Saravanan666/pypi-org huggingface dataset:
Package: jupysql
JupySQLJoin our community|Newsletter|Contact us|Docs|Blog|Website|YouTube[!TIP]
Deploy AI apps for free onPloomber Cloud!Run SQL in Jupyter/IPython via a%sqland%%sqlmagics.FeaturesPandas integrationSQL composition (no more hard-to-debug CTEs!)Plot massive datasets without blowing up memoryDuckDB integrationInstallationpip install jupysqlor:conda install jupysql -c conda-forgeDocumentationClick here to see the documentation.CreditsThis project is a fork ofipython-sql; the objective is to turn this project into a full-featured SQL client for Jupyter. We're looking for feedback and taking feature requests, so pleasejoin our communityand enter the #jupysql channel.
Package: jupytab
Jupytab allows you toexplore in Tableau data which is generated
dynamically by a Jupyter Notebook. You can thus create Tableau data
sources in a very flexible way using all the power of Python.
This is achieved by having Tableau access data through aweb
server created by Jupytab.This package is an helper package to split dependencies between
Jupytab server and your notebook. It only requires pandas.The full documentation is available on the project's home page.
Package: jupytab-server
Jupytab Server allows you toexplore in Tableau data which is generated
dynamically by a Jupyter Notebook. You can thus create Tableau data
sources in a very flexible way using all the power of Python.
This is achieved by having Tableau access data through aweb
server created by Jupytab.Jupytab Server is built onsolid foundations: Tableau's Web Data
Connector and the Jupyter Kernel Gateway.Features:Expose multiple pandas dataframesto Tableau from a Jupyter
notebookAccessseveral notebooksfrom Tableau through asingle
entry point(web server)Manage your notebooks using aweb interfaceSecure accessto your dataThe full documentation is available on the project's home page.
Package: jupytalk
jupytalkContents used and most of the time maintained for
presentation, talks, shows, teachings…GitHub/jupytalkdocumentationBlogHistorycurrent - 2021-01-05 - 0.00Mb0.0.0 - 2021-01-05 - 0.00Mb15: remove ggplot (not maintained anymore) (2019-01-28)13: add notebook on scikit-plot (2018-10-14)4: replace basemap by cartopy (2018-07-24)9: add notebook on pyecharts (2018-07-05)8: try catch around ggplot (not maintained anymore) (2018-05-24)7: split unit test on ggplot - failing on appveyor (2018-03-28)6: fix notebook on pythreejs (update to 1.0.0) (2018-03-22)5: fix unit test with ete3 (2017-12-20)
Package: jupyteach-jupyterlite-contents
jupyteach_jupyterlite_contentsA JupyterLite server extension.RequirementsJupyterLite >= 0.1.0b15InstallTo install the extension, execute:pipinstalljupyteach_jupyterlite_contentsThen build your JupyterLite site:jupyterlitebuildUninstallTo remove the extension, execute:pipuninstalljupyteach_jupyterlite_contentsContributingDevelopment 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 jupyteach_jupyterlite_contents directory# Install package in development modepython-mpipinstall-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).Development uninstallpipuninstalljupyteach_jupyterlite_contentsIn 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@jupyteach/jupyterlite-contentswithin that folder.Packaging the extensionSeeRELEASE# first incremement version numbers in _version.py and package.json# npmyarnrunbuild:prod
npmpublish--accesspublic# pythonpython-mbuild
twineuploaddist/*
Package: jupytee
jupytee - magics for using GPT-like models inside JupyterA small, experimental playground with Jupyter magics to use OpenAI's GPT-3 models inside Jupyter environments.This isn't even alpha software - it's just a quick and dirty prototype.  But it works, if you have the pythonopenaipackage installed and the environment variableOPENAI_API_KEYdefined with your personal API key asper the docs.Yes, the name is a silly play on the pronunciation of GPT and Jupyter.Installationpip install jupyteeUsageTo load the extension, use%load_ext jupyteeThe package provides a few core magics,%chat,%picand%code(along with some extra helpers), that wrap your interactions around theOpenAI Python API. They target the main entry points of the API: text completion, image generation and code completion, respectively.You can see them in action in the notebook contained in theexamplesdirectory (which you can run immediately by clicking on the Binder button above).Briefly, these are some examples of how you can use them. A simple question (note the extra space before?, needed b/c IPython's help will otherwise trigger by accident):%chat What is 100F in Celsius ?You can control the sampling temperature with-T:%chat -T 1 --raw Write an uplifting short poemMarkdown (with math) work:%%chat
