Code InsightĪs a full-fledged data science IDE, the DataSpell team is constantly working on enhancing code insight. The appearance of interactive outputs (Plotly, Bokeh, and others) has been adjusted to match the dark IDE theme, bringing them in line with the rest of the UI. This feature, in addition to a number of important bug fixes involving cell manipulations in command mode, makes changing the structure of notebooks easier and helps keep their structure clear. Cell output copy-pastingĬell outputs are now copy-pasted along with the cell sources. Our goal is to make cell outputs as easy to manipulate as the source code chunks, and provide interactivity and visual appeal at the same time. The ability to readily explore computation results is one of the cornerstones of interactive programming with Jupyter. You can use the context menu or keyboard shortcuts to copy and paste files. This simplifies the exchange of data and notebooks, and it helps you keep your projects in sync. You can also copy them between two remote Jupyter instances. With DataSpell 2022.1, you can copy local files to a remote Jupyter instance and vice versa.
Copying files to and from remote Jupyter servers Choose File | Add Jupyter connection…, paste the JupyterHub server URL, and work with Jupyter notebooks right from DataSpell. DataSpell 2022.1 has adopted the API changes of the new version and allows connections to JupyterHub 2.0 by URL the same way connections work for Jupyter and JupyterHub 1.0 servers.
Dataspell cost upgrade#
JupyterHub, a platform that provides multi-user access to remote Jupyter servers, has received a major upgrade with version 2.0, which introduced roles and scopes. To ensure you can adopt this trend, the new DataSpell release brings improvements for your remote Jupyter workflows.
Network accessible Jupyter servers allow access to shared data and computational resources, providing the ability to collaborate with your teammates. Over the past few years, usage of remote servers for computation and data storage has increased throughout the industry – the fields of data analysis and machine learning are no exception. Go through the detailed feature descriptions below, give the new release a try, and share your feedback and feature requests with us via our issue tracker and Slack! Last but not least: if you’ve never tried DataSpell and are wondering how its Jupyter notebooks’ features look, or just want a quick recap, it’s now easier than ever with the Onboarding Tour embedded right in the IDE. Interactive graphics like Plotly and Bokeh now use the same theme as the IDE does, making it visually appealing for those who use dark themes. Cell outputs received a number of fixes, making work with interactive tables smoother. Writing code in Jupyter is now enhanced by the completion provided by Jupyter runtime and the superclasses extraction action Python script users are familiar with. Further support for notebook cell manipulations with fixes for cell output copy-pasting and group cell manipulations like code to markdown cell conversions have been added. Both local and remote Jupyter notebooks now handle kernel restart requests better. Improvements to the way DataSpell interacts with remote Jupyter servers brought the inclusion of JupyterHub 2.0 support, as well as the ability to copy files from the local machine to remote Jupyter right in the workspace.
We’ve received a lot of feedback since then and are doing our best to address it with new features and fixes coming with the new DataSpell 2022.1 release. It’s been quite a while since we released the first public version of DataSpell back in November 2021. Valeria Letusheva JupyterHub 2.0 support, the ability to copy files to remote Jupyter servers, runtime completion, and the DataSpell Onboarding Tour
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