Saravanan666/pypi-org huggingface dataset:
Package: nbsafety
➤ nbsafetyAboutnbsafetyadds a layer of protection to computational notebooks by solving thestale dependency problemwhen executing cells out-of-order. Here's an
example in action:When the first cell is rerun, the second cell now contains a reference to an
updatedfand is suggested for re-execution with a turquoise highlight. The
third cell contains a reference to a staley--yis stale due to its
dependency on an old value off. As such, the third cell is marked as unsafe
for re-execution with a red highlight.  Once the second cell is rerun, it is
now suggested to re-execute the third cell in order to refresh its stale
output.nbsafetyaccomplishes its magic using a combination of a runtime tracer (to
build the implicit dependency graph) and a static checker (to provide warnings
before running a cell), both of which are deeply aware of Python's data model.
In particular,nbsafetyrequiresminimal to no changesin user
behavior, opting to get out of the way unless absolutely necessary and letting
you use notebooks the way you prefer.InstallpipinstallnbsafetyInterfaceThe kernel ships with an extension that highlights cells with live references
to stale symbols using red UI elements. It furthermore uses turquoise highlights
for cells with live references to updated symbols, as well as for cells that
resolve staleness.RunningTo run annbsafetykernel in Jupyter, select "Python 3 (nbsafety)" from the
list of notebook types in Jupyter's "New" dropdown dialogue. For JupyterLab,
similarly select "Python 3 (nbsafety)" from the list of available kernels in
the Launcher tab.Jupyter Notebook Entrypoint:Jupyter Lab Entrypoint:UninstallpipuninstallnbsafetyLicenseCode in this project licensed under theBSD-3-Clause License.➤ ContributorsStephen MackeRay GongShreya Shankar
Package: nbscuid
nbscuid 🦑Notebook-Based, Super CUstomizable Infrastructure for DiagnosticsThis is a package to enable running notebook-based diagnostic workflows. Based on my-cesm-experiment by matt-long:https://github.com/matt-long/my-cesm-experiment.See some examples of workflows athttps://github.com/rmshkv/nbscuid-examples. For a basic tutorial, followhttps://nbscuid.readthedocs.io/en/latest/tutorialsetup.html.CapabilitiesIntegration with data catalogsInject custom parameters into code and Markdown cellsRun many notebooks at once on a parameter set, or different parameters per notebookRun different notebooks in different environmentsCache intermediate data productsQuickly build a Jupyter book with resultsInstallationRun:pip install nbscuidAlternatively, to install the commandsnbscuid-runandnbscuid-buildwithout installing all ofnbscuid's dependencies, first install pipx withpip install pipx, then run:pipx install nbscuidRunning a notebook collectionCreate a new folder that contains aconfig.ymlfile. (A guide to what goes in aconfig.ymlfile is coming soon!) This will be the run directory for your collection of notebooks, where all the computed notebooks will appear.To run all the notebooks you've specified, execute:nbscuid-run path/to/config.ymlTo build the jupyter book if desired, execute:nbscuid-build path/to/config.yml
Package: nbsearch
nbsearchDatasette based notebook search extension, originally inspired by Simon Willison'sFast Autocomplete Search for Your Website.Related:Sketching a datasette powered Jupyter Notebook Search Engine: nbsearchInstallationpip3 install --upgrade git+https://github.com/ouseful-testing/nbsearch.gitUsage - inside Jupyter notebook environmentThis is still very much a work in progress. I think it works in Binder (erm, maybe...)Installing the extension and restarting the Jupyter server should make a Jupyter proxy served version of the search form available from theNewmenu.At the moment, I think you need to create the index explicitly. From the command line:nbsearch index -p PATH(From a notebook command cell, prefix with!. Default path is.).The sqlite db that stores the results is in~/.nbsearch/notebooks.sqlite.All notebooks down fromPATHwill be indexed.When you have generated an index, launch thenbsearchpanel from the notebook homepageNewmenu.Usage - from the command linecreate a database by passing a path to some notebook files, eg:nbsearch index -p "/Users/myuser/Documents/content/notebooks"run the server, eg:nbsearch servedatasetteshould start up and display a server port number. (To kill it, I look for process IDs:ps -al |grep datasette; there is probably a better way... It  might be