JupyterLite is a JupyterLab distribution that runs entirely in the web browser, backed by in-browser language kernels. With standard JupyterLab, where kernels run in separate processes and communicate with the client by message passing, JupyterLite uses kernels that run entirely in the browser, based on JavaScript and WebAssembly.

This means JupyterLite deployments can be scaled to millions of users without the need for individual containers for each user session, only static files need to be served, which can be done with a simple web server like GitHub pages.

This opens up new possibilities for large-scale deployments, eliminating the need for complex cloud computing infrastructure. JupyterLite is versatile and supports a wide range of languages, with the majority of its kernels implemented using Xeus, a C++ library for developing language-specific kernels.

In conjunction with JupyterLite, we present Emscripten-forge, a conda/mamba based distribution for WebAssembly packages. Conda-forge is a community effort and a GitHub organization which contains repositories of conda recipes and thus provides conda packages for a wide range of software and platforms. However, targeting WebAssembly is not supported by conda-forge. Emscripten-forge addresses this gap by providing conda packages for WebAssembly, making it possible to create custom JupyterLite deployments with tailored conda environments containing the required kernels and packages.

In this talk, we delve deep into the JupyterLite ecosystem, exploring its integration with Xeus Mamba and Emscripten-forge.

We will demonstrate how this can be used to create sophisticated JupyterLite deployments with custom conda environments and give an outlook for future developments like R packages and runtime package resolution.

Many Python frameworks are suitable for creating basic dashboards or prototypes but struggle with more complex ones. Taking lessons from the JavaScript community, the experts on building UI’s, we created a new framework called Solara. Solara scales to much more complex apps and compute-intensive dashboards. Built on the Jupyter stack, Solara apps and its reusable components run in the Jupyter notebook and on its own production quality server based on Starlette/FastAPI.

Solara has a declarative API that is designed for dynamic and complex UIs yet is easy to write. Reactive variables power our state management, which automatically triggers rerenders. Our component-centric architecture stimulates code reusability, and hot reloading promotes efficient workflows. With our rich set of UI and data-focused components, Solara spans the entire spectrum from rapid prototyping to robust, complex dashboards.

Are you looking for a high performance visualization component for the web? Need to filter, sort, pivot, and aggregate static/streaming data in realtime? Daunted by the massive JS ecosystem? In this talk, we’ll build a high performance web frontend using the open source library Perspective.