Saravanan666/pypi-org huggingface dataset:
Package: ipynao
ipynaoA widget library for controlling NaoInstallationYou can install usingpip:pipinstallipynaoIf you are using Jupyter Notebook 5.2 or earlier, you may also need to enable
the nbextension:jupyternbextensionenable--py[--sys-prefix|--user|--system]ipynaoDevelopment InstallationCreate a dev environment:condacreate-nipynao-dev-cconda-forgenodejsyarnpythonjupyterlab
condaactivateipynao-devInstall the python. This will also build the TS package.pipinstall-e".[test, examples]"When developing your extensions, you need to manually enable your extensions with the
notebook / lab frontend. For lab, this is done by the command:jupyter labextension develop --overwrite .
yarn run buildFor classic notebook, you need to run:jupyter nbextension install --sys-prefix --symlink --overwrite --py ipynao
jupyter nbextension enable --sys-prefix --py ipynaoNote that the--symlinkflag doesn't work on Windows, so you will here have to run
theinstallcommand every time that you rebuild your extension. For certain installations
you might also need another flag instead of--sys-prefix, but we won't cover the meaning
of those flags here.How 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>
Package: ipynavis-3d-poc
ipynavis-3d-pocA Custom Jupyter Widget LibraryInstallationYou can install usingpip:pipinstallipynavis_3d_pocIf you are using Jupyter Notebook 5.2 or earlier, you may also need to enable
the nbextension:jupyternbextensionenable--py[--sys-prefix|--user|--system]ipynavis_3d_pocDevelopment InstallationCreate a dev environment:condacreate-nipynavis_3d_poc-dev-cconda-forgenodejsyarnpythonjupyterlab
condaactivateipynavis_3d_poc-devInstall the python. This will also build the TS package.pipinstall-e".[test, examples]"When developing your extensions, you need to manually enable your extensions with the
notebook / lab frontend. For lab, this is done by the command:jupyter labextension develop --overwrite .
yarn run buildFor classic notebook, you need to run:jupyter nbextension install --sys-prefix --symlink --overwrite --py ipynavis_3d_poc
jupyter nbextension enable --sys-prefix --py ipynavis_3d_pocNote that the--symlinkflag doesn't work on Windows, so you will here have to run
theinstallcommand every time that you rebuild your extension. For certain installations
you might also need another flag instead of--sys-prefix, but we won't cover the meaning
of those flags here.How 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.
Package: ipynb2catsoop
ipynb2catsoopconvert ipython / jupyter notebooks to catsoop pageusage: ipynb2catsoop [-h] [-v] [-u UNIT_NAME] [-d DIRECTORY] ifn

usage: %prog [args...] notebook.ipynb

positional arguments:
  ifn                   input ipython / jupyter notebook file

optional arguments:
  -h, --help            show this help message and exit
  -v, --verbose         verbose output
  -u UNIT_NAME, --unit-name UNIT_NAME
                        catsoop unit name (subdir where content.md is to be stored
  -d DIRECTORY, --directory DIRECTORY
                        directory where course content is located
Package: ipynb2rmd
Usage# Generate test.rmd$ipynb2rmdtest.ipynb# Generate test.rmd and run R Markdown to render as pdf$ipynb2rmdtest.ipynb--compile# Compile an already existing rmd file$ipynb2rmdtest.rmd--compileChunk OptionsTo use rmarkdown chunk options in your Jupyter notebook, start a code cell with#r <chunk options>.InstallationTo install ipynb2rmd, simply:$pipinstallipynb2rmdRequirementshttps://github.com/IRkernel/IRkernelhttps://github.com/rstudio/rmarkdown
Package: ipynb2viewer
##ipynb2viewerPost IPython notebook files to nbviewer. IPython notebook content will be posted to gist.github.com.Install------ `pip install ipynb2viewer`Usage-----Upload all ipynb files in the given path to gist.github.com and return nbviewer urls.- `ipynb2viewer all <path>`Upload mentioned file to gist.github.com as private and return nbviewer urls.- `ipynb2viewer file <filename> --private`Upload mentioned file to gist.github.com and return nbviewer url.- `ipynb2viewer file <filename>`Upload mentioned file to gist.github.com and open nbviewer url in webbrowser.- `ipynb2viewer file <filename> --open`Upload all ipynb files in the given path to gist.github.com and open nbviewer urls in webbrowser.- `ipynb2viewer all <path> --open`- Free software: BSD licenseHistory-------0.1.0 (2013-12-22)++++++++++++++++++* First release on PyPI.
