This release adds support for new geospatial formats, tighter integration with the scientific Python ecosystem, a redesigned Story Map editor, and a more expressive way to style geographic data.
The QGIS open-source project is a cornerstone in the geosciences ecosystem, providing robust tools for spatial data analysis and visualisation.
The latest iteration of the web-based collaborative CAD editor
Scaling Jupyter dashboards up to the millions.
We are thrilled to introduce JupyterCAD, a tool that integrates Computer-Aided Design (CAD) capabilities into JupyterLab.
Introducing a mamba-based distribution for WebAssembly, and deploying scalable computing environments with JupyterLite.
JupyterLab provides multiple ways to improve your coding workflow: code highlighting, code completion, theming, debugger with rich variable rendering and more.
Easily embed a console, a notebook, or a fully-fledged IDE on any web page.
Last year, we set ourselves to implement a visual debugger for JupyterLab. This endeavor required major developments in the JupyterLab front-end, in core-Jupyter protocols, and on the kernel side (the part of the Jupyter infrastructure responsible for executing the code).
Introducing a new Jupyter kernel for Robot Framework
Scientific visualization in the Jupyter notebook
Use Jupyter and 3D Slicer kernel to implement biomedical data processing workflows in a notebook.
As you may already know, the Jupyter Notebook and JupyterLab are Browser-based applications. Browsers are incredibly powerful, they allow you to swap rich and interactive graphical interfaces containing buttons, sliders, maps, 2D and 3D plots and even video games in your webpages!
As Jupyter grew in popularity, a broad ecosystem of visualization packages based on Jupyter widgets has been developed, bringing even more interactivity to the Jupyter world.
Project Jupyter aims at providing a consistent set of tools for interactive computing workflows across multiple programming languages. Jupyter projects are popular at all stages of a research project from the exploration phase to the communication of results and teaching.
The recent release of the Jupyter kernel for C++, based on the Cling interpreter enabled a number of new workflows for the users of the C++ programming language.