Produce the LaTeX form of Maxwell's equations.Forpic, you can control image size and the number of images returned:%pic -s m -n 2 an astronaut knittingWhen generating code, you can iteratively refine the answer by referring to theCODEspecial word (in all CAPS):%code A function to add two numbers.and then:%code Update CODE to have a docstring explaining its use.LicenseBSD 3-Clause.BSD 3-Clause LicenseCopyright (c) 2022, Fernando PérezRedistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:Redistributions of source code must retain the above copyright notice, this
list of conditions and the following disclaimer.Redistributions in binary form must reproduce the above copyright notice,
this list of conditions and the following disclaimer in the documentation
and/or other materials provided with the distribution.Neither the name of the copyright holder nor the names of its
contributors may be used to endorse or promote products derived from
this software without specific prior written permission.THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
Package: jupytemplate
Jupyter templateA simple template for jupyter notebooks.The extension sets up any new Jupyter Notebook
with a conventional and general-purpose
template to shape Data Science analysis.The template includes conventional sections,
likeData Import,ProcessingandReferences,
as well as code to perform common operations, like
importing and configuring charting libraries.Moreover, it prompts for a meaningful name whenever
you try and save a notebook called 'Untitled'.You find this annoying? Don't worry, you can disable
this one.MotivationJupyter notebooks are awesome tools: they enable fast
prototyping and ease result sharing. However, due to
their flexibility, they are prone to be abused.In order to help Data Scientists keep their notebooks
clean, a reasonably flexible yet conventional template
may help. Moreover, the template is also a
productivity tool, speeding up common setup,
such as library import and configuration.Quick startWe assume Jupyter notebook is already installed in your environment.
However, even if this is not tha case, don't worry: jupytemplate
declares Jupyter notebook as a dependency, thus any package manager,
like pip, will install it for you.It is not mandatory, but you can install the full set of Jupyter
extensions.pipinstalljupyter_contrib_nbextensions
jupytercontribnbextensioninstall--userFeel free to visittheir repositoryfor more information.Now you can install the package:pipinstalljupytemplateThen, you have to install the javascript files from
the Python package in a conventional jupyter directory:jupyternbextensioninstall--pyjupytemplate--sys-prefixFinally, you may want to enable the extension:jupyternbextensionenablejupytemplate/main--sys-prefixYou can easily enable, disable or configure the extension
by using thenbextension_configuratorserver extension, as shown below.Editing the templateTemplate location can be found by running:importjupytemplateprint(jupytemplate.get_template_path())Of course, you can edit the template as you like, in order
to adapt it to your own needs, but keep the file nametemplate.ipynb.After editing the template, run:jupyternbextensioninstall--pyjupytemplate--sys-prefix
jupyternbextensionenablejupytemplate/main--sys-prefixto make changes effective.ReferencesPlease consider reading the following resources for
a more comprehensive understanding:Will Kohersen,Set Your Jupyter Notebook up Right with this ExtensionWill Kohersen,How to Write a Jupyter Notebook ExtensionWill Kohersen,Setup extension
Package: jupyter2pytest
Jupyter Notebook GraderThis is a script that will compile a jupyter notebook with a specified structure into a python script that is pytest compatible.For use in code,extractorhandles extracting cells from a notebook with a given prefix into aTestcellBlockobject.compilerdeals more with taking an assignment notebook and a notebook with testcases,
which can be and often are the same notebook, and with specified prefixes and writing it into a python file capable of running against pytest. For example, the prefix for assignment code could be### ASSIGNMENT CODE for Puzzle (.*) ==where the group in the regex determines what test the code applies to. Prefixes must have at least one group to match against, and that first group will be the
identification used. To run as a CLI tool, usepython3 -m jupyter2pytest [code file] [code prefix] [test file] [test prefix] [pytest output file].
