Saravanan666/pypi-org huggingface dataset:
Package: nbconvert-queue
nbconvert_queueA JupyterLab extension for queuing notebooks executions.This extension is composed of a Python package namednbconvert_queuefor the server extension and a NPM package namednbconvert_queuefor the frontend extension.RequirementsJupyterLab >= 4.0.0InstallTo install the extension, execute:pipinstallnbconvert_queueUninstallTo remove the extension, execute:pipuninstallnbconvert_queueTroubleshootIf you are seeing the frontend extension, but it is not working, check
that the server extension is enabled:jupyterserverextensionlistIf the server extension is installed and enabled, but you are not seeing
the frontend extension, check the frontend extension is installed:jupyterlabextensionlistContributingDevelopment 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 nbconvert_queue directory# Install package in development modepipinstall-e"."# Link your development version of the extension with JupyterLabjupyterlabextensiondevelop.--overwrite# Server extension must be manually installed in develop modejupyterserverextensionenablenbconvert_queue# Rebuild extension Typescript source after making changesjlpmbuildYou 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 modejupyterserverextensiondisablenbconvert_queue
pipuninstallnbconvert_queueIn 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 namednbconvert_queuewithin that folder.Packaging the extensionSeeRELEASE
Package: nbconvert_reportlab
An experimental tool to convert Jupyter notebooks to PDFs usingReportlab.Install:pip install nbconvert_reportlabUse:jupyter nbconvert --to pdf-rl MyNotebook.ipynbJupyter comes with support for generating PDFs by filling a template to
make a Latex file, and then running Latex to convert that to PDF. This is a
powerful approach, but Latex code is not a great intermediate format for
automatic generation, and that can lead to a variety of problems.This package uses the open source Reportlab Toolkit to convert notebooks
directly to PDFs. This avoids a lot of complexity, but at least for now there
are many things that it cannot handle and will simply skip over.See anexample output PDF.
Package: nbconvert-theme-pale-sand-navy
nbconvert-theme-pale-sand-navyThis is a theme for the jupyter nbconvert extension. Checkout the screenshot below which was created fromthis project.Installationpipinstallnbconvert-theme-pale-sand-navyUsageAfter installing the package you can select theme by passing the template parameter to the jupyter nbconvert command.jupyternbconvert--tohtml--templatepale-sand-navynotebook.ipynbIt can also be easily used inside GitHub Actions likehere.
Package: nbcourse
nbcourse: publish your course based on Jupyter notebooksFeaturesnbcoursehelps you building a static website to publish your course content in the form of jupyter notebooks (one notebook for one chapter).Main features:all the configuration is described by a singlenbcourse.ymlfileit is based ondoitin order to build efficently the html fileschapters can be displayed inpreview modeonly so attendees can see the whole course program without being able to access content of the lessons to comenotebooks can be:rendered as static html files,rendered as static reveal slideshows,packaged with all their material in a downloadable archive,compiled in a single pdf book usingbookbookthe theme can be easily customized (html files are templated using jinja)Seethis python course(in French) as an example.InstallationpipinstallnbcourseUsageInitiate an empty nbcourse projectnbcourse--initConfigure your websitePut your notebooks file in thenotebook/directoryEdit thenbcourse.ymlfile created by thenbcourse --initcommand.Build your websitenbcourseResulting files are in thebuild/directory.Get helpnbcourse--helpPublishPublishing withGitLab Pagesis as simple as adding a.gitlab-ci.ymlfile such as:pages:image:boileaum/jupyterscript:-pip install nbcourse-nbcourse -n 5-mv build publicartifacts:paths:-public
Package: nb-courselevels
courselevelsJupyter notebook extension forbackground colouring of cells (3 predefined colors)creating framed cellsUIThree buttons are provided that toggle the colour of selected cells
(1 finger = basic, 2 fingers = intermediate, 4 fingers = advanced/expert)
In addition a button allows to add/remove a frame around the selected cellsThis is designed for flagging course contents, so that students can better navigate it;
color code is as followsbasic (green)intermediate (blue)advanced/expert (red)see an example inexamples/READMEconfigCan be customized through the nbextensions-configurator panel
Also the following actions can be attached to keyboard sohrtcuts using Jupyter's shortcuts editorcourselevels:toggle-basiccourselevels:toggle-intrmediatecourselevels:toggle-advancedcourselevels:toggle-frameinstallationInstall via:pip install nb-courselevelsThe extension should be automatically installed and enabled.
