Saravanan666/pypi-org huggingface dataset:
Package: ipycalc
ipycalcSimple Engineering Calculations in PythonTurn the contents of a Jupyter cell into a formatted calculation by following the steps below:Installipycalcusingpip install ipycalcUsefrom ipycalc import calcto bringipycalcinto your notebook's namespace.Use%%calcas the first line of a cell to indicate that you want to runipycalcon the contents of a cell.The basic calculation syntax is:Variable Description:variable_name=python_expression->result_decimal_places*result_unit# Reference TextKey components of theipycalcsyntax are::(required) The description must come before this character.=(optional) Used to assign a python expression to a variable name. Omit this if you simply want to reprint a previously defined variable.->(optional) Separates the python expression from the results formatting rules.*(optional) Indicate the number of decimals you want to see in the result to the left of the*, and the units you want to see in the result to the right.#(optional) Indicates reference text to the side of the calculation - handy for equation references or code references.Here are a few useful things to keep in mind when usingipycalc:Subscripts can be added by using the_character to indicate the start of a subscript.To stack fractions place the numerator and denominater in parentheses: (num)/(denom) yields $\dfrac{num}{denom}$.Ifstatements andelsestatements are available using python's inlineifstatement notation.Square roots can be displayed usingsqrt.Prime characters can be displayed using^prime.If a line gets too long for printing, you can add a line break to the description, equation, or reference by inserting\\.ipycalcassists you with printing your notebooks. It has a built innbconverttemplate calledipycalcthat works just like thewebpdftemplate, except it fixes the the bad margins in thewebpdftemplate, and avoids page breaks right after headers. Any cells tagged withhide_cellwill not be rendered. Any cells tagged withhide_inputwill only show the output upon printing. You can select it from the file menu via "File -> Save and Export Notebook As... -> Ipycalc"IPycalc is still in its infancy. I'm sure there are bugs, so be cautious and use your head. A special thanks to @connorferster forhandcalcswhich inspired this project:https://github.com/connorferster/handcalcs
Package: ipycanvas-drawing
Jupyter drawing utilitySmall utility to make simple drawings in Jupyter notebooks with ipycanvas and ipywidgets.
Useful for getting quick user input in research prototypes, e.g., for masking or annotation.Installpipinstallipycanvas-drawingUsageCreate a simple drawing interface. Check out the notebook inexamplesfor a more complete example.fromipycanvas_drawingimportDrawingWidget# Create a drawing widget# You can set other setup parameters: background, alpha, default_style, default_radiusdrawing_widget=DrawingWidget(width=500,height=500)# Show the drawing widgetdrawing_widget.show()# Get the image data as a numpy arrayimage_output=drawing_widget.get_image_data()Known issuesVisual Studio Code's Jupyter environment doesn't like ipycanvas'ssync_image_datafunctionality.
Workaround: open notebooks in Jupyter lab or Notebook in the browser.ipycanvas does not work in Google Colab.
Workaround: use theBinderto quickly try the tool without needing to install it on your own machine.CreditsBased on thehand drawing exampleprovided by @martinRenou, but adds some additional functionality like adding squares and ellipses and a 1-step undo.
Package: iPyCat
iPyCATInterface Python en ligne de Commande pour les Analyses de Textes.PréambuleCes instructions vous permettront d'utiliser au mieux l'application iPyCAT et de l'installer facilement sur votre machine. Nous vous donnons toutes les étapes clés afin de commencer à utiliser notre application rapidement.Pré-requisAfin de lancer l'application iPyCAT sur votre machine, vous devez posséder une version de Python <= 3.7. L'application est multi-plateforme et fonctionne sur Windows, MAC ou Linux.InstallationPour installer iPyCAT sur votre machine, assurez-vous de posséder Python <= 3.7 sur votre machine et dans votre PATH. En ligne de commande, dans votre terminal, installez notre application via PyPI en exécutant la commande suivante :pip install iPyCAT && iPyCAT updatePour mettre à jour l'application iPyCAT, saisir en ligne de commande :pip install --upgrade iPyCAT && iPyCAT updatePrise en main de l'applicationCette section est en cours de développement. De nouveaux exemples seront ajoutés sous peu.Générer un nuage de motsiPyCAT nuage-de-mots /chemin/de/mon/document/txt/exemple.txtLa liste des paramètres optionnels sont disponibles en saisissant :iPyCAT nuage-de-mots --helpAutres commandesSaisissez iPyCAT dans votre terminal afin de voir la liste des commandes supportées par notre application.iPyCATQuestions techniquesEn cas de problème pour utiliser iPyCAT, merci de nous contacter par mail afin de résoudre cela ensemble à cette adresse :ipycat@googlegroups.com.Afin de répondre avec diligence à votre demande, nous vous prions de bien vouloir répondre à ces questions dans votre premier message :> Quelle est votre système d'exploitation ? (Windows, MAC, etc.)