Package: ipynbcompress
OverviewSo you have included an image withIPython.display.Image()and the
file size of your IPython Notebook got huge? No problem! This package
will resize images in your notebook and compress them as PNG or JPEG.
Images are only resized if they are above the specified width. 2048px
and PNG compression is the default, which should give relative high
quality images and normal sized notebooks. JPEG compression is nice if
you serve the notebooks over the web (eg nbviewer) and prefer fast
loading times.InstallationInstall usingpip…pipinstallipynbcompressExampleFrom command line:$ipynb-compressnotebook4.ipynbnotebook4.ipynb:10megabytesdecrease$find.-name"*ipynb"-size+2M-execipynb-compress{}\;./lab03.21/automatedscan.ipynb:warning:nocompression-0bytesgained./lab03.21/automatedscan.ipynb:compressionlessthan100kbytes-keepingoriginal./lab03.21/trouble.ipynb:9megabytesdecrease...In python:>>>importos>>>fromipynbcompressimportcompress>>>filename='/path/to/notebook.ipynb'>>>out='/path/to/compressed.ipynb'>>># original size...os.stat(filename).st_size11563736>>># return bytes saved...compress(filename,output_filename=out,img_width=800,img_format='jpeg')11451545>>>compress(filename,output_filename=out,img_width=800,img_format='png')11205762>>># defaults to img_width = 2048px and png compression...compress(filename,output_filename=out)11411377>>># overwrite existing notebook...compress(filename)11411377API referenceAPI reference is athttp://ipynbcompress.rtfd.org.DevelopmentInstall dependencies and link development version of ipynbcompress to
pip:gitclonehttps://github.com/arve0/ipynbcompresscdipynbcompresspipinstall-rrequirements.txt# install dependencies and ipynbcompress-packageTestingpytestBuild documentation locallyTo build the documentation:pipinstall-rdocs/requirements.txtmakedocs
Package: ipynb-conversor
Jupyter notebook to Python file conversorContributorsThanks goes to these wonderful people (emoji key):<td align="center"><a href="https://github.com/vitia-fritelle"><img src="https://avatars.githubusercontent.com/u/71563179" width="100px;" alt=""/><br /><sub><b>Vitor Junior</b></sub></a><br /><a href="https://github.com/organizar-bot/commits?author=vitia-fritelle" title="Code">💻</a></td>Examples of How to Use ItOn a Python program:fromipynb_converterimportipynb_converterfile_path="jupyter_notebook.ipynb"save_name="python_file.py"#optionalipynb_converter(file_path,save_name)On command line:py -m ipynb_converter "jupyter_notebook.ipynb" "python_file.py"orpy -m ipynb_converter "jupyter_notebook.ipynb"This project follows theall-contributorsspecification. Contributions of any kind welcome!
Package: ipynb_format
ipynb_format.pyis a small script to format the python code in ipython notebooks.
The code formatter is based onyapf.InstallationTo install from PyPI on Linux:$pipinstallipynb_formator from Github:$pipinstall--upgradehttps://github.com/fg1/ipynb_format/archive/master.tar.gzUsageusage:ipynb_format[-h][--styleSTYLE][files[files...]]Formatipythonnotebookusingyapfpositionalarguments:filesoptionalarguments:-h,--helpshowthishelpmessageandexit--styleSTYLEyapfstyletouseThe formatting style option is the same as foryapf.
Package: ipynb-image-extract
ipynb-image-extractoripynb-image-extractor is a Python package that allows you to easily extract images from IPython Notebooks and save them to a specified output folder.InstallationYou can install ipynb-image-extractor via pip:pipinstallipynb-image-extractUsageOnce installed, you can use the extract-images command to extract images from an IPython Notebook file and save them to an output folder. Here's the basic usage:extract-imagesinput.ipynboutput_folderinput.ipynb: The path to the IPython Notebook file from which you want to extract images.output_folder: The folder where the extracted images will be saved.How it WorksThe package utilizes thenbformatandPillowlibraries to parse the IPython Notebook and extract image data from 'image/png' outputs. The images are saved in PNG format.ContributionsContributions are welcome! If you encounter issues, have ideas for improvements, or want to contribute to the project, please open an issue or submit a pull request on theGitHub repository.LicenseThis project is licensed under the MIT License - see theLICENSEfile for details.
Package: ipynbname
ipynbnameWhen run in a Jupyter notebook, simply returns the notebook filename or the full path to the notebook.
I created this to help with automating posting blog posts written in Jupyter notebooks directly to
GitHub Pages.You would think there was already some built-in way to access the current notebook name, but it took many hours
of searching for a way to do it. As it seems many others did, I tried using Javascript, but the async nature of
JS meant that it was unreliable. Finally I stumbled on thispost.