Package: jupyter-admin
🪐 💁 Jupyter Admin🛂Jupyter Adminis a UI (Web User Interface) and CLI (Command Line Interface) to manage the Datalayer Jupyter components.Jupyter Administration UI and CLI for the Jupyter ecosystem, with telemetry. It provides facilities to the Jupyter components to:DeployConfigureMonitorManage# Start the frontend webpack server and jupyter server.# echo open http://localhost:2003# echo open http://localhost:8686/hub/jupyter-admin# make start# Connect to the jupyterhub local sqlite database and run e.g.# .schema# .tables# .schema api_tokens# select * from api_tokens;# make sqlite# open http://localhost:3063# open http://localhost:8686/api/jupyter/lab?token=60c1661cc408f978c309d04157af55c9588ff9557c9380e4fb50785750703da6yarnstartpipinstall-e.[test]jupyterlabextensiondevelop.--overwrite
jupyterlabextensionlist# jupyter server extension enable datalayerjupyterserverextensionlist# open http://localhost:8686/api/jupyter/lab?token=60c1661cc408f978c309d04157af55c9588ff9557c9380e4fb50785750703da6yarnjupyterlab
Package: jupyter_aichat
!pip install jupyter-aichatCollecting jupyter_aichat
  Downloading jupyter_aichat-0.0.1-py2.py3-none-any.whl (3.9 kB)
Installing collected packages: jupyter_aichat
Successfully installed jupyter_aichat-0.0.1%load_ext jupyter_aichat%%ai
I've created an AI chat user interface for Jupyter notebooks.
It adds the `%ai` and `%%ai` magic commands for writing messages,
renders response messages in the notebook,
and keeps the whole conversation in memory.That sounds really interesting! Can you tell me more about how it works and what kind
of AI it uses?%%ai
The user just types `%ai "<message>"` or `%%ai` followed by a multi-line message.
It asks for the ChatGPT API key before sending the first message.
Both sent messages and received messages are kept in memory
and the whole message history is submitted every time the magic command is used.
The response from ChatGPT is rendered as Markdown.That sounds really convenient! And what exactly is ChatGPT and how does it generate
responses?%ai "I think you know that best yourself :)"As an AI language model, I don’t know everything about what specific tools or
algorithms you’ve used in the creation of your AI chat user interface. However,
generally speaking, GPT (Generative Pre-trained Transformer) is a type of language
model that uses deep learning to generate human-like text. ChatGPT is a variant of GPT
specifically designed for chatbots and conversational agents, and it has been trained
on vast amounts of existing human conversations to learn how to simulate natural
language interactions. When a user inputs a message, ChatGPT uses this training to
generate an appropriate response based on the context of the conversation.%%ai
Thanks for the summary!
I'm publishing this on GitHub and putting this very discussion as the README.That sounds like a great idea! Having a clear explanation of how the chat interface
works and the technology it uses will help make it more accessible to potential users.
Good luck with your project!
Package: jupyter-ai-chatgpt
jupyter_ai_chatgptThis extension is composed of a Python package namedjupyter_ai_chatgptthat exposes the model engines to the Jupyter AI server extension,
and an NPM package named@jupyter-ai/chatgptthat provides a frontend labextension registering inserters.RequirementsJupyterLab >= 3.0InstallTo install the extension, execute:pipinstalljupyter_ai_chatgptUninstallTo remove the extension, execute:pipuninstalljupyter_ai_chatgptContributingDevelopment installNote: You will need NodeJS to build the extension package.Thejlpmcommand is JupyterLab's pinned version ofyarnthat is installed with JupyterLab. You may useyarnornpmin lieu ofjlpmbelow.# Clone the repo to your local environment# Change directory to the jupyter_ai_chatgpt directory# Install package in development modepipinstall-e".[test]"# 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 uninstallpipuninstalljupyter_ai_chatgptIn 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@jupyter-ai/chatgptwithin that folder.Testing the extensionBackend testsThis AI module is usingPytestfor Python code testing.Install test dependencies (needed only once):pipinstall-e".[test]"# Each time you install the Python package, you need to restore the front-end extension linkjupyterlabextensiondevelop.--overwriteTo execute them, run:pytest-vv-rap--covjupyter_ai_chatgptFrontend 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: jupyter-ai-dalle
jupyter_ai_dalleThis extension is composed of a Python package namedjupyter_ai_dallethat exposes the model engines to the Jupyter AI server extension,