> Quelle est la version du système d'exploitation ? (Windows 10, MACOS 10.15.2, etc.)
> Joignez à votre message la sortie complète affichée en ligne de commandes.
Package: ipycc
ipyccA Python package for creative coding in JupyterThis package makes it easy to explore creative coding in Python using Jupyter notebooks. Its design is heavily inspired byp5.jsandTurtle graphicsfrom the Python standard library.TurtlesA dark blue square with a sprial pattern drawn in white. The spiral is drawn one side at a time.fromipyccimportTurtleted=Turtle()ted.draw()ted.bgcolor("midnightblue")ted.pencolor("ghostwhite")forsideinrange(40):length=side*5ted.fd(length)awaitted.delay(0.1)ted.lt(123)awaitted.delay(0.1)SketchesA light blue square with a circle in its center. The circle is drawn with a white center and black edge.fromipyccimportSketchp5=Sketch(400,400)p5.background("dodgerblue")p5.circle(200,200,50)p5.run_sketch()Ten white circles moving like fireflies on a dark blue background.importmathfromrandomimportuniformfromipyccimportSketchp5=Sketch(400,400)coupling=1num_bugs=10k_n=coupling/num_bugsclassBug:def__init__(self):self.x=p5.width*0.5self.y=p5.height*0.5self.r=5self.angle=uniform(0,math.tau)self.freq=uniform(5,10)self.da_dt=0self.dt=0.01defrender(self):p5.fill("ghostwhite")p5.no_stroke()p5.circle(self.x,self.y,2*self.r)defupdate(self):self.angle+=self.da_dt*self.dtdx=math.cos(self.angle)dy=math.sin(self.angle)self.x+=dxself.y+=dydefsync(self,bugs):self.da_dt=self.freqforbuginbugs:self.da_dt+=k_n*math.sin(bug.angle-self.angle)bugs=[Bug()for_inrange(num_bugs)]defdraw():p5.background("#1919706F")forbuginbugs:bug.sync(bugs)forbuginbugs:bug.update()bug.render()# Loop for 10 seconds.p5.run_sketch(draw,10)ipycc provides a simplified interface to the HTML canvas by wrappingipycanvasin a beginner-friendly API.AcknowledgementsPortions of theSketchclass are lovingly borrowed from theirp5.jsandprocesocounterparts.Portions of theTurtleclass are lovingly borrowed from their standard library counterparts.
Package: ipyclipboard
ipyclipboardA simple Jupyter Widget to read and write text from the clipboard.ipyclipboard-screencast.webmFeatures⚠️ This widget only supports text data for now.If you would like to see more features, please open an issue or submit a pull request, thanks!InstallpipinstallipyclipboardUsageSee the example notebook:example.ipynbUninstallpipuninstallipyclipboard
Package: ipycollections
ipycollectionsA JupyterLab extension that provides a more interactive format for collectionsRequirementsJupyterLab >= 4.0.0InstallTo install the extension, execute:pipinstallipycollectionsUninstallTo remove the extension, execute:pipuninstallipycollectionsUsageIn a JupyterLab notebook, use the following line to enable the extension%load_ext ipycollectionsIf you would like the extension to be enabled by default, edit yourconfiguration file(often~/.ipython/profile_default/ipython_config.py) to includeipycollectionsas an extension:c.InteractiveShellApp.extensions = [
    'ipycollections',
    # ...
]If you wish to disable the extension, use:%unload_ext ipycollecitonsContributingDevelopment 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 ipycollections directory# Install package in development modepipinstall-e"."# Link your development version of the extension with JupyterLabjupyterlabextensiondevelop.--overwrite# 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 uninstallpipuninstallipycollectionsIn 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 named@dfnotebook/ipycollections-extensionwithin that folder.Testing the extensionFrontend testsThis extension is usingJestfor JavaScript code testing.To execute them, execute:jlpm
jlpmtestIntegration testsThis extension usesPlaywrightfor the integration tests (aka user level tests).
