Saravanan666/pypi-org huggingface dataset:
Package: jupyter-remote-desktop-proxy
Jupyter Remote Desktop ProxyRun XFCE (or other desktop environments) on Jupyter.This is based onhttps://github.com/ryanlovett/nbnovnc.When this extension is launched it will run a Linux desktop on the Jupyter single-user server, and proxy it to your browser using VNC via Jupyter.If avncserverexecutable is found inPATHit will be used, otherwise a bundled TightVNC server is run.
You can use this to install vncserver with support for other features, for example theDockerfilein this repository installs TurboVNC for improved OpenGL support.InstallationInstall this package itself, withpipfromPyPI:pipinstalljupyter-remote-desktop-proxyInstall thewebsockifydependency. Unfortunately,
the PyPIwebsockifypackage is broken, so you need to install it either
fromconda-forgeor withaptInstall the packages needed to provide the actual Linux Desktop environment.
You need to pick a desktop environment (there are many!) - here is the packages
you would need for using the light-weightXFCE4desktop environment:dbus-x11
libgl1-mesa-glx
xfce4
xfce4-panel
xfce4-session
xfce4-settings
xorg
xubuntu-icon-themeThe recommended way to install these is from your Linux system package manager
of choice (such as apt).DockerTo spin up such a notebook first build the container:$dockerbuild-t$(whoami)/$(basename${PWD}).Now you can ran the image:$dockerrun--rm--security-optseccomp=unconfined-p8888:8888$(whoami)/$(basename${PWD})Executingthecommand:jupyternotebook[I12:43:59.148NotebookApp]Writingnotebookservercookiesecretto/home/jovyan/.local/share/jupyter/runtime/notebook_cookie_secret[I12:44:00.221NotebookApp]JupyterLabextensionloadedfrom/opt/conda/lib/python3.7/site-packages/jupyterlab[I12:44:00.221NotebookApp]JupyterLabapplicationdirectoryis/opt/conda/share/jupyter/lab[I12:44:00.224NotebookApp]Servingnotebooksfromlocaldirectory:/home/jovyan[I12:44:00.225NotebookApp]TheJupyterNotebookisrunningat:[I12:44:00.225NotebookApp]http://924904e0a646:8888/?token=40475e553b7671b9e93533b97afe584fa2030448505a7d83[I12:44:00.225NotebookApp]orhttp://127.0.0.1:8888/?token=40475e553b7671b9e93533b97afe584fa2030448505a7d83[I12:44:00.225NotebookApp]UseControl-Ctostopthisserverandshutdownallkernels(twicetoskipconfirmation).[C12:44:00.229NotebookApp]Toaccessthenotebook,openthisfileinabrowser:file:///home/jovyan/.local/share/jupyter/runtime/nbserver-8-open.htmlOrcopyandpasteoneoftheseURLs:http://924904e0a646:8888/?token=40475e553b7671b9e93533b97afe584fa2030448505a7d83orhttp://127.0.0.1:8888/?token=40475e553b7671b9e93533b97afe584fa2030448505a7d83
*snip*Now head to the URL shown and you will be greated with a XFCE desktop.Note the--security-opt seccomp=unconfinedparameter - this is necessary
to start daemons (such as dbus, pulseaudio, etc) necessary for linux desktop
to work. This is the option kubernetes runs with by default, so most kubernetes
based JupyterHubs will not need any modifications for this to work.LimitationsDesktop applications that require access to OpenGL are currently unsupported.