I have refactored the code there so a user can get either the name or path, but credit for most of the code
goes to the author of this post, thanks!ExamplesGet the notebook name:importipynbnamenb_fname=ipynbname.name()Get the full path to the notebook:importipynbnamenb_path=ipynbname.path()LimitationsNote that this only reliably works when running a notebook in a browser. So it does not currently work for things like nbconvert or papermill.For VS Code there is aworkaround.
Package: ipynb-path
A simple python package to get the path of the current IPython / Jupyter Notebook file.Installationpipinstallipynb-pathUsageIf you can access to your Jupyter Notebook/Lab server without a password,
you can use justipynb_path.get()in a.ipynbfile.importipynb_path__file__=ipynb_path.get()If you need a password to access the server, you should specify it.importipynb_path__file__=ipynb_path.get(password='foo')You can also specify__name__for compatibility between.pyand.ipynb.
In this case,ipynb_path.get()does not overwrite__file__even if it is called in a.pyfile.importipynb_path__file__=ipynb_path.get(__name__)
Package: ipynb-py-convert
ipynb-py-convertAtom/Hydrogen or VSCode/Python allows creating a python files split into cells with# %%separators with the ability to run cells via backend Jupyter session and interactively show results back.More examples:Jupyter Python VSCode examples,Atom/Hydrogen Getting Started.ipynb-py-convertpython module converts files: .ipynb to .py and .py to .ipynb.ipynb-py-convertis a fork of thevscode-ipynb-py-converter.Installcondainstall-cdefaults-cconda-forgeipynb-py-convertorpipinstallipynb-py-convertTroubleshootingIf encoding problems on Windows try usingpython>=3.7, settingset PYTHONUTF8=1in Windows console and useipynb-py-convertfor UTF-8 files only. If usingGit-Bash on Windowssetting:exportLANG=C.UTF-8exportPYTHONIOENCODING=utf-8exportPYTHONUTF8=1should be enough. Also try setting default Bash settings to UTF-8: [Options] - [Text] - [Locale / Character set] - [C / UTF-8]. It might affect all Bash runs so there would be no need to setting encoding every time.Exampleipynb-py-convert examples/plot.py examples/plot.ipynboripynb-py-convert examples/plot.ipynb examples/plot.pyVSCodeMarkdown cells are converted to python multiline strings'''. Code cells are left as is.# %%is used by vscode as the cell marker on which 'Run Cell' action is available.Jupyter ipynb notebook
Package: ipyniivue
ipyNiiVueipyNiiVue is a Python /Niivuebridge forJupyter Widgets. A Python API is used to interact with NiiVue.Try it onlineYou can try ipyniivue online at,, or.Getting startedInstallationpipinstallipyniivueDevelopmentcondacreate-nipyniivue-dev-cconda-forgenodejsyarnpythonjupyterlab=3.6.3
condaactivateipyniivue-dev
gitclonehttps://github.com/niivue/ipyniivue.gitcdipyniivue
yarninstall
jupyterlabextensiondevelop--overwrite.
yarnrunwatchThen, in another terminal/cmd window:cdipyniivue
condaactivateipyniivue-dev
jupyterlabTo view changes made in the typescript, reload the jupyter page. To view changes made in the python, restart the kernel.Usagedocumentation
Package: ipyniivue-experimental
ipyniivue_experimentalpython3.11-mvenv.venv&&source.venv/bin/activate
pipinstallipyniivue_experimental
pipinstalljupyterlabExamplefrom ipyniivue_experimental import AnyNiivue

nv = AnyNiivue()
nv# second cell, wait for one second till the frontend code from cell1 is done loading.
my_volumes = [
           { "url": "https://niivue.github.io/niivue/images/mni152.nii.gz" }
        ]
nv.load_volumes(my_volumes)How this project was made:This project was made withnpm create anywidget@latestcreate-anywidget version 0.4.5┌  Welcome to anywidget!
│
◇  Where should we create your project?
│  .
│
◇  Directory not empty. Continue?
│  Yes
│
◇  Which framework?
│  Vanilla
│
◇  Which variant?
│  JavaScript
│
└  Your project is ready!3npm install4npm i @niivue/niivuepython3.11 -m venv .venv && source .venv/bin/activate
pip install -e ".[dev]"npm run dev# Changelog:

## v0.0.5 

Adding functions 
load_volumes, load_meshes, set_opacity, set_crosshair_width and set_crosshair_color.