nice if CLI kept track of process IDs and let you kill from a selection?)UIOld screenshotAcopybutton on a code cell lets you copy code from the code cell.Results are limited in length; theShow all cellbutton expands the result cell to its full length. TheShow previous cellandShow next cellbuttons display the full previous / next cell (repeatedly clicking these buttons grab the next next and previous previous cells etc.)Clicking on the notebook structure visualisation graphic (the pink/blue image: the colours representent cell type and relative length) will collapse / reveal the display of the result block.Known IssuesThe links to notebooks may well be broken in the search results: I need to think about how to index and handle paths in links, particular in proxy server case.The app requires the latest version ofdatasettefrom the repo, not pypi.The index is not updatedeverunless you rerun the indexer, although I've started trying to ponder a filesystem watchdoghere. Another possibility my be a Jupyter notebook content manager or post-save hook to update records as the notebook server saves them but this would not catch filesystem operations (dragging new notebooks to a folder, deleting notebooks etc?)If the sqlite db is updated, I assume by some magic that thedatasetteserver queries over the updated content?UsefulQuick way to killdatasetteprocesses:ps aux | grep datasette | grep -v grep | awk '{print $2}' | xargs kill
Package: nb-serverproxy-openrefine
nb_serverproxy_openrefineJupyter server proxy for OpenRefineBased on the originalhttps://github.com/psychemedia/jupyterserverproxy-openrefinewhich has some docs, although the reponame/install instructions will need updating for this repo.I will pop the package on PyPi at some point.Jupyter-server-proxy config for running OpenRefine.Install as:pipinstallnb-serverproxy-openrefineTo install directly from this repo:pipinstallgit+https://github.com/innovationOUtside/nb_serverproxy_openrefine.gitOpen to Notebook homepage:Open to OpenRefine:Open to Jupyterlab:OpenRefine can now be started and launched from the notebook homepage New menu:Or from the JupyterLab launcher:The OpenRefine client can be found on theopenrefinepath (the port number is allocated dynamically).Calling the path directly (eg starting MyBinder with the pathopenrefine, or adding?urlpath=openrefineto the Binder URL) will launch the Binder container directly into the OpenRefine GUI application.The directory path into which the OpenRefine project files are saved is$HOME/openrefineby default, although you can trump it via the$REFINE_DIRglobal variable:openrefine_path=os.getenv("REFINE_DIR")if"REFINE_DIR"inos.environelsestr(Path.home()/'openrefine')The host openrefine will use is127.0.0.1by default. This can be overriden with the$REFINE_DOMAINglobal variableEarly original work on getting OpenRefine running in MyBinder was done by @betatim (betatim/openrefineder) and @yuvipanda helped me get my head round various bits ofjupyterhub/jupyter-server-proxy/which is key to proxying web services via Jupyter. @manics PR for handling predefined, rather than allocated, port mappings also made life much easier...Python ClientA Python client is also available for working with OpenRefine:opencultureconsulting/openrefine-clientlooks to be the best supported but seems to rely on Python 2.7; there is acurrently failing PR to add Python3 support.dbutlerdb /refine-client-pyworks with Python3 but lagsopencultureconsulting /openrefine-clientUsing the client requires Open Refine to be running.TO DO: should we hardwire the port? Else how do we know where to connect?:When the client works with Python3 I will add it as an optional dependency to this package.
Package: nb-service
Netbox NbserviceNetboxPlugin for ITSM service mapping.CompatibilityThis plugin in compatible withNetBox2.10 and later.
Tested in versions: 2.10.6; 2.11.12; 3.1.11; 3.2.1InstallationAdd the following line to /opt/netbox/local_requirements.txt withnb-serviceEnable the plugin in /opt/netbox/netbox/netbox/configuration.py:PLUGINS = ['nb_service']Runs /opt/netbox/upgrade.shsudo /opt/netbox/upgrade.shScreenshotsVersions 2.XService ListService ViewService RelationsService DiagramApplication ListApplication ViewApplication DevicesVersions 3.XService ListService ViewService RelationsService DiagramApplication ListApplication ViewApplication Devices
Package: nb-service-ntt
Netbox NbserviceNetboxPlugin for ITSM service mapping.CompatibilityThis plugin in compatible withNetBox3.7.