Package: nb-cpp
# Newton Basins C++ Implementation (pybind11)A Python/C++ (pybind11) package to generate newton basins images.## Installation### From PyPI```pip install nb-cpp```### From source code```pip install git+https://github.com/gmagno/nb-cpp.git```or```git clone git@github.com:gmagno/nb-cpp.gitcd nb-cpp/make install```## Example UsageJust run:```pythonimport matplotlib as mpl  # don't forget to `pip install matplotlib` firstimport matplotlib.pyplot as pltimport nb_cpphsv = nb_cpp.compute(imw=32, imh=32, # for more details, run: help(nb_py.compute))rgb = mpl.colors.hsv_to_rgb(hsv)plt.figure()plt.imshow(rgb)plt.show()```## LicenseThis project is licensed under the MIT License - see the [LICENSE.md](LICENSE.md) file for details
Package: nb-cron
nb_cronProvides crontab access from within Jupyter.Cron tab in the Jupyter file browserThis extension adds aCrontab to the Jupyter file browser and aCronmenu item in notebook view. Features include:View the list of the cron job(s) that currently exist.Edit existing cron job(s)Delete existing cron job(s)Add new cron jobHelper to build papermill commandAllows setting of notebook's environment, kernel and parametersAble to inspect notebook (relative or full path) to extract environment, kernel and parameters to build papermill command and optionsAble to set commands to run before and/or after papermill using jupyter_nbextensions_configuratorInstallationAfter installing the package using conda or pip, you can add nb_cron to jupyter as follows:jupyter nbextension install nb_cron --py --sys-prefix --symlink
jupyter nbextension enable nb_cron --py --sys-prefix
jupyter serverextension enable nb_cron --py --sys-prefixCron tab in tree viewTo create a new cron job:Use theCreate New Cron Jobbutton at the top of the page, and fill in the bash command and cron schedule.Use theNotebook Command Builderto build a bash command for running a notebook using papermill.To edit an existing cron job:Click theEditbutton on the left of a cron job listing and fill in the bash command and cron schedule.To delete an existing cron job:Click theTrashbutton on the left of a cron job listing to delete the cron job.Cron menu item in notebook viewTo manage cron jobsClickView cron jobs(refer to cron tab in tree view)To schedule new cron job for current notebookClickSchedule notebook job.Opens up theCreate new jobandNotebook command builderdialog.Auto inspect notebook and fill up theNotebook command builderdialog.To edit existing cron job that uses current notebookClickEdit notebook job.Only available if there is an existing cron job contains the current notebook in the cron command.Only able to edit the first job. Please useView cron jobsto edit if there are multiple jobs for the notebook.To set parameters tag for papermillClick notebook cell that you want to parameterize (cell that contains all the parameters for running papermill)ClickCron>Set papermill parameters cellin menu bar.
Package: nbd
A lightweight ipython/jupyter notebook diffing tool.PurposeThis tool makes ipython/jupyter notebook diffs more readable.This tool is meant for text-based diffing from the command-line.OverviewRunningndbshows differences in the following types of data:Python codereStructuredText codeResource files (e.g. PNGs)This will show you most of what has changed in theIn[1]:andOut[1]:lines of the notebook.The output ofndbisgit-diffoutput and can be piped
to other commands likeless(1)andtee(1).RequirementsPython >= 2.6nbconvertpandocgitInstallInstall with pip (or your favorite python package manager):pip install nbdUsageHelp:nbd -hSimple usage:nbd <notebook>Pipe toless(1):nbd <notebook> | lessOptions (see help for all):nbd -e python <notebook>
nbd <notebook1> <notebook2> <notebook3>
nbd <notebook> --git-diff-option="--name-only"Build and install from sourcesSource distribution:python setup.py sdistAfter building, install with pip:pip install dist/nbd-$version.tar.gzInstall in a virtual environment to avoid system pip issues.TutorialSee the tutorial in thedemo/directory:demo
tutorial.