Package: jupyter-reorder-python-imports
jupyter-reorder-python-importsreorder-python-importsis a great library. Now available in Jupyter notebook and lab.What does it do?Once loaded, automatically format python imports according to reorder-python-imports using theirformatting methods.Quickstartpython -m pip install jupyter-reorder-python-importsImport into Jupyter using two methods:%load_ext jupyter_reorder_python_importsOr,import jupyter_reorder_python_imports

jupyter_reorder_python_imports.load()The latter method allows for specifying the minimum python version (as a tuple of integers) to be used forremoving obsolete__future__imports. For example,jupyter_reorder_python_imports.load(min_python_version=(3,9))specifies 3.9 as the minimum python version.See theexamplesfolder for some examples.TestingTests use playwright. Prior to running the tests execute:python -m playwright install --with-deps firefoxIf desired, pass the--no-headlessflag to pytest for local debugging.ContributionsTODO:Improve testingRead configuration from pyproject.toml
Package: jupyter-repo2docker
repo2dockerrepo2dockerfetches a git repository and builds a container image based on
the configuration files found in the repository.See therepo2docker documentationfor more information on using repo2docker.For support questions please search or post tohttps://discourse.jupyter.org/c/binder.See thecontributing guidefor information on contributing to
repo2docker.Please note that this repository is participating in a study into sustainability
of open source projects. Data will be gathered about this repository for
approximately the next 12 months, starting from 2021-06-11.Data collected will include number of contributors, number of PRs, time taken to
close/merge these PRs, and issues closed.For more information, please visitour informational pageor download ourparticipant information sheet.Using repo2dockerPrerequisitesDocker to build & run the repositories. Thecommunity editionis recommended.Python 3.6+.Supported on Linux and macOS.See documentation note about Windows support.InstallationThis a quick guide to installingrepo2docker, see our documentation fora full guide.To install from PyPI:pipinstalljupyter-repo2dockerTo install from source:gitclonehttps://github.com/jupyterhub/repo2docker.gitcdrepo2docker
pipinstall-e.UsageThe core feature of repo2docker is to fetch a git repository (from GitHub or locally),
build a container image based on the specifications found in the repository &
optionally launch the container that you can use to explore the repository.Note that Docker needs to be running on your machine for this to work.Example:jupyter-repo2dockerhttps://github.com/norvig/pytudesAfter building (it might take a while!), it should output in your terminal
something like:Copy/pastethisURLintoyourbrowserwhenyouconnectforthefirsttime,tologinwithatoken:http://0.0.0.0:36511/?token=f94f8fabb92e22f5bfab116c382b4707fc2cade56ad1ace0If you copy paste that URL into your browser you will see a Jupyter Notebook
with the contents of the repository you had just built!For more information on how to userepo2docker, see theusage guide.Repository specificationsRepo2Docker looks for configuration files in the source repository to
determine how the Docker image should be built. For a list of the configuration
files thatrepo2dockercan use, see thecomplete list of configuration files.The philosophy of repo2docker is inspired byHeroku Build Packs.Docker ImageRepo2Docker can be run inside a Docker container if access to the Docker Daemon is provided, for example seeBinderHub. Docker images arepublished to quay.io. The oldDocker Hub imageis no longer supported.
Package: jupyter-requests
Jupyter RequestsSend requests to a Jupyter server. Useful for testing/exploring the Jupyter RESTful API.Command LineMake a request to a jupyter server from the command line.jupyter_requests get api/contentsAPIfromjupyter_requestsimportJupyterRequesterimportpprint# Port number of the serverport=8888# Get a requester object.r=JupyterRequester(port=port)endpoint='api/contents'response=r.get(endpoint)pprint(response)
Package: jupyter_resource_usage_proxy
Jupyter Resource Usage ProxyIn one terminal/environment:pip install fps_uvicornpip install fps_resource_usagepip install fps-noauth#launchaterminalserverathttp://127.0.0.1:8000fps-uvicorn --port=8000 --no-open-browserIn another terminal/environment:pip install jupyter_resource_usagepip install jupyter_resource_usage_proxypip install jupyterlab#launchJupyterLabathttp://127.0.0.1:8888,deactivatetheresourceusageserverextension,andproxyresourceusageathttp://127.0.0.1:8000jupyter lab --port=8888 --ServerApp.jpserver_extensions="jupyter_resource_usage=False" --ResourceUsageProxyExtensionApp.proxy_url='http://127.0.0.1:8000'Resource usage should now be served fromhttp://127.0.0.1:8000.