Tested in versions: 3.7.1InstallationAdd the following line to /opt/netbox/local_requirements.txt withnb-service-nttEnable the plugin in /opt/netbox/netbox/netbox/configuration.py:PLUGINS = ['nb_service_ntt']Runs /opt/netbox/upgrade.shsudo /opt/netbox/upgrade.sh
Package: nbsite
NBSite: Build a tested, sphinx-based website from notebooksBuild StatusCoverageLatest dev releaseLatest releaseDocsDISCLAIMERNBSite is a tool supporting the developers of theHoloVizproject. As such it is tailored to their use case, workflow, andbreaking changes may occur at any time. We suggest that before using NBSite you investigate alternatives such asMyST-NBornbsphinx. If you select NBSite anyway, we recommend that you pin its version.NBSite lets you build a website from a set of notebooks plus a minimal
amount of config. The idea behind NBSite is that notebooks can simultaneously be documentation (things you want to tell people about), examples (a starting point for people to run and use themselves), and test cases (see nbsmoke).Sites built with NBSiteNon exhaustive list of sites built with NBSite (as of November 2022):PanelhvPlotHoloViewsGeoViewsDatashaderLumenColorcetParamHoloViz.orgexamples.pyviz.orgPyViz.orgAbout HoloVizNBSite is part of the HoloViz initiative for making Python-based visualization tools work well together.
Seeholoviz.orgfor related packages that you can use with NBSite andstatus.holoviz.orgfor the current status of each HoloViz project.
Package: nbsocks
About shadowsocks-rm---------------This project is https://github.com/shadowsocks/shadowsocks clone. I JUST fix bug on the original code. Unless it is necessary to have additional features.shadowsocks===========|PyPI version| |Build Status| |Coverage Status|A fast tunnel proxy that helps you bypass firewalls.Server------Install~~~~~~~Debian / Ubuntu:::apt-get install python-pippip install shadowsocksCentOS:::yum install python-setuptools && easy_install pippip install shadowsocksWindows:See `Install Server onWindows <https://github.com/shadowsocks/shadowsocks/wiki/Install-Shadowsocks-Server-on-Windows>`__Usage~~~~~::ssserver -p 443 -k password -m rc4-md5To run in the background:::sudo ssserver -p 443 -k password -m rc4-md5 --user nobody -d startTo stop:::sudo ssserver -d stopTo check the log:::sudo less /var/log/shadowsocks.logCheck all the options via ``-h``. You can also use a`Configuration <https://github.com/shadowsocks/shadowsocks/wiki/Configuration-via-Config-File>`__file instead.Client-------  `Windows <https://github.com/shadowsocks/shadowsocks/wiki/Ports-and-Clients#windows>`__/ `OSX <https://github.com/shadowsocks/shadowsocks-iOS/wiki/Shadowsocks-for-OSX-Help>`__-  `Android <https://github.com/shadowsocks/shadowsocks/wiki/Ports-and-Clients#android>`__/ `iOS <https://github.com/shadowsocks/shadowsocks-iOS/wiki/Help>`__-  `OpenWRT <https://github.com/shadowsocks/openwrt-shadowsocks>`__Use GUI clients on your local PC/phones. Check the README of your clientfor more information.Documentation-------------You can find all the documentation in the`Wiki <https://github.com/shadowsocks/shadowsocks/wiki>`__.License-------Copyright 2015 clowwindyLicensed under the Apache License, Version 2.0 (the "License"); you maynot use this file except in compliance with the License. You may obtaina copy of the License at::http://www.apache.org/licenses/LICENSE-2.0Unless required by applicable law or agreed to in writing, softwaredistributed under the License is distributed on an "AS IS" BASIS,WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.See the License for the specific language governing permissions andlimitations under the License.Bugs and Issues----------------  `Troubleshooting <https://github.com/shadowsocks/shadowsocks/wiki/Troubleshooting>`__-  `IssueTracker <https://github.com/shadowsocks/shadowsocks/issues?state=open>`__-  `Mailing list <https://groups.google.com/group/shadowsocks>`__.. |PyPI version| image:: https://img.shields.io/pypi/v/shadowsocks.svg?style=flat:target: https://pypi.python.org/pypi/shadowsocks.. |Build Status| image:: https://img.shields.io/travis/shadowsocks/shadowsocks/master.svg?style=flat:target: https://travis-ci.org/shadowsocks/shadowsocks.. |Coverage Status| image:: https://jenkins.shadowvpn.org/result/shadowsocks:target: https://jenkins.shadowvpn.org/job/Shadowsocks/ws/PYENV/py34/label/linux/htmlcov/index.html
Package: nbspellcheck
npspellcheckspell checking jupyter notebooksWriting correctly should be a priority, even for programmers and scientists.But this is not easy in jupyter notebooks.In english, a good solution is to make use of the spellchecker notebook extension, which highlights incorrect text:pip install jupyter_contrib_nbextensions
jupyter contrib nbextension install --user
jupyter nbextension enable spellchecker/mainHowever, this extension is currently not able to suggest corrections, and is only available for English.Since I write blog posts based on jupyter notebooks in French, I came up with a small script for spell checking.Installation:pip install nbspellcheckExample of use:nbspellcheck.py my_jupyter_notebook.ipynb -l frA big thank you to the developers ofnltk: python natural language toolkitpyspellchecker: python spell checkerthat are doing all the heavy lifting.I made this real fast, and the user interface can be improved. Please don't hesitate to send a PR.
