Jupyter widgets, the interactive controls and widget libraries used in notebooks.
Welcome to the first part of a series of articles showing you how to create a dashboard in Jupyter and deploy it as a standalone web app. Importantly, you won’t need to rewrite your app in a different framework for deployment. We will use a pure Python solution with no JavaScript or CSS required.
Bringing the Power of OpenLayers to Jupyter.
Today, we are proud to announce that the ipydatagrid open source project has been incorporated into Project Jupyter as part of the Jupyter Widgets subproject.
anywidget is a Python library that makes it simple and enjoyable to create custom Jupyter Widgets that run in classic Jupyter notebooks, JupyterLite, JupyterLab, Google Colab, VS Code, and more.
A tutorial that demonstrates a zero-server, interactive 3D rendering notebook and walks through the quick and easy configuration that can be customized to your needs.
After a long break from in-person events, we are excited to announce an in-person Jupyter Community Workshop!
Ipycanvas + Box2D
When using a Jupyter Notebook to work on data science projects, I’ve found small user interface abstractions to be very useful. Scrubbing a slider or uploading a file can be more intuitive than editing a script and running it manually.
If there is one thing that recent events tell us, it is that genomics is a large source of data, and that its manipulation and understanding allow for the quick development of new drugs and… vaccines.
Diving into the implementation of xwidgets
Scientific visualization in the Jupyter notebook
The Jupyter widgets ecosystem offers a broad variety of data visualization tools for exploratory analysis in the notebook. However, we lack a good story for exploratory graph visualization.
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.
Creating complex layouts of widgets (button, sliders, maps, graphs etc.) can be cumbersome. New layout templates make this task a breeze.
Project Jupyter is a huge hit in data science, but it has not yet found widespread adoption in robotics. Today, we are releasing the first version of jupyter-ros, a collection of Jupyter interactive widgets inspired by Qt and RViz, to bring their features to the Jupyter ecosystem.
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.
A Hands-On Guide
We are pleased to announce the release of ipywidgets 6.0, the Jupyter interactive widget library. Jupyter interactive widgets enable building simple GUIs in the Jupyter notebook.
A version of ipywidget has been released, which fixes important security issues.
On April 19, 2016, we released ipywidgets 5.0. The ipywidgets package provides interactive HTML & JavaScript widgets (such as sliders, checkboxes, text boxes, charts, and more) for the Jupyter architecture that combine front-end controls coupled to a Jupyter kernel.