Package: jupyter-rightbar-doc
jupyter-rightbar-docA JupyterLab extension.RequirementsJupyterLab >= 3.0Installpipinstalljupyter-rightbar-docContributingDevelopment installNote: You will need NodeJS to build the extension package.Thejlpmcommand is JupyterLab's pinned version ofyarnthat is installed with JupyterLab. You may useyarnornpmin lieu ofjlpmbelow.# Clone the repo to your local environment# Change directory to the jupyter-rightbar-doc directory# Install package in development modepipinstall-e.# Link your development version of the extension with JupyterLabjupyterlabextensiondevelop.--overwrite# Rebuild extension Typescript source after making changesjlpmrunbuildYou can watch the source directory and run JupyterLab at the same time in different terminals to watch for changes in the extension's source and automatically rebuild the extension.# Watch the source directory in one terminal, automatically rebuilding when neededjlpmrunwatch# Run JupyterLab in another terminaljupyterlabWith the watch command running, every saved change will immediately be built locally and available in your running JupyterLab. Refresh JupyterLab to load the change in your browser (you may need to wait several seconds for the extension to be rebuilt).By default, thejlpm run buildcommand generates the source maps for this extension to make it easier to debug using the browser dev tools. To also generate source maps for the JupyterLab core extensions, you can run the following command:jupyterlabbuild--minimize=FalseUninstallpipuninstalljupyter-rightbar-doc
Package: jupyter-rospkg
jupyter-rospkgA server extension for JupyterLab to handle ROS packagesThis extension is composed of a Python package namedjupyter_rospkgfor the server extension.RequirementsJupyterLab >= 3.0InstallTo install the extension, execute:pipinstalljupyter_rospkgUninstallTo remove the extension, execute:pipuninstalljupyter_rospkgTroubleshootIf it is not working, check that the server extension is enabled:jupyterserverextensionlistContributingDevelopment installNote: You will need NodeJS to build the extension package.Thejlpmcommand is JupyterLab's pinned version ofyarnthat is installed with JupyterLab. You may useyarnornpmin lieu ofjlpmbelow.# Clone the repo to your local environment# Change directory to the jupyter_rospkg directory# Install package in development modepipinstall-e.# Server extension must be manually installed in develop modejupyterserverextensionenablejupyter_rospkgYou can watch the source directory and run JupyterLab at the same time in different terminals to watch for changes in the extension's source and automatically rebuild the extension.# Watch the source directory in one terminal, automatically rebuilding when neededjlpmwatch# Run JupyterLab in another terminaljupyterlabWith the watch command running, every saved change will immediately be built locally and available in your running JupyterLab. Refresh JupyterLab to load the change in your browser (you may need to wait several seconds for the extension to be rebuilt).By default, thejlpm buildcommand generates the source maps for this extension to make it easier to debug using the browser dev tools. To also generate source maps for the JupyterLab core extensions, you can run the following command:jupyterlabbuild--minimize=FalseDevelopment uninstall# Server extension must be manually disabled in develop modejupyterserverextensiondisablejupyter_rospkg
pipuninstalljupyter_rospkgIn development mode, you will also need to remove the symlink created byjupyter labextension developcommand. To find its location, you can runjupyter labextension listto figure out where thelabextensionsfolder is located. Then you can remove the symlink namedjupyter-rospkgwithin that folder.Testing the extensionServer testsThis extension is usingPytestfor Python code testing.Install test dependencies (needed only once):pipinstall-e".[test]"To execute them, run:pytest-vv-rap--covjupyter_rospkgPackaging the extensionSeeRELEASE
Package: jupyter-rstudio-singularity
jupyter-rstudio-singularityLaunch RStudio with Singularity from the command line.Free software: Apache Software License 2.0Documentation:https://jupyter-rstudio-singularity.readthedocs.io.FeaturesTODOCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.0 (2023-01-23)First release on PyPI.
Package: jupyter-rtc-test
Jupyter RTC Test📶 Stress tests for 🪐 Jupyter 🔌 Real Time Collaboration (RTC).The goal of this repository is to stress test the Real Time Collaboration (RTC) feature of JupyterLab and Jupyter Server and is a needed requirementto avoid users having issues when they enable RTC.The current list of discovered issues ismaintained on this page.The tests aims to replicate real life cases, meaning that most of them are running in a distrbuted way. You can run the test on a standalone (local laptop or CI) machine, in which case the distributed behavior is simulated.You can also run the tests in a real a distributed environment like Kubernetes, this however requires you to setup additional infrastructure and configuration. Please note you can also run the Kubernetes flavored tests on a local Minikube instance.InstallInstallthe tool directly from PyPI andlaunch itfrom the command line.DevelopSetup yourenvironmentto run thetests.You can also use theuser interfacesif you prefer.⚖️ LicenseCopyright (c) 2023 Datalayer, Inc.Released under the terms of the BSD 3-Clause license (seeLICENSE).This repository contains source code taken from the various repositories underBSD-3orMITlicense.