More precisely, the JupyterLab helperGalatais used to handle testing the extension in JupyterLab.More information are provided within theui-testsREADME.Packaging the extensionSeeRELEASE
Package: ipycolorful
ipycolorfulPyPI+npmA Jupyter widget forreact-colorful.Referencesipywidgetsdocumentation andrepo.Building a Custom Widget - Email widgettutorial.Build a Jupyter Widget with React and TypeScriptblog post by John Waidhofer.jupyter-widget-react-cookiecuttertemplate by John Waidhofer.react-colorfulpackage.widget-cookiecuttertemplate.How To Add Custom Build Steps and Commands To setup.pyblog post by Chuan Ji.Creating Reactive Jupyter Widgets With Svelteblog post by Alex Cabrera.widget-svelte-cookiecuttertemplate by Alex Cabrera.How to delete a tag in Gitblog post by Manik Rathee.Developmentmamba env create -f environment.ymlormamba create -n ipycolorful-dev -c conda-forge jupyterlab jupyter-packaging nodejs yarn python.conda activate ipycolorful-dev.pip install -e .+conda list.JupyterLab (source):jupyter labextension develop --overwrite ..Jupyter Notebook/classic notebook (source):jupyter nbextension install --sys-prefix --symlink --overwrite --py ipycolorful.jupyter nbextension enable --sys-prefix --py ipycolorful.yarn run clean+yarn run build.jupyter laborjupyter notebook.Deploymentconda activate ipycolorful-dev.Update the version in thepackage.json,ipycolorful/_version.py, and/oripycolorful/_frontend.pyfiles.npm pack --dry-run.yarn login.yarn publish.yarn run clean.python -m build --no-isolation ..After removing the old files:twine check dist/ipycolorful*(vs.twine check dist/*).twine upload dist/ipycolorful*(vs.twine upload dist/*).git tag 0.1.0(update the version).git tag.GitHub Desktop +git push --tags.Notesmamba:mamba --version.Documentation.condashould be used for activation and deactivation.Reimplement: mamba env create -f env.yml(open) issue.conda deactivate+mamba env remove -n ipycolorful-dev(source).conda-forge.conda-lock.ipycanvas.bqplot.babel-loader..yarnrcfile.Node.js releases.Collection of React Hooks.check-manifest:check-manifest --help.check-manifest -v.check-manifest -u -v.check-manifestbecame super slow(open) issue.Alternative:manifix.setup-cfg-fmt:setup-cfg-fmt setup.cfg.Taplo:VS Code extension.Repo.Online editor.Configuration.Validation schemas.@jupyterlab/builderpackage:Try to match the version with that ofjupyterlab(Python).Configuration(package.jsonfile).CLI(andgenerateConfig()).gitignore_parserpackage.Rendering Interactive Widgets on nbviewer.
Package: ipycov
[![Build Status](https://travis-ci.org/sanbales/ipython-coverage.svg?branch=master)](https://travis-ci.org/sanbales/ipython-coverage)# IPython CoverageIntroduces `%coverage` and `%%coverage` magics to allow runningof [coverage](https://github.com/nedbat/coveragepy)from a [Jupyter Notebook](https://github.com/jupyter/notebook).It currently presents the coverage HTML report as an IFrame.# Installation```bashpip install ipycoverage```# Usage## Load the extension```ipython%load_ext ipycov```## Use the magicIn a cell, you can run the cell magic like such:```ipython%%coveragefrom your_module import your_function  # or anything else you want to importyour_function()```twine register dist/pad-on-left-1.0.0.tar.gz -r testpypiOr simply run the line magic:```ipython%coverage function_to_call()```# Important Note> This is not a fully developed magic, and it is not stable yet.>> It has only been tested against:> * `coverage==4.5.2`> * `IPython==7.0.1`.> * `JupyterLab==0.35.1`## Missing Features / Future Work* Improve naming and instructions* Add more options; potentially dynamically load them from `coverage`* Add tests* Add examples* Add CI/CD* Submit to PyPI and Conda
Package: ipyd3
ipyd3Library for visualizing D3.js inside Jupyter.InstallationTo install use pip:$ pip install ipyd3For a development installation (requiresNode.jsandYarn version 1),$ git clone https://github.com//ipyd3.git
$ cd ipyd3
$ pip install -e .
$ jupyter nbextension install --py --symlink --overwrite --sys-prefix ipyd3
$ jupyter nbextension enable --py --sys-prefix ipyd3When actively developing your extension for JupyterLab, run the command:$ jupyter labextension develop --overwrite ipyd3Then you need to rebuild the JS when you make a code change:$ cd js
$ yarn run buildYou then need to refresh the JupyterLab page when your javascript changes.