## v0.0.4

Setting up the project
Package: ipynose
ipynoseprint nosetests result in the iPython (notebook)iPython notebook examplehere.Usagefromipynoseimportipynose1. no pathnosetests without specific path.(-voption default)ipynose.show_nose_result()1)Ifempty,Errorshouldoccur...SKIP:showingclassskippingFirstnodeshouldbeequaltolastnode...SKIP:showingclassskipping1)Lastnodeshouldcontaionsinsertedself.item...SKIP:showingclassskippingInitialQueue...SKIP:showingclassskipping1)'peek'returnsfirstnodeitem....SKIP:showingclassskippingtest_dequeue...oktest_enqueue_when_empty...oktest_enqueue_when_not_empty...oktest_make_queue...oktest_peek...ok----------------------------------------------------------------------Ran10testsin0.014sOK(SKIP=5)2. Specific pathnosetests for specific file.(-voption default)EXAMPLE_TEST_PATH="py/queue/tests/test_queue.py"ipynose.show_nose_result(EXAMPLE_TEST_PATH)test_dequeue...oktest_enqueue_when_empty...oktest_enqueue_when_not_empty...oktest_make_queue...oktest_peek...ok----------------------------------------------------------------------Ran5testsin0.001sOK
Package: ipynta
ipyntais a Python library designed for rapid development of image pre-processing pipelines.InstallationpipinstallipyntaHigh level overviewThe diagram above describes the purpose of each iPynta class family and how can they be used collectively in an image pre-processing pipeline.Core Class FamiliesSourcingPredicatesTransformersPersistenceUtility Class FamiliesLoadersPackagingWhy was it named ipynta?I-pintameans"to paint"in tagalog! This library is proudly developed by a Singapore-based Filipino lad with nothing better to do during evenings.
Package: ipyobservable
ipyobservableJupyter widget for ObservableInstallationTo install use pip:$ pip install ipyobservableFor a development installation (requiresNode.jsandYarn version 1),$ git clone https://github.com/davidbrochart/ipyobservable.git
$ cd ipyobservable
$ pip install -e .
$ jupyter nbextension install --py --symlink --overwrite --sys-prefix ipyobservable
$ jupyter nbextension enable --py --sys-prefix ipyobservableWhen actively developing your extension for JupyterLab, run the command:$ jupyter labextension develop --overwrite ipyobservableThen 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: ipypandas
ipypandas[!NOTE]
❗ PROOF OF CONCEPT, WORK IN PROGRESS ❗Interactive features for the python data analysis library pandas in jupyter.Pandas dataframes are rendered via ipypandas, which enables these interactive features (fully server side):Lazy loadingSort columnsResize columnsReorder columnsSearch valuesFilter valuesThe rendering has been tested for the following development environments (full theme support):JupyterLabJupyterNotebookVisual Studio CodePyCharm ProfessionalInstallationTo get started with ipypandas, install it viapip:pipinstallipypandasUsageImporting ipypandas will enable the interactive pandas output globally:importpandasaspd...importipypandasMore information can be found on thedocumentationpage.DevelopmentCreate a dev environment:mambacreate-nipypandaspython=3.12jupyterlab=4.0nodejs=20.5
mambaactivateipypandasInstall python module and build typescript dependencies:pipinstall-e.[dev]While developing you need to manually enable your extensions with the frontend. For JupyterLab, this is done by the command:jupyterlabextensiondevelop--overwrite.TypescriptIf 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.jlpmclean&&jlpminstall&&jlpmbuild&&jlpmwatchAfter a change wait for the build to finish and then refresh your browser and the changes should take effect.PythonIf you make changes to the python code then you will need to restart the notebook kernel to have it take effect.CommandsSome commands which may be useful for development.Installjlpmclean&&jlpminstall&&jlpmbuild
pipuninstallipypandas&&pipinstall-e.[dev]Registerjupyterlabclean
jupyterlabextensionlist
jupyterlabextensiondevelop--overwrite.Examplesjupyterlab./examplesDocumentationcddocs
makehtmlVersioningtbump0.1.xCreditsBased on thecookiecutter templatefromjupyter-widgets.LicenseBSD-3-Clause
Package: ipyparallel
Interactive Parallel Computing with IPythonIPython Parallel (ipyparallel) is a Python package and collection of CLI scripts for controlling clusters of IPython processes, built on the Jupyter protocol.IPython Parallel provides the following commands:ipcluster - start/stop/list clustersipcontroller - start a controlleripengine - start an engineInstallInstall IPython Parallel:pip install ipyparallelThis will install and enable the IPython Parallel extensions
for Jupyter Notebook and (as of 7.0) Jupyter Lab 3.0.RunStart a cluster:ipcluster startUse it from Python:importosimportipyparallelasippcluster=ipp.Cluster(n=4)withclusterasrc:ar=rc[:].apply_async(os.getpid)pid_map=ar.get_dict()Seethe docsfor more info.
