Search Results for "remote desktop"

This project provides a version of VS Code that runs a server on a remote machine and allows access through a modern web browser. It's based on the very same architecture used by Gitpod or GitHub Codespaces at scale. VS Code has traditionally been a desktop IDE built with web technologies. A few years back, people started patching it in order to run it in a remote context and to make it accessible through web browsers.

...It brings together console, editor, plotting, workspace, history, and file-management panes into a unified interface, helping data scientists, statisticians, and analysts to work more productively. The IDE is cross-platform: there are desktop versions for Windows, macOS and Linux, as well as a server version for remote or multi-user deployment via a web browser. In addition to code editing and execution, RStudio offers extensive support for reproducible research via R Markdown, notebooks, and integration with version control systems like Git and SVN. Package development is built in, with tooling for building, checking, and testing R packages, plus integration with documentation tools, CRAN submission workflows, and project templates.

Paradev, formerly Superset, is an open-source desktop development environment designed to orchestrate multiple AI coding agents simultaneously. It allows developers to run Claude Code, Codex, OpenCode, Gemini CLI, and other command-line agents within a unified workspace. Each task receives an isolated Git worktree, branch, and terminal environment to prevent conflicting changes. Users can monitor agent progress, inspect code modifications, and manage commits without switching applications....

All-in-one web-based development environment for machine learning. The ML workspace is an all-in-one web-based IDE specialized for machine learning and data science. It is simple to deploy and gets you started within minutes to productively built ML solutions on your own machines. This workspace is the ultimate tool for developers preloaded with a variety of popular data science libraries (e.g., Tensorflow, PyTorch, Keras, Sklearn) and dev tools (e.g., Jupyter, VS Code, Tensorboard)...