Package: ipydagred3
ipydagred3ipywidgets library for drawing directed acyclic graphs in jupyterlab usingdagre-d3InstallationYou can install usingpip:pipinstallipydagred3FeaturesDynamically create and modify graphs from pythonChange color, shape, tooltip, etcClick events (click on node or edge and get event in ipywidget indicating source, good for node inspector tools)Tooltips and Click eventsExamplesNetwork example from the first gifNetwork ExampleTooltip Example from the second gifTooltip Example
Package: ipydataclean
Jupyter notebook extension and python library for interactive cleaning of pandas DataFrames with a selection of techniques, from simple replacements of missing values to imputation with a Restricted Boltzmann Machine.Installationpipinstallipydatacleanjupyternbextensionenabledataclean--py--sys-prefixUsageUse your Jupyter notebook as normal. When a pandas DataFrame is present in your python kernel you should see a new notification on the Data Cleaner icon in your toolbar. DataFrames with names beginning with an underscore will be ignored.Data Cleaner toolbar icon.Clicking on the icon will open a floating window containing a summary of the DataFrames in your kernel. Clicking on the name of one of these DataFrames will show some of the Data Cleaner controls and some summary statistics on the DataFrame columns.Data Cleaner window.Clicking on the name of one of these columns will show data cleaning tools specific to that column, with a histogram or bar chart showing the distribution of these values. As you create a step the effect that this will have on the data distribution is shown as a preview.Creating a data cleaning step on a column.You can also choose to fill in missing and mistyped values in your DataFrame with a Restricted Boltzmann Machine. This uses the boltzmannclean package.Creating a Restricted Boltzmann Machine cleaning step.Once you create your steps they are added to a processing pipeline which can be viewed in the “Pipeline” widget.A data cleaning pipeline.These steps can be modified or deleted using these controls, and when ready the pipeline can be executed on the dataframe or output to code. Executing your pipeline will create a new DataFrame with the suffix “_cleaned” in your kernel, while exporting will create a new code cell in your notebook defining a python function which will carry out the pipeline cleaning steps.An exported pipeline.CaveatsDuplicated or non string column names are not supported.For DataFrames over 1000 rows, a sample of 1000 rows will be used for previewing and creating your processing pipeline, with the whole DataFrame only operated on when the pipeline is executed.
Package: ipydatagrid
ipydatagridFast Datagrid widget for the Jupyter Notebook and JupyterLabMenuUsage and ExamplesInstallationDevelopment installationContributionsLicenseCode of ConductSecurity Vulnerability reportingUsage and ExamplesA fully-featured DataGrid interfaceHighly performant and fully integrated with ipywidgetsCustomize the way data is represented in your grid using a variety of renderersEnjoy a sophisticated selections model with two-way data bindingConditional formatting powered by Vega ExpressionsTutorial and example notebooks can be found in the/examplesdirectory.InstallationIf using JupyterLab,ipydatagridrequires JupyterLab version 3 or higher.You can installipydatagridusingpiporconda:Usingpip:pipinstallipydatagridUsingconda:condainstall-cconda-forgeipydatagridIf you are using Jupyter Notebook 5.2 or earlier, you may also need to enable
the nbextension:jupyternbextensionenable--py[--sys-prefix|--user|--system]ipydatagridNOTE: For examples using Scales from bqplot to work as intended, the bqplot notebook and lab extensions must be installed as well. See thebqplot repofor installation instructions:Development installationFor a development installation:gitclonehttps://github.com/Bloomberg/ipydatagrid.gitcdipydatagrid
condainstallipywidgets=8jupyterlab
pipinstall-ve.Enabling development install for Jupyter notebook:jupyternbextensioninstall--py--symlink--sys-prefixipydatagrid
jupyternbextensionenable--py--sys-prefixipydatagridEnabling development install for JupyterLab:jupyterlabextensiondevelop.--overwriteNote for developers: the--symlinkargument on Linux or OS X allows one to modify the JavaScript code in-place. This feature is not available with Windows.
`ContributionsWe :heart: contributions.Have you had a good experience with this project? Why not share some love and contribute code, or just let us know about any issues you had with it?We welcome issue reportshere; be sure to choose the proper issue template for your issue, so that we can be sure you're providing the necessary information.Before sending aPull Request, please make sure you read ourContribution Guidelines.LicensePlease read theLICENSEfile.Code of ConductThis project has adopted aCode of Conduct.