Package: nbdbsession
nbdbsessionThis code helps you to manage connections to sql databases in jupyter notebooks.nbdbsessionstands for "notebook database session".I use notebooks very often to connect to databases like postgres. With the notebook sessions, I often work on PoCs (proof of concept), on presentations or on debugging.catherinedevlinhas created open source software that I love:ipython-sql.  (Note: There was a fork of this project:jupy-sql. The original version is not actively maintained, and does not work with sqlalchemy version 2 that wasreleased in January 2023)This code --nbdbsession-- lets you connect to sql databases from your notebook, and run queries.How To UsenbdbsessionFirst, install it:pip install nbdbsessionThen, in your git repository where you start your notebook, create a.settings.tomlfile with your database login credentials:You need to define your database credentials in a toml file. The toml file should look like this:# either: .settings.toml on top level of your git repo# or:     $HOME/.nbdbsession.creds.toml[davidkuda]db_driver="postgresql"database="dev"user="davidkuda"password="${DB_PASSWORD}"# you can use environment variablesdb_url="localhost"port=5439# the ssh command is optional:ssh_cmd="ssh -fL 5432:db.kuda.ai:5432"nbdbsession will scan three places for a toml file and will choose the first hit in this order:env var$SETTINGS_FILE_PATH(root directory of a git project)/.settings.toml$HOME/.nbdbsession.creds.tomlFinally, you can connect to your database in your notebook by running the following code in a cell:fromnbdbsession.sqlconnimportconnectconnect("davidkuda")# note: this is the name as defined in .settings.tomlOnce you have done that, you can run sql commands by prepending%sql(one line)%%sql(multi-line) in the notebook.Run single line sql commands directly in your notebook:%sqlSELECT*FROMtableLIMIT10;Run multi-line sql commands directly in your notebook:%%sqlSELECT*FROMtableLIMIT10;How to publish a pkg to PyPI# package codepythonsetup.pysdist# upload code to PyPItwineuploaddist/*# update pkgpipinstallnbdbsession--upgradeManaging the conn without this repoIn the usual way, you would create a connection string, something like this:%load_extsqlimportparse# make a connection string for your database connectionconfig={"user":"postgres","password":parse.quote("postgres"),"url":"127.0.0.1","port":5432,"database":"postgres",}conn_string=f'postgresql://{c["user"]}:{c["password"]}@{c["url"]}:{c["port"]}/{c["database"]}'# results in: 'postgresql://postgres:postgres@127.0.0.1:5432/postgres'%sql$conn_stringWith the code in this repo, you reduce all that to one line:fromnbdbsession.sqlconnimportconnect# this will enable ipython sql and use the conn str that you choose:connect("staging")%sql
Package: nbdefense
🛡️ NB Defense🏃‍♀️ Quick Startpipinstallnbdefense🙋‍♂️ What is NB Defense?Brought to you by Protect AI, NB Defense is a CLI tool and SDK that encourages you to think about security throughout every step of your machine learning development process. You can use nbdefense to scan forSecrets,Personally Identifiable Information (PII),Common Vulnerabilities and Exposures(CVE), andLicensesin your notebook and dependency files.NB Defense also acts as a SDK for ourJupyter Lab Extension. Visit ourdocumentation, or the repository below to learn more.Jupyter Lab Extension Repository📄 DocumentationFor more details anddocumentationvisit these links:DocumentationGetting Started on a Local Machine💪 ContributingWelcome to the team! We are open to contributions and working with the community to make notebooks safer for everyone.If you would like to contribute, please visitCONTRIBUTING.mdto get started as a developer, or to suggest bug fixes, improvements, or new features followthis linkto our FAQ page.
Package: nbdefense_jupyter
🛡️ NB Defense Jupyter Lab Extension🏃‍♀️ Quick Startpipinstallnbdefense_jupyter
jupyterserverextensionenablenbdefense_jupyter🙋‍♂️ What is the NB Defense Jupyter Lab Extension?Brought to you by Protect AI, NB Defense Jupyter Lab Extension (JLE) is an open source tool that encourages you to think about security throughout every step of your machine learning development process. You can use nbdefense to scan forSecrets,Personally Identifiable Information (PII),Common Vulnerabilities and Exposures(CVE), andLicensesin your notebook files.The NB Defense Jupyter Lab Extension depends on ourCLI/SDKrepository Visit ourdocumentation, or the repository below to learn more.NB Defense Repository📄 DocumentationFor more details anddocumentationvisit these links:DocumentationGetting Started on a Local MachineGetting Started on with Cloud Services💪 ContributingWelcome to the team! We are open to contributions and working with the community to make notebooks safer for everyone.If you would like to contribute, please visitCONTRIBUTING.mdto get started as a developer, or to suggest bug fixes, improvements, or new features followthis linkto our FAQ page.
Package: nbdefs2py
A small package (only) to export functions and classes from notebooks to scriptsTable of ContentsInstallationUsageLicenseInstallationpip install nbdefs2pyUsagenbdefs2pycan be used as a CLI tool or a Python function.$python-mnbdefs2py-husage: python -m nbfuncs [-h] [-i IGNORE] [--update] [--no-update] [--include INCLUDE [INCLUDE ...]][--exclude EXCLUDE [EXCLUDE ...]]SRC DSTExtract definitions from notebooks.positional arguments:SRC                   source file/pathDST                   target file/pathoptional arguments:-h, --help            show this help message and exit-i IGNORE, --ignore IGNOREglob expression of files to ignore--update              update only existing functions--no-update           overwrite destination file--include INCLUDE [INCLUDE ...]names of functions to include--exclude EXCLUDE [EXCLUDE ...]names of functions to ignore>>>fromnbdefs2py.ioimportexport>>>export(source="nb.ipynb",destination="exported.py")Licensenbdefs2pyis distributed under the terms of theMITlicense.
