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Visualizing Data via Deno, TypeScript, and VegaLite in JupyterLab Deno brings TypeScript, JavaScript, npm, and ES Modules to Jupyter with an easy to install kernel. The Deno Kernel is the first language runtime with a builtin jupyter kernel. There’s no better time to get started with Deno than now. Once deno is installed, run the deno jupyter kernel installation: deno jupyter --unstable --install
The Jupyter contributor community is proud to announce JupyterLab 4.0, the next major release of our full-featured development environment. The package is now available on PyPI and conda-forge. You can upgrade by running pip install --upgrade jupyterlab or conda install -c conda-forge jupyterlab. We have updated our JupyterLab Documentation for this new version. Here are some of the major new feat
Introducing the new JupyterLab Desktop!We are pleased to announce a major update to JupyterLab Desktop which adds many new features with main focus on the user experience. JupyterLab Desktop is the cross-platform desktop application for JupyterLab and it is the quickest and easiest way to get started with Jupyter notebooks on your personal computer. JupyterLab DesktopWelcome PageUsers are now pres
The Open Source Jupyter team at AWS is proud to announce the release of Jupyter Scheduler, a JupyterLab extension that can run your Jupyter notebooks in the background. Jupyter Scheduler was developed from the start as an open-source project under the umbrella of the Jupyter project and governance. You can set up your notebooks to run once or on a schedule. By default, Jupyter Scheduler runs noteb
We are pleased to announce the release of desktop application for JupyterLab! Standalone and self-containedJupyterLab App is the cross-platform standalone application distribution of JupyterLab. It is a self-contained desktop application which bundles a Python environment with several popular Python libraries ready to use in scientific computing and data science workflows. JupyterLab App running o
Jupyter is a fantastic tool for data exploration. The ability to transform our data interactively and get immediate visual feedback allows us to understand it quickly. However, when working on large projects, collaboration can become difficult. Features such as live collaboration are a gigantic leap forward for teamwork. Still, it has to complement an asynchronous workflow that allows team members
JupyterLite is a JupyterLab distribution that runs entirely in the web browser, backed by in-browser language kernels. MotivationJupyterLite is a reboot of several attempts at making a full static Jupyter distribution that runs in the browser, without having to start the Python Jupyter Server on the host machine, usually done by running jupyter lab or jupyter notebook in a terminal. The goal of th
Jupyter notebooks are mostly known for their web-based user interface, such as JupyterLab or the Classic Notebook. They offer a great user experience, allow for rich output rendering, provide interactivity through e.g. widgets, and make possible working with remote kernels. If just like me you tend to never leave the terminal in your workflow, you may be missing a tool to interact with Jupyter not
The 3.0 release of JupyterLab brings many new features to users and substantial improvements to the extension system. InstallationTo install JupyterLab with pip: pip install jupyterlab==3With mamba: mamba install -c conda-forge jupyterlab=3With conda: conda install -c conda-forge jupyterlab=3(Note that many third-party extensions are still in the process of updating to be compatible with JupyterLa
Jupyter Book is an open source project for building beautiful, publication-quality books, websites, and documents from source material that contains computational content. With this post, we’re happy to announce that Jupyter Book has been re-written from the ground up, making it easier to install, faster to use, and able to create more complex publishing content in your books. It is now supported
Building on a Jupyter Notebooks foundation, the de facto tool for data scientists, machine learning engineers and AI developers, Elyra is an open-source project that provides a set of AI-centric extensions to JupyterLab aiming to help users through the model development life cycle complexities, making JupyterLab even better for AI practitioners. Elyra is proud to announce its 1.0.0 Release. This r
While it is well known in the Python scientific computing community, Jupyter is in fact a language-agnostic development environment. High-quality language kernels exist for the main languages of data sciences, such as Python, C++, R or Julia. But another important tool for data science is the SQL family of programming languages. Today, we announce the release of a Jupyter kernel for SQLite. This n
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. Cytoscape is an open-source software platform for visualizing complex networks and integrating these with any type of attribute data. While it comes from the computational biology community, cytoscape is fully-
