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python3-jupyter-packaging-0.12.3-1.lbn36.noarch
Jupyter Packaging Tools to help build and install Jupyter Python packages that require a pre-build step that may include JavaScript build steps. Install pip install jupyter-packaging Usage There are three ways to use jupyter-packaging in another package. In general, you should not depend on jupyter_packaging as a runtime dependency, only as a build dependency. As a Build Requirement Use a pyproject.toml file as outlined in pep-518. An example: [build-system] requires = ["jupyter_packaging>=0.10,<2"] build-backend = "setuptools.build_meta" Below is an example setup.py using the above config. It assumes the rest of your metadata is in setup.cfg. We wrap the import in a try/catch to allow the file to be run without jupyter_packaging so that python setup.py can be run directly when not building. from setuptools import setup try: from jupyter_packaging import wrap_installers, npm_builder builder = npm_builder() cmdclass = wrap_installers(pre_develop=builder, pre_dist=builder)
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python3-jupyter-polymake-0.16-18.20180129.7049940.fc36.noarch
This package contains a Jupyter kernel for polymake.
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python3-jupyter-polymake-0.16-18.20180129.7049940.fc36.noarch
This package contains a Jupyter kernel for polymake.
Located in LBN / … / Core Linux / BastionLinux 36
python3-jupyter-polymake-0.16-18.20180129.7049940.fc36.noarch
This package contains a Jupyter kernel for polymake.
Located in LBN / … / Data Science / BastionLinux 36
python3-jupyter-server-2.14.1-1.lbn36.noarch
Jupyter Server The Jupyter Server provides the backend (i.e. the core services, APIs, and REST endpoints) for Jupyter web applications like Jupyter notebook, JupyterLab, and Voila. For more information, read our documentation here. Installation and Basic usage To install the latest release locally, make sure you have pip installed and run: pip install jupyter_server Jupyter Server currently supports Python>=3.6 on Linux, OSX and Windows. Versioning and Branches If Jupyter Server is a dependency of your project/application, it is important that you pin it to a version that works for your application. Currently, Jupyter Server only has minor and patch versions. Different minor versions likely include API-changes while patch versions do not change API. When a new minor version is released on PyPI, a branch for that version will be created in this repository, and the version of the main branch will be bumped to the next minor version number. That way, the main branch always reflects the
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python3-jupyter-server-fileid-0.9.0-1.lbn36.noarch
jupyter_server_fileid A Jupyter Server extension providing an implementation of the File ID service. Requirements Jupyter Server Install To install the extension, execute: pip install jupyter_server_fileid Uninstall To remove the extension, execute: pip uninstall jupyter_server_fileid Troubleshoot If you are seeing the frontend extension, but it is not working, check that the server extension is enabled: jupyter server extension list Contributing Development install pip install -e . You can watch the source directory and run your Jupyter Server-based application at the same time in different terminals to watch for changes in the extension's source and automatically rebuild the extension. For example, when running JupyterLab: jupyter lab --autoreload If your extension does not depend a part
Located in LBN / … / Data Science / BastionLinux 36
python3-jupyter-server-kernels-0.1.2-1.lbn36.noarch
Jupyter Server Kernels Jupyter Server Kernels is a Jupyter Server Extension providing support for kernels.
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python3-jupyter-server-kernels-proxy-0.1.0-1.lbn36.noarch
Jupyter Server Kernels Proxy
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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/*
Located in LBN / … / Data Science / BastionLinux 36
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
Located in LBN / … / Data Science / BastionLinux 36

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