Package: nbsphinx
nbsphinxis aSphinxextension that provides a source parser for*.ipynbfiles.
Custom Sphinx directives are used to showJupyter Notebookcode cells (and of
course their results) in both HTML and LaTeX output.
Un-evaluated notebooks – i.e. notebooks without stored output cells – will be
automatically executed during the Sphinx build process.Quick Start:InstallnbsphinxEdit yourconf.pyand add'nbsphinx'toextensions.Edit yourindex.rstand add the names of your*.ipynbfiles
to thetoctree.Run Sphinx!Online documentation (and example of use):https://nbsphinx.readthedocs.io/Source code repository (and issue tracker):https://github.com/spatialaudio/nbsphinx/License:MIT – see the fileLICENSEfor details.
Package: nbsqueeze
Welcome to nbsqueezeCreating plots in Jupyter notebooks is great for exploring your data.
The images that are generated by your plotting code are conveniently
stored within the notebook file as base64 encoded text strings. A
downside to this approach is that Jupyter notebooks with many plots
easily become quite large. Uploading such large notebook files to github
and subsequent testing and rendering of such notebooks to produce
documentation soon becomes intolerably slow…This small Python packagenbsqueezeis created to reduce the file size
of Jupyter notebooks by extracting embedded images as separate image
files. This open source package available via the Python Package indexhttps://pypi.org.For documentation and source code seegithub.
Package: nbs-social-auth
No BullShit Python Social AuthInspiration:Building SPAs and RestFul APIs in python frameworks like Django/ FastAPI/ Flask etc are a delight unless we encounter adding social login.
There is pretty good support for social login in Django for Templated apps usingSocial-Corebut this tends to be sticky to the templated applications and becomes confusing to provide a plain no Bull Shit approach to add a basic Google Social Login to the API,This is a fairly simple package with it's inital version supporting only Google Social Login since it's only thing I wanted to add in the APP I was building but it's open for contributions and feedback from the community to improve and add other providers.To use it,fromnbs_social_auth.googleimportGoogleOAuth2# Intialize the Google OAuth with the Credentialsgoogle_auth=GoogleOAuth2(GOOGLE_CLIENT_ID=<GOOGLE_CLIENT_ID>,GOOGLE_CLIENT_SECRET=<GOOGLE_OAUTH2_CLIENT_SECRET>,GOOGLE_REDIRECT_URI=<GOOGLE_CLIENT_SECRET>)# Now we open up and endpoint to grab the AUTH URL on the APP# In future we can add multiple providers and then send the AUTH URL based on a parameter@router.get("/social-auth-init-url")defget_social_auth_url(request):returngoogle_auth.get_auth_url()Now the client recieves the auth URL and goes there to grab the auth credentials and we usually want it to redirect to a Frontned Page where we grab the auth token and then call the next API -> which would exchange the token with a JWT that is used across the API for authentication of the User@router.get("/check-social-auth-code")defcheck_social_auth_code(request,code:str):try:social_user=google_auth.validate_code(code)email=social_user.get('email')# Register the User here / set provider / avatar-url or other parameters# Generate the token as per your logic heretoken=jwt.encode({'email':email},SECRET,algorithm=algorithm)# Return the token, save on client side and use for subsequent authenticated requestsexceptExceptionase:# Handle the Error and pass a meaningful error message to the clientDrop issueshere
Package: nbss-upload
nbss-uploadUpload notebooks (Jupyter, Rmd, etc) to aNotebookSharing.spaceinstance.Installationnbss-uploadis available on PyPI, and can be installed withpip.pipinstallnbss-uploadUsageSimply call it with the path to the notebook you want to upload.$nbss-uploadtest.ipynb
https://notebooksharing.space/view/04ab7ab45c2f08628eba9cb8fe5fb9a63f5961d5dfce622b9e26974ddc138916This will upload the notebook and return the URL you can use to share it with others.By default, only users who you share the URL with can access the notebook - it will
not be visible to search engines. Annotations will also be turned off by default to
help fight abuse.You can enable annotations viahypothes.isby passing--enable-annotationsor-a.
