Bulma
bulma.ioCSS components, layout and themes for responsive interfaces
CSS components, layout and themes for responsive interfaces
An approachable JavaScript framework for building interactive user interfaces.
Build standards-based web components with reactive state, scoped styles, and declarative templates.
Use an open-source IDE in a browser or on desktop, with an extension model based on Open VSX.
Build desktop applications with JavaScript, HTML, and CSS using a Chromium and Node.js runtime.
Build reactive web applications in Rust with client-side or server-side rendering.
Realtime voice, video, and AI APIs for developers
A PowerShell framework for unit, integration, and environment tests with mocking and CI reports.
A source-focused SVG icon family with generated framework packages.
Build interactive terminal applications in Go with an event-driven model, update, and view loop.
Build and deploy full-stack web projects with Git integration and preview environments.
Search downloaded programming and framework documentation offline from a desktop reference library.
Install and manage multi-language Git hooks from a versioned repository configuration.
Automate remote execution, configuration management, and infrastructure orchestration.
A browser IDE for running short code samples or building supported multi-file projects across many languages.
Research trading decisions with reinforcement-learning experiments
Combine subscriptions, usage meters and prepaid product credits
Run web and mobile application tests on hosted browsers and physical devices without maintaining a device lab.
Describe mobile and web UI journeys as YAML flows and run them on a real or virtual target.
Run gray-box end-to-end tests against React Native apps on iOS and Android.
Build a custom build, test, and release pipeline from a Python-configured framework.
Build browser interfaces with declarative components compiled from HTML, CSS, and JavaScript.
Compiles and optimizes machine-learning models for deployment across hardware targets.
Build and train Python machine-learning models with tensor operations, neural-network layers, and automatic differentiation.