If you have any concerns about the Code, or behavior which you have experienced in the project, please
contact us atopensource@bloomberg.net.Security Vulnerability ReportingIf you believe you have identified a security vulnerability in this project, please send email to the project
team atopensource@bloomberg.net, detailing the suspected issue and any methods you've found to reproduce it.Please do NOT open an issue in the GitHub repository, as we'd prefer to keep vulnerability reports private until
we've had an opportunity to review and address them.
Package: ipydb
ipydb is anIPythonplugin for running SQL queries and viewing their results.UsageSome demonstration videos are available in thedocumentation$ ipython
In [1] : %load_ext ipydb
In [2] : %automagic on
Automagic is ON, % prefix IS NOT needed for line magics.

In [3] : connecturl mysql://user:pass@localhost/employees
In [4] localhost/employees: tables
departments
dept_emp
dept_manager
employees
salaries
titles

In [5] localhost/employees: fields departments
departments
-----------
    dept_name                          VARCHAR(40)
    dept_no                            CHAR(4)

In [6] localhost/employees: select * from departments order by dept_name
+---------+--------------------+
| dept_no | dept_name          |
+---------+--------------------+
| d009    | Customer Service   |
| d005    | Development        |
| d002    | Finance            |
| d003    | Human Resources    |
| d001    | Marketing          |
| d004    | Production         |
| d006    | Quality Management |
| d008    | Research           |
| d007    | Sales              |FeaturesTab-completion of table names, fields and joinsView query results in ascii-table format piped through lessSingle-line or multi-line query editingTab-completion metadata is read in the background and persisted across sessionsCross-database support, thanks to SqlAlchemy:supported databasesInstallationTo install ipydb:$pipinstallipydbYou will need a python driver for your database of choice. For example:$pipinstallmysql-pythonipydb usesSqlAlchemyto interact with databases.
See theSupported Databasespage
for a (large!) list of supportedDB-API 2.0drivers and how to
write a connection URL for your particular database.Start ipython and load the ipydb plugin:$ipythonIn[1]:load_extipydbDocumentationDocumentation is available at:http://ipydb.readthedocs.orgConnecting to DatabasesThere are two ways to connect to a database with ipydb. Directly via a connection url, using
theconnecturlmagic function, or, using a connection ‘nickname’ with theconnectmagic function.1. UsingconnecturlYou can connect to a database using an SqlAlchemy style url as follows:%connecturl drivername://username:password@host/databaseSome examples:In [3] : connecturl mysql://myuser:mypass@localhost/mydatabase
In [4] : connecturl sqlite:///path/to/mydb.sqlite
In [5] : connecturl sqlite:///:memory:See theSqlAlchemy Documentationfor further information.2. Usingconnectand a.db-connectionsconfiguration fileFor this to work, you need to create a file called.db-connectionslocated in your home directory..db-connectionsis an “ini” formatted file,
parsable by python’s ConfigParser module.Here’s an example of what~/.db-connectionsmight look like:[mydb]type=mysqlusername=rootpassword=xxxxhost=localhostdatabase=employees[myotherdb]type=sqlitedatabase=/path/to/file.sqliteEach database connection defined in~/.db-connectionsis
then referenceable via its [section heading]. So with the
above.db-connectionsfile, the following examples would work:In [6] : connect mydb
In [7] mydb : connect myotherdb
Package: ipydeck
ipydeckipydeckis yet another Jupyter widget fordeck.gl, built onanywidget.InstallationpipinstallipydeckUsageFromhttps://deck.gl/playground:fromipydeckimportDeck,Layer,ViewStatelayers=[Layer(type="GeoJsonLayer",data="https://raw.githubusercontent.com/visgl/deck.gl-data/master/examples/geojson/vancouver-blocks.json",opacity=0.8,stroked=False,filled=True,extruded=True,wireframe=True,elevation_scale=0.1,get_elevation="@@=properties.valuePerSqm",get_fill_color=[199,233,180],get_line_color=[255,255,255],)]view_state=ViewState(latitude=49.254,longitude=-123.13,zoom=11,max_zoom=16,pitch=45,bearing=0)deck=Deck(layers=layers,initial_view_state=view_state,map_style="light",)deckAlternativespydecklonboardLicenseMIT
Package: ipydex
IPython based debugging and exploring toolThis package provides the following features:IPS()– An embedded IPython shell with some extra features like conditional execution:IPS(x>0).activate_ips_on_exception()– Open an IPython shell in the frame where an exception is raised, but with the ability to move to other frames.dirsearch– easily search for substrings in the attribute list of an object or in the keys of a dict.displaytools– an extesion for jupyter notebooks to display intermediate results (e.g. of assignments). Useful for didactic purposes.