The notebook can be made discoverable to search engines by passing--enable-discveryor-d.All notebook formats supported by notebooksharing.space -.ipynb,.rmd,.htmlare supported.
Package: nbstata
Welcome to nbstatanbstatais aJupyter
kernelforStatabuilt on top ofpystata.For the User Guide, click
here.What is Jupyter?JupyterLabis a browser-based editor that allows you to combine interactive code
and results withMarkdownin a
single document (called a Jupyter notebook). It is open source and
widely used. Though it is named after the three core programming
languages it supports (Julia, Python, and R), it can be used with with a
wide variety of languages.nbstataallows you to create Stata notebooks (as opposed to using
Stata within aPythonnotebook, which is a nice way toembed Stata
commands within Python
codebut
is needlessly clunky if you are working primarily with Stata).nbstatafeaturesEasy
setupWorks with Stata 17+ (only).Displays Stata output without the redundant ‘echo’ of (multi-line)
commandsAutocompletion for variables, macros, matrices, and file pathsDataGrid widget withbrowse-like capabilities (e.g., interactive
filtering)Variable and data properties (describeande/return list)
available in a ‘contextual help’ side panelInteractive/richtext help files accessible within notebook#delimit ;interactive support (along with all types of
comments)What can you do with Stata notebooks……that you can’t do with theofficial Stata
interface?Exploratory analysis that is both:interactivepreserved for future reference/editingPresent results in a way that interweaves:[1]coderesults (including graphs)rich text:listsHeadingslinksmath: $y_{it}=\beta_0+\varepsilon_{it}$[1] Statadynamic
documentscan do this part, just with a less interactive workflow. (See also:markstat,stmd,
andStatamarkdown)
UsingnbstatawithQuartoinstead gives you a similar workflow, with greater flexibility of
output.Contributingnbstatais being developed usingnbdev.
The/nbsdirectory is where edits to the source code should be made.
(The python code is then exported to the/nbdevlibrary folder.)For more, seeCONTRIBUTING.md.AcknowledgementsKyle Barron authored the originalstata_kerneland Vinci Chow carried
that work forward for Stata 17, converting the backend to usepystata.nbstatawas
originally derived from hispystata-kernel, but much
of the docs and newer features are derived directly fromstata_kernel.
Package: nbsv
nbsvSimularium Viewer Jupyter WidgetInstallationYou can install usingpip:pipinstallnbsvIf you are using Jupyter Notebook 5.2 or earlier, you may also need to enable
the nbextension:jupyternbextensionenable--py[--sys-prefix|--user|--system]nbsvDevelopment InstallationCreate a dev environment:condacreate-nnbsv-d-cconda-forgeyarnpythonjupyterlab=3.6.4
condaactivatenbsv
nvmuse18Note: make sure you are using the node managed by nvm and not in your conda env by checkingwhich nodeInstall and build:yarninstall
./build.shHow to see your changesTypescript:If you use JupyterLab to develop then you 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 widget.# Watch the source directory in one terminal, automatically rebuilding when neededyarnrunwatch# Run JupyterLab in another terminaljupyterlabAfter a change wait for the build to finish and then refresh your browser and the changes should take effect.Python:If you make a change to the python code then you will need to restart the notebook kernel to have it take effect.Updating the versionTo update the version, install tbump and use it to bump the version.
By default it will also create a tag.pipinstalltbump
tbump<new-version>