and an NPM package namedjupyter_ai_dallethat provides a frontend labextension registering inserters.RequirementsJupyterLab >= 3.0InstallTo install the extension, execute:pipinstalljupyter_ai_dalleUninstallTo remove the extension, execute:pipuninstalljupyter_ai_dalleContributingDevelopment installNote: You will need NodeJS to build the extension package.Thejlpmcommand is JupyterLab's pinned version ofyarnthat is installed with JupyterLab. You may useyarnornpmin lieu ofjlpmbelow.# Clone the repo to your local environment# Change directory to the jupyter_ai_dalle directory# Install package in development modepipinstall-e".[test]"# 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 uninstallpipuninstalljupyter_ai_dalleIn development mode, you will also need to remove the symlink created byjupyter labextension developcommand. To find its location, you can runjupyter labextension listto figure out where thelabextensionsfolder is located. Then you can remove the symlink namedjupyter_ai_dallewithin that folder.Testing the extensionBackend testsThis AI module is usingPytestfor Python code testing.Install test dependencies (needed only once):pipinstall-e".[test]"# Each time you install the Python package, you need to restore the front-end extension linkjupyterlabextensiondevelop.--overwriteTo execute them, run:pytest-vv-rap--covjupyter_ai_dalleFrontend 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: jupyter-alabaster-theme
# Jupyter Alabaster Theme[![Documentation Status](http://readthedocs.org/projects/jupyter-alabaster-theme/badge/?version=latest)](http://jupyter-alabaster-theme.readthedocs.io/en/latest/?badge=latest)A Sphinx theme for Jupyter based on the [Alabaster theme](https://alabaster.readthedocs.io/en/latest/).To use this theme on any Sphinx based documentation, follow these steps:## InstallationInstall the `jupyter_alabaster_theme` package using pip:```bashpip install jupyter_alabaster_theme```## ConfigurationTo use the theme in your Sphinx based documentation, follow these steps. For furtherdetails, see the documentation for this theme [here](http://jupyter-alabaster-theme.readthedocs.io/en/latest/).### Edit `conf.py`Most of the work to use the theme is in editing your `conf.py` file that configuresSphinx.First, You will need to set the theme itself to `jupyter_alabaster_theme`:```pythonhtml_theme = 'jupyter_alabaster_theme'```Second, you will need to add `jupyter_alabaster_theme` to the list of extensions:```pythonextensions = [...'jupyter_alabaster_theme',]```Finally, at the bottom of `conf.py`, the following block of code, if present, should be removed:```pythonif not on_rtd:# only import and set the theme if we're building docs locallyimport sphinx_rtd_themehtml_theme = 'sphinx_rtd_theme'html_theme_path = [sphinx_rtd_theme.get_html_theme_path()]```### Update documentation dependenciesTo get your documentation to build, you will need to update its build dependencies. Update your `environment.yml` or `requirements.txt` to depend on  `jupyter_alabaster_theme` to get the build working on ReadTheDocs. Note, we have not yet released a [Conda](https://conda.io/docs/intro.html) package for this theme, so you will need to list it in the `environment.yml` file under the `pip` section.## QuestionsIf you have questions about this project, please go to our Gitter channel:https://gitter.im/jupyter/jupyter
Package: jupyter-analysis-extension
Ipywidget Analysis ExtensionAbout The ProjectDependenciesipywidgets(version>=7.0.0, <8.0)qgrid(version>=1.3.1)traitlets(version>=5.0.5)ipykernel(version>=5.5.3)plotly(version>=4.14.3)statsmodels(version>=0.12.2)scipy(version>=1.6.3)seaborn(version>=0.11.1)ipyevents(version~=0.8.2)scikit-learn(version~=0.24.2)setuptools(version~=49.6.0)ipython(veresion~=7.22.0)matplotlibnumpypandasjupyterlabandnotebookGetting Startedapt-getsudo apt-get install wkhtmltopdfpippip install jupyter-analysis-extension

or

git clone https://github.com/KyoungjunPark/ipywidget_statistics.git
==
<Notebook>
pip install -r requirements.txt
jupyter nbextension enable --py --sys-prefix widgetsnbextension
jupyter nbextension enable --py --sys-prefix qgrid

<JupyterLab 3>
TO BE SUPPORTED SOON
# pip install -r requirements_lab.txt
# jupyter labextension install @jupyter-widgets/jupyterlab-manager
# jupyter labextension install @j123npm/qgrid2@1.1.4 (for JupyterLab 3)
==

jupyter notebookCondaTBD.UsageAdd these codes in the first cell of jupter notebook.%load_extautoreload%autoreload2%matplotlibinlineimportipywidgetsaswidgetsfromjupyter_analysis_extension.widget_funcimportWidgetFuncWidgