Today’s release of ContainDS Dashboards 0.3.0 brings two eagerly-awaited features! User Permissions When creating a new dashboard, you can now choose whether to allow access to ‘All Users’ who are logged in to the JupyterHub, or just ‘Selected Users’: You can manually add whichever users you want to be able to view the dashboard. The […]
ContainDS Dashboards is a JupyterHub extension – which allows it to leverage the security and hosting standards provided by JupyterHub – but it doesn’t inherently require Jupyter notebooks to run. You can build dashboards based on Python or R scripts, to be served by Plotly Dash, Bokeh, Streamlit, or R Shiny Server for example. Until […]
If you’re using pure HoloViews objects to display charts in a Jupyter notebook, you might run into problems when trying to convert your notebook into a script to run directly in a Bokeh or Voila server. This post explains what goes wrong, and provides a workaround. The screenshots are from ContainDS Dashboards running in JupyterHub, […]
ContainDS Dashboards is an extension for JupyterHub allowing you to publish interactive visualizations for non-technical colleagues to try out. There are now a number of different open-source visualization frameworks supported out-of-the-box, and this post summarises those available, helping you decide which might be right for your project. Voila Voila is very closely related to Jupyter […]
The desktop application ‘ContainDS’ has now been rebranded as ‘ContainDS Desktop’. This is to distinguish it from the new ‘ContainDS Dashboards’ product which enables data scientists to share their data visualisations and prototypes online (cloud-based or on-premise) instantly, securely, and reliably. Please read more about ContainDS Dashboards here. To create simple shareable data science environments […]
Version 0.3.0 of ContainDS has some exciting new features! Streamlit Apps It is now possible to run Streamlit apps in ContainDS, easily starting new environments to develop and run your apps. When finished, export as a ‘containds’ file so you can share directly with your clients and colleagues. Then can import the file into ContainDS […]
The latest release of ContainDS (0.2.6) has some small but important changes to the way Jupyter containers are handled. Pull before Configuring A Docker image on Docker Hub may contain important configuration information which is unavailable to ContainDS until after it is pulled to the local machine. This might inform ContainDS about the correct way […]
In the new version 0.2.5 of ContainDS you can export the entire container as a ‘.containds’ file, including the environment (installed packages) and workspace. This file can be shared directly with a colleague or client who can import it straight into ContainDS running on their computer and use your container exactly as it was when […]
Today saw a minor release containing some code to catch an error that was seen in production whereby the ‘WEB’ button was unable to correctly obtain the URL of the container. Also, the current container selected in the list on the left-hand panel is now highlighted so you can see clearly which container you are […]
Version 0.2.3 of ContainDS adds ‘Local Folder’ as a dropdown option in the Binder tab when creating a new container. You can browse for the folder or just enter the full path directly: This requires that the folder contains a Binder-ready source tree, meaning it must have: the notebooks and/or data for your project, and […]