Most of the progress made in software projects comes from incrementalism. The ability to quickly see the outcome of an execution and iterate has been one of the main reasons for the success of Jupyter, especially in scientific exploratory workflows. Jupyter users like to experiment in the notebook, and to use the notebook as an interactive communication tool. However, for more classical software d
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! All this power is readily made available to the Python ecosystem by Jupyter interactive widgets libraries. Whether you
Notebooks come alive with Jupyter widgets, which allow users to produce interactive GUIs inline in the Jupyter notebook or JupyterLab. You can either use them to add a few interactive controls and plots in notebooks or to create fully-fledged applications and interactive dashboards. Both can be built with components from the core built-in widgets such as buttons, sliders, and dropdowns, or with th
… from Jupyter notebooks to standalone applications and dashboards The goal of Project Jupyter is to improve the workflows of researchers, educators, scientists, and other practitioners of scientific computing, from the exploratory phase of their work to the communication of the results. But interactive notebooks are not the best communication tool for all audiences. While they have proven invalua
Today, we are pleased to announce the 1.0 release of JupyterHub. We’ve come a long way since our first release in March, 2015. There are loads of new features and improvements covered in the changelog, but we’ll cover a few of the highlights here. You can upgrade jupyterhub with conda or pip: (Before upgrading, always make sure to backup your database!) conda install -c conda-forge jupyterhub==1.0
This may be the right time for Jupyter-based developer tools, as cloud robotics is taking off.A PR2 robot in the browser, and making him dance through the traditional Qt interfaceHistorically, the ROS (Robot Operating System) community has relied on Qt for building complex user interfaces. Nowadays, the Jupyter notebook and the ipywidgets framework offer a compelling alternative for several reason
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 flagship project of Jupyter, the Notebook, and its modernized version, JupyterLab are web applications allowing the creatio
Jupyter is now widely used for teaching and research. The use of Kubernetes for deploying a JupyterHub has enabled reliable setups scaling to thousands of users. There are many cloud computing vendors (Google, Amazon, …) and the first attempts to use JupyterHub with Kubernetes is based on them. But relying on vendor clouds increases the risk of vendor lock-in. In addition, there are many pre-exist
This article is the first in a series of guest blog posts about open source projects in the Jupyter ecosystem and the problems they attempt to solve. If you would like to submit a guest post to highlight a specific tool or project, please get in touch with us. Jupyter Notebooks go a long way towards making computations reproducible and sharable. Nevertheless, for many Jupyter users, it remains a c
It is our pleasure to announce that Project Jupyter has been awarded the 2017 ACM Software System Award, a significant honor for the project. We are humbled to join an illustrious list of projects that contains major highlights of computing history, including Unix, TeX, S (R’s predecessor), the Web, Mosaic, Java, INGRES (modern databases) and more. Officially, the recipients of the award are the f
JupyterLab viewing LaTeX source code and a PDF documentThe new JupyterLab interface is much more than a replacement for the classic notebook. It aims to bring together all the pieces required for a complete scientific workflow. The extension-based architecture of JupyterLab comes with a number of components already enabled: a Jupyter notebook,a text editor,a file browser in the sidebar,a number of
Plug your application into the Jupyter worldKernels are a simple but powerful abstraction in the Jupyter architecture. They…
We are proud to announce the beta release series of JupyterLab, the next-generation web-based interface for Project Jupyter. tl;dr: JupyterLab is ready for daily use (installation, documentation, try it with Binder) JupyterLab is an interactive development environment for working with notebooks, code, and data.The Evolution of the Jupyter NotebookProject Jupyter exists to develop open-source softw
Scientists, educators and engineers not only use programming languages to build software systems, but also in interactive workflows, using the tools available to explore a problem and reason about it. Running some code, looking at a visualization, loading data, and running more code. Quick iteration is especially important during the exploratory phase of a project. For this kind of workflow, users
Open Community CallWe want to see all the cool things you’re doing with Jupyter, so we’re holding an open call with the community for people to chat, and share their creations and work. Think of it as a “virtual JupyterCon”: It’s a place to announce and share fun things happening in the Jupyter community.
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