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transient-display-data
Advanced tools
transient-display-data
for Jupyter LabThis is a JupyterLab extension that allows JupyterLab to receive messages in a new
transient_display_data
type
and display them in the console window of the associted notebook.
As summarized here,
the transient display data messages are designed to send messages that are transient
in nature and will not be displayed and saved with the notebooks. Such messages
include but not limited to status or progress information for long calculations, and
debug information. This message type is identical to display_data
in content so you
only need to use message type transient_display_data
instead of display_data
to
mark the message as transient.
This new message type is currently under review. However, even before it is officially accepted, kernels can send messages of this type safely because all Jupyter clients ignore messages of unknown types, and JupyterLab with this extension will be able to display them. An an example, the SoS Kernel uses this message type to send progress information during the execution of the SoS workflows.
conda install jupyterlab-transient-display-data -c conda-forge
transient-display-data
extension using command
jupyter labextension install transient-display-data
or go to the extension manager, search for transient-display-data
, and install.transient_display_data
After you installed this extention, you can test it by
New Console for Notebook
to create a console windowShow Transient Message
.kernel = get_ipython().kernel
kernel.send_response(kernel.iopub_socket,
'transient_display_data',
{
'data': {
'text/plain': 'I am transient'
}
}
);
and a message I am transient
should be displayed in the console window.
%run
[1]
[2]
[3]
You can see progress messages in the console window.
FAQs
Extension to display transient_display_data in Jupyter Lab
The npm package transient-display-data receives a total of 7 weekly downloads. As such, transient-display-data popularity was classified as not popular.
We found that transient-display-data demonstrated a not healthy version release cadence and project activity because the last version was released a year ago. It has 1 open source maintainer collaborating on the project.
Did you know?
Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.
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