Package: nbdev-cards
nbdev_cardsA deck of cards demo ofnbdevbased on ideas
fromThink Python 2nd
Editionby Allen B.
Downey.InstallInstall using:pip install nbdev-cardsor:conda install -c fastai nbdev-cardsHow to useThis lib provides aCardclass you can use to create, display, and compare playing cards:Card(1,3)3♦️Suits are numbered according to this list:suits['♣️', '♦️', '❤️', '♠️']
Package: nbdev-cards2022
nbdev_cardsA deck of cards demo ofnbdevbased on ideas
from “Think Python 2nd Edition” by Allen B. Downey.pip installThenbdev-cards2022package
was uploaded toPyPIand can be easily installed
using the below command.pip install nbdev-cards2022conda installThenbdev-cards2022was
also uploaded toAnacondaand can be installed
using the below command.conda install -c hdocmsu nbdev-cards2022How to useimport the card and deck modulesfromnbdev_cards.cardimport*fromnbdev_cards.deckimport*This lib provids aCardclass
that you can use to create, display, and compare playing cards.Card(2,3)3♥display all suitssuits['♣', '♦', '♥', '♠']display all ranksranks[None, 'A', '2', '3', '4', '5', '6', '7', '8', '9', '10', 'J', 'Q', 'K']Deckclass can
be called to generate a deck of playing card. Initially, the deck is
ordered.deck=Deck()deckA♣; 2♣; 3♣; 4♣; 5♣; 6♣; 7♣; 8♣; 9♣; 10♣; J♣; Q♣; K♣; A♦; 2♦; 3♦; 4♦; 5♦; 6♦; 7♦; 8♦; 9♦; 10♦; J♦; Q♦; K♦; A♥; 2♥; 3♥; 4♥; 5♥; 6♥; 7♥; 8♥; 9♥; 10♥; J♥; Q♥; K♥; A♠; 2♠; 3♠; 4♠; 5♠; 6♠; 7♠; 8♠; 9♠; 10♠; J♠; Q♠; K♠shuffle()method could be used to shuffle the deck.deck.shuffle()deckQ♥; 6♥; 4♥; Q♣; 8♥; K♣; A♦; Q♠; 7♠; 5♦; J♣; J♥; 6♠; A♣; 9♥; 9♣; J♠; A♠; 10♥; 3♥; 7♦; K♠; 4♠; 2♦; 5♠; K♦; 10♣; 5♣; 4♦; 8♣; 7♣; 10♠; Q♦; K♥; A♥; 7♥; 6♦; 3♠; 3♦; 9♦; 4♣; 6♣; 3♣; 8♦; 5♥; 9♠; 10♦; 2♠; J♦; 8♠; 2♥; 2♣draw_n()function can be used to draw n card with or without
replacement.let’s draw 10 cards with replacement.draw_n(10,replace=True)[10♦, 3♣, 6♦, Q♦, 3♥, K♠, 4♣, K♣, 3♣, 2♦]now let’s draw 10 cards without replacement.draw_n(10,replace=False)[Q♣, A♥, A♦, J♦, 2♦, 5♠, 8♦, J♥, 5♣, 3♠]Example: One can draw two sets of cards each set contains four cards
and compare to see which one has higher rank.Developer installIf you want to develop nbdev_cards yourself, please use an editable
installation of nbdev_cards.git clone https://github.com/hdocmsu/nbdev_cards.gitpip install -e "nbdev_cards[dev]"You also need to use an editable installation ofnbdev,fastcore, andexcnb.Happy Coding!!!
Package: nbdev-cards-31082022
nbdev_cardsA deck of cards demo ofnbdevbased on ideas
fromThink Python 2nd
Editionby Allen B.
