is tightly integrated with PyTorch and PyTorch Lightning, offering flexible APIs for building and training spatiotemporal networks. The library includes efficient implementations of state-of-the-art architectures such as SlowFast, X3D, and MViT, optimized for both research prototyping and production inference. It supports video I/O pipelines, data augmentation, distributed training, and mixed precision computation for large-scale experiments. ...

DeepDiff is a Swift library for efficiently calculating differences between collections and models. It is designed for iOS, macOS, and Swift developers who need fast diffing when updating lists, tables, collection views, or other ordered data displays. The library relies on models conforming to a diff-aware protocol so items can be uniquely identified and compared. This makes it useful for deciding which elements were inserted, deleted, moved, or replaced between two versions of a dataset....