Package: ipyparams
ipyparamsSend parameters/arguments to notebooks via URL query string parameters.ExamplesIf you want to prepopulate parameters likefoo=barandbaz=1in a notebook, you can simply encode them in the URL:https://your.jupyter.server/awsome_notebook.ipynb?foo=bar&baz=1In the notebook, just include the following:importipyparamsThe values are now accessible in theipyparams.paramsdictionary.ipyparams.params['foo']# returns "bar"ipyparams.params['baz']# returns "1"Duplicate parametersURL query strings can contain multiple parameters with the same name, such ashttps://your.jupyter.server/awsome_notebook.ipynb?foo=bar&foo=baz.  Theipyparams.paramsdictionary only contains the last value for each name, but you can still access all the "raw" parameters usingipyparams.raw_paramsdictionary.importipyparamsipyparams.params['foo']# returns 'baz'ipyparams.raw_params['foo']# returns ['bar', 'baz']Missing parametersIf you try to access a parameter that does not exist, you will simply getNoneback.importipyparamsipyparams.params['unicorn']# returns Noneipyparams.raw_params['unicorn']# returns NoneGet the notebook nameimportipyparamsipyparams.notebook_name# returns 'awesome_notebook.ipynb'Get the full, raw URL of the notebookimportipyparamsipyparams.raw_url# returns https://your.jupyter.server/awsome_notebook.ipynb?foo=bar&baz=1
Package: ipypb
Interactive ProgressBarPython progress bar that uses native ipython functionality. Widget-free. Works even in JupyterLab.The reason for creating this package is that other progress bars use custom bar objects and/or widget tools, ignoring the builtinIPythonfunctionality. This makes them unusable in "clean" environments like JupyterLab. In contrast,ipypbcan run even in very restricted environments.Another useful feature ofipypbis that the progress bar information is available even after closing a notebook and killing its ipython kernel. Once you launch this notebook again, you'll see the same progress bar information as before closing instead of widjet-related erorrs likeFailed to display Jupyter Widget of type HBox, as shown below:Also have a look at thisNBViewer example.NotesCurrently at beta stage.Simple usage example:fromtimeimportsleepfromipypbimporttrackforiintrack(range(10)):sleep(0.1)A few other conveniences are available. For example, you can useipypbas a python's range-like function:fromipypbimportirangeforiinirange(1,10,2):# same as range(1, 10, 2) but with progressbar# <do stuff>...It may also be helpful to use the factory methodipb, which handles different usage scenarios and returns eithertrackorirangeinstance depending on input arguments. Another usage example is when you already have a bunch of code withtqdmand want to
replace it withipypb:fromipypbimportipbtqdm_notebook=ipb# or if you run it in interactive shelltqdm=ipbIt will automatically process keyword arguments to ensure compatibility withtqdm's API. Note, thatipboffers a common interface for both notebook and terminal environments.Asynchronous flowIt's also possible to useipypbfor tracking tasks that are executed asyncrhonously or in parallel. The major use case is when the order of executed tasks from a task pool doesn't correspond to the desired order for displaying a progress. In this case, you can instructipypbto preserve the desired order by submitting a description of the progress hierarchy. Below is an example for simple heirarchy consisting of three levels:i <-- j <-- k. Progress on each parent level depends on full exectunion of its sublevels. Note how levelsk:1andk:2get moved to the groupj:0they belong to, even though initially they appear in the end, below thej:1group:Note: this feature is currently in provisional state, which means that its API main change in future releases. In order to test it, dofromipypbimportchainInstallpip install --upgrade ipypbRequirementsPython 3.6+ and IPython v.5.6+ excluding v.6.1 and v.6.2LimitationsThe feature to erase progressbar when loop is over is not yet supported.
Package: ipy-pdcache
%%pdcache cell magicAutomatically cache results of intensive computations in IPython.Inspired byipycache.Installation$pipinstallipy-pdcacheUsageIn IPython:In[1]:%load_extipy_pdcacheIn[2]:importpandasaspdIn[3]:%%pdcachedfdata.csv...:df=pd.DataFrame({'A':[1,2,3],'B':[4,5,6]})...:In[4]:!catdata.csv,A,B0,1,41,2,52,3,6This will cache the dataframe and automatically load it when re-executing the cell.