Downey.Installpipinstallnbdev-cardscondainstallnbdev-cardsHow to useThis requires aCardclass to create , display and compare playing
cardsCard(1,3)3♦️suits['♣️', '♦️', '❤️', '♠️']
Package: nbdev-cards-nix-flake
nbdev_cardsPublished : 2022-09-12 22:22:37 (KST)트럼프 카드 라이브러리에 대한 아이디어는Think Python 2nd Edition by
Allen B. Downey에서
가져옴.설치다음의 코드를 이용해 설치한다:pipinstallcard다른 방법:condainstall-csepiabrowncard사용법이 라이브러리는 트럼프 카드들을 생성하고 비교할 수 있는Card클래스를 제공한다.Card(suit=1,rank=3)3♦️suits['♣️', '♦️', '♥️', '♠️']assertCard(suit=1,rank=3)<Card(suit=2,rank=3)
Package: nbdev-extensions
nbdev-extensionsThese extensions will have niche use cases in some places, however these
are ones where I find a benefit in having them at least once. Also known
as, cool ideas myself or others have considered with nbdev brought to
lifeInstallpipinstallnbdev-extensionsHow to usenbdev-extensionscurrently has the following features:new_nb-
A CLI/functional interface to quickly generate blank template
notebooks for nbdev development with all of the necessary boilerplate
cells prefilled based on the passed parameters.Code Notes- A note-taking annotation tool utilizing
nbdev to write quick comments and explanations for sections of code in
a code cell without cluttering the code cell with comments. These show
up as panels in the rendered documentation, one with just the source
code and the other with the source and an explanation
Package: nbdev-hello-dice
nbdev-hello-worldThis is a simple dice throwing class that usesNumPy
default_rngto build an array of random integers depending upon the number of sides
on the dice and the number of dice thrown.Installpipinstallnbdev-hello-diceHow to useHere, we throw 1 die with 6 sides:result=throw(6)result1 = sum([1])Next, we can throw $\times 2$ dice and look at the sumthrow(6,2)3 = sum([1 2])The dice values are stored in an array, asthrow(N, inhand).diceas
suchresult=throw(6,4)result.dicearray([2, 1, 4, 6])Thesumof the dice values are saved inthrow.(N, inhand).sumas
suchresult.sum13
Package: nbdev-hellow-world
nbdev_hellow_worldA deck of cards demo ofnbdevbased on ideas
from Allen Downey.InstallInstall using:pipinstallnbdev_hellow_worldorcondainstall-cfastainbdev-hellow-worldHow to useThis lib provides aCardclass
you can use to create, display, and compare playing cards:Card(1,3)3♦️Suits are numbered according to this list:suits['♣️', '♦️', '❤️', '♠️']Ranks are numbered according to this list:ranks[None, 'A', '2', '3', '4', '5', '6', '7', '8', '9', '10', 'J', 'Q', 'K']
Package: nbdev-ignore
Nbdev-ignoreInstallpipinstallnbdev-ignoreHow it worksThere’s only one functionignore_in this module. It’s exactly the
same as thehide_processor innbdev, so that “#| ignore”
serves the same purpose as “#| hide”. For details on how it works, see.In order for it to also serve as a test flag, we will need to manually
add it totst_flags(see below), as currently there’s no way to plug
it into thenbdev_testprocess.How to useTo enable the#| ignoredirective, in your settings.ini make sure to:Addnbdev_ignoreas a requirementAddprocs = nbdev_igore.core:ignore_, where it should point to the
exact function being calledAdd it to test flags:tst_flags = ignore, so that cells with this
directive also avoids testing. If you already have other test flags,
separate them with space. For example, if you already havenotestas
your test flag, thentst_flags = notest ignore.
Package: nbdev-othmane-test
nbdev-othmane-testA deck of cards demo ofnbdevbased on ideas
fromThink Python 2by
Allen B. DowneyInstallInstall using:pip install nbdev-othmane-testor:conda install -c fastai nbdev-othmane-testHow to useThis lib privdes aCardclass you can use to create, display and compare playing cards:Card(1,3)3♦️
Package: nbdev-whatsapp
Análisis de textoAnálisis de un grupo de WhatsApp basado en el artículoWhatsapp Group Chat Analysis using Python and Plotlypublicado porSaiteja Kura%load_ext autoreload
%autoreload 2The autoreload extension is already loaded. To reload it, use:
  %reload_ext autoreloadThis file will become your README and also the index of your documentation.Installpip install hola_nbdev2How to useAlgunos ejemplosstartsWithDateAndTimeVerifica si la el texto inicia con fecha y horax = '01/10/18 19:18 - Señora 5: Claudia, puedes reenviar los paquetes, por favor? 🙏🏼 Aún no estaba en el grupo'
startsWithDateAndTime(x)TruestartsWithDateAndTimeEncuentra al autor del mensaje si está en alguno de estos formatosNombreNombre y apellidoNombre + 2 apellidosNúmero telefónico (México)Nombre y emojiNombre genéricoy = x.split(' - ')
y
print(FindAuthor(y[1]))True