Package: jupyter-run
🪐 🏃 Jupyter Runyarn#  "installConfig": {#    "hoistingLimits": "workspaces"#  },yarnbuild# open http://localhost:3063# open http://localhost:8888/api/jupyter/lab?token=60c1661cc408f978c309d04157af55c9588ff9557c9380e4fb50785750703da6yarnstartpipinstall-e.[test]jupyterlabextensiondevelop.--overwrite
jupyterlabextensionlist
jupyterserverextensionlist# open http://localhost:8888/api/jupyter/lab?token=60c1661cc408f978c309d04157af55c9588ff9557c9380e4fb50785750703da6yarnjupyterlab
Package: jupyter-saagie-plugin
This plugin allows you to easily create a Saagie Python job from a local
Jupyter notebook.InstallIn your Jupyter Python environment, run:pip installjupyter-saagie-pluginUsageSimply runjupyter notebookas always, you will see a new button in
the toolbar. Use it to log in to your account and deploy a job using the
code in your notebook. You can update an existing job as well.For deploying to a Python job, Python 3.5 & 2.7 are supported.If you want to pre-fill your Saagie root URL (used in the plugin’s login
form), you can setup aSAAGIE_ROOT_URLenvironment variable before
you run the notebook.Uninstallpip uninstall jupyter-saagie-plugin
jupyter nbextension uninstall saagie --userModifying this extensionIn dev mode, you can use a Docker of Jupyter notebook and install this
extension in it. First, run a Jupyter Docker in bash mode:docker run -it --rm -p 8888:8888 --user root -e GRANT_SUDO=yes -v [your_project_path]/jupyter-saagie-plugin/:/jupyter-saagie-plugin/ [--env SAAGIE_ROOT_URL="https://xxx-manager.prod.saagie.io/"] saagie/jupyter-python-nbk:latest /bin/bash(Seting up the ``SAAGIE_ROOT_URL`` environment variable is optional)Then install the Jupyter extension in your Docker container:cd /jupyter-saagie-plugin/
python3 setup.py install
cd /notebooks-dir
/usr/local/bin/start-notebook.sh --NotebookApp.token='' --NotebookApp.password=''Build and shareIn order to build this plugin, run the following command:python setup.py sdistThis will generate a tar.gz archive in thedistdirectory.If you want to share it on Pypi, just installtwine(withpip install twine) and run:twine upload dist/jupyter-saagie-plugin-x.x.x.tar.gzBut first, You can test your Pypi deployment onTestPypitest environment. If so,
just run:twine upload --repository-url https://test.pypi.org/legacy/ dist/jupyter-saagie-plugin-x.x.x.tar.gz
Package: jupyterscad
Jupyter SCAD: SCAD in JupyterJupyter SCAD provides rendering and interactive visualization for 3D objects described inSolidPython2within a Jupyter notebook. Additionally, it provides interactive visualization for STLs.This program is focused on the use case of generating stl files with Python (aka SolidPython2) interactively within a Jupyter notebook.DocumentationDocumentation is hosted athttps://jreiberkyle.github.io/jupyterscad/.Quick StartJupyter SCAD can be installed withpip:pip install jupyterscadAn OpenSCAD object can be defined using SolidPython2, viewed in a Jupyter
notebook, and saved to anstlfile with:fromjupyterscadimportviewfromsolid2importcubeview(cube([1.5,2,1],center=True),outfile='cube.stl')AlternativesAs an alternative to Jupyter SCAD, one could use a Jupyter notebook as an external editor, using SolidPython2 to update the SCAD file and OpenSCAD to visualize and render the SCAD file.
The benefit to this approach is that one can visualize the preview. The drawback is that the two-program workflow can feel distracting.
See more on using external editors for OpenSCADhere.Or, one can useViewSCAD, which was the motivation for this project. However the last time ViewSCAD was updated was 2019 (checked on 9/21/2023). It only supports SolidPython, not SolidPython2.Transitioning from ViewSCADThis package was inspired byViewSCADand therefore
maintains a very similar interface.To transition from ViewSCAD, replaceimportviewscadr=viewscad.Renderer()r.render(obj)withfromjupyterscadimportviewview(obj)Visualization BackendThis package usespythreejsfor visualization.Alternatives considered, ordered from closest fit to farthest:pyvolume: provides mesh visualization and interaction but (as of 2023.09.24) the latest release is alpha and documentation is sparse.matplotlib mplot3d: provides mesh visualization and interaction but is slow.pyvista: provides stl loading and visualization but visualization does not work in docker image.AcknowledgementsThanks tonickc92for creatingViewSCAD, which is the inspiration for this project.
Package: jupyter-scdg-viewer-widget
SCDG Viewer WidgetJupyter Notebook Widget to view SCDG in the form of graph.This widget project was initialized using the very handy Cookiecuttertemplate.ExampleInstallationTo install use pip:$ pip install jupyter-scdg-viewer-widget
$ jupyter nbextension enable --py --sys-prefix scdgviewerTo install for jupyterlab$ jupyter labextension install scdgviewerFor a development installation (requires npm),$ git clone git@gitlab.inria.fr:TAMIS/madlab/jupyter-scdg-viewer-widget.git
$ cd jupyter-scdg-viewer-widget
$ pip install -e .
