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python3-jupyter-server-kernels-proxy-0.1.0-1.lbn36.noarch
Jupyter Server Kernels Proxy
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BastionLinux 36
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python3-jupyter-server-mathjax-0.2.6-1.lbn36.noarch
MathJax resources endpoints for Jupyter Server
Basic Usage
Install from PyPI:
> pip install jupyter_server_mathjax
This will automatically enable the extension in Jupyter Server.
To test the installation, you can run Jupyter Server and visit the /static/jupyter_server_mathjax/MathJax.js endpoint:
> jupyter server
Maintenance Notes
To install an editable install locally for development, first clone the repository locally,
then run:
`pip install -e .[test]`
Note that the editable install will not install the data file that
automatically configures the extension for use. To manually enable it, run:
jupyter server extension enable --py jupyter_server_mathjax
To build for distribution, use the build package:
pip install build
python -m build
Then release using twine:
twine check dist/*
twine check dist/*
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python3-jupyter-server-proxy-4.1.0-1.lbn36.noarch
Jupyter Server Proxy
Jupyter Server Proxy lets you run arbitrary external processes (such as
RStudio, Shiny Server, Syncthing, PostgreSQL, Code Server, etc)
alongside your notebook server and provide authenticated web access to
them using a path like /rstudio next to others like /lab. Alongside
the python package that provides the main functionality, the JupyterLab
extension (@jupyterhub/jupyter-server-proxy) provides buttons in the
JupyterLab launcher window to get to RStudio for example.
Note: This project used to be called nbserverproxy. As
nbserverproxy is an older version of jupyter-server-proxy, uninstall
nbserverproxy before installing jupyter-server-proxy to avoid conflicts.
The primary use cases are:
Use with JupyterHub / Binder to allow launching users into web
interfaces that have nothing to do with Jupyter - such as RStudio,
Shiny, or OpenRefine.
Allow access from frontend javascript (in classic notebook or
JupyterLab extensions) to access web APIs of other processes
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BastionLinux 36
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python3-jupyter-server-proxy-noe-1.1-1.lbn36.noarch
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BastionLinux 36
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python3-jupyter-server-terminals-0.4.4-1.lbn36.noarch
Jupyter Server Terminals
Jupyter Server Terminals is a Jupyter Server Extension providing support for terminals.
Installation and Basic usage
To install the latest release locally, make sure you have
pip installed and run:
pip install jupyter_server_terminals
Jupyter Server Terminals currently supports Python>=3.6 on Linux, OSX and Windows.
Testing
See CONTRIBUTING.
Contributing
If you are interested in contributing to the project, see CONTRIBUTING.
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BastionLinux 36
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python3-jupyter-server-terminals-proxy-0.1.4-1.lbn36.noarch
Jupyter Server Terminals Proxy
In one terminal/environment:
pip install fps_uvicorn
pip install fps_terminals
pip install fps-noauth
fps-uvicorn --port=8000 --no-open-browser
In another terminal/environment:
pip install jupyter_server_terminals_proxy
pip install jupyterlab
jupyter lab --port=8888 --ServerApp.terminals_enabled=False --TerminalsProxyExtensionApp.proxy_url='http:/127.0.0.1:8000'
Terminals should now be served from http:/127.0.0.1:8000.
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python3-jupyter-server-widget-0.1.2-1.lbn36.noarch
Jupyter Server WidgetJupyter Notebook %magics and Widget to start and stop
servers from a CellLoad extension inside a Jupyter notebook: %load_ext
jupyterserverwidget Add server commands with cell magic: %server myserver1
--args myargs%servers myserver1 --args myargs myserver2 --args myargs Click
buttons to start them, click again to stop. Installation...
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BastionLinux 36
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python3-jupyter-server-xarray-leaflet-0.2.3-1.lbn36.noarch
A Jupyter Server extension for xarray-leaflet
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BastionLinux 36
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python3-jupyter-spark-0.3.0-1.lbn19.noarch
[](https://travis-ci.org/mozilla/jupyter-spark)
[](https://codecov.io/gh/mozilla/jupyter-
spark)
Jupyter Notebook extension for Apache Spark integration.
Includes a
progress indicator for the current Notebook cell ...
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BastionLinux 19
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python3-jupyter-sphinx-0.3.2-3.fc36.noarch
Jupyter-Sphinx enables running code embedded in Sphinx documentation and
embedding output of that code into the resulting document. It has
support for rich output such as images and even Jupyter interactive
widgets.
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