$ jupyter nbextension install --py --symlink --sys-prefix scdgviewer
$ jupyter nbextension enable --py --sys-prefix scdgviewer
Package: jupyter-scheduler
jupyter_schedulerA JupyterLab extension for running notebook jobs. Documentation is available onReadTheDocs.This extension is composed of a Python package namedjupyter_schedulerfor the server extension and a NPM package named@jupyterlab/schedulerfor the frontend extension. Installation of this extension provides a
REST API to run, query, stop and delete
notebook jobs; the UI provides an interface to create, list and view job
details.RequirementsJupyterLab >= 3.0InstallTo install the extension, execute:pipinstalljupyter_schedulerUninstallTo remove the extension, execute:pipuninstalljupyter_schedulerUser's guidePlease refer to ouruser's guidefor more information on installation and usage.ContributingPlease refer to ourcontributor's guidefor more information on installation and usage.
Package: jupyter-security
Jupyter Securitypipinstall-e.[test]jupyterlabextensiondevelop.--overwrite
jupyterlabextensionlist
jupyterserverextensionlist# open http://localhost:8686/api/jupyter/lab?token=60c1661cc408f978c309d04157af55c9588ff9557c9380e4fb50785750703da6yarnjupyterlab
Package: jupyter-sequor
jupyter-sequorFollow and scroll automatically cell outputs in Jupyter notebooksInstallationpipinstalljupyter-sequorUsageA minimal example:NOTE: The example requires additional packagelorem.importloremimporttimeforainrange(0,200,10):text=lorem.text()print(text)time.sleep(0.2)Note that theFollowbutton appears only when the cell enters ascrolledstate.Feel free to enable/disable the follow on a cell level by clicking the button.
Package: jupyter-server
Jupyter ServerThe 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 ourdocumentation here.Installation and Basic usageTo install the latest release locally, make sure you havepip installedand run:pip install jupyter_serverJupyter Server currently supports Python>=3.6 on Linux, OSX and Windows.Versioning and BranchesIf 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 latest un-released version.To see the changes between releases, checkout theCHANGELOG.Usage - Running Jupyter ServerRunning in a local installationLaunch with:jupyter serverTestingSeeCONTRIBUTING.ContributingIf you are interested in contributing to the project, seeCONTRIBUTING.rst.Team Meetings and RoadmapWhen: Thursdays8:00am, Pacific timeWhere:Jovyan ZoomWhat:Meeting notesSee our tentativeroadmap here.About the Jupyter Development TeamThe Jupyter Development Team is the set of all contributors to the Jupyter project.
This includes all of the Jupyter subprojects.The core team that coordinates development on GitHub can be found here:https://github.com/jupyter/.Our Copyright PolicyJupyter uses a shared copyright model. Each contributor maintains copyright
over their contributions to Jupyter. But, it is important to note that these
contributions are typically only changes to the repositories. Thus, the Jupyter
source code, in its entirety is not the copyright of any single person or
institution. Instead, it is the collective copyright of the entire Jupyter
Development Team. If individual contributors want to maintain a record of what
changes/contributions they have specific copyright on, they should indicate
their copyright in the commit message of the change, when they commit the
change to one of the Jupyter repositories.With this in mind, the following banner should be used in any source code file
to indicate the copyright and license terms:# Copyright (c) Jupyter Development Team.
# Distributed under the terms of the Modified BSD License.
Package: jupyter-server-fileid
jupyter_server_fileidA Jupyter Server extension providing an implementation of the File ID service.RequirementsJupyter ServerInstallTo install the extension, execute:pipinstalljupyter_server_fileidUninstallTo remove the extension, execute:pipuninstalljupyter_server_fileidTroubleshootIf you are seeing the frontend extension, but it is not working, check
that the server extension is enabled:jupyterserverextensionlistContributingDevelopment install# Clone the repo to your local environment# Change directory to the jupyter_server_fileid directory# Install package in development mode - will automatically enable# The server extension.pipinstall-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:jupyterlab--autoreloadIf your extension does not depend a particular frontend, you can run the
server directly:jupyterserver--autoreloadRunning TestsInstall dependencies:pipinstall-e".[test]"To run the python tests, use:pytest# To test a specific filepytestjupyter_server_fileid/tests/test_handlers.py# To run a specific testpytestjupyter_server_fileid/tests/test_handlers.py-k"test_get"Development uninstallpipuninstalljupyter_server_fileidPackaging the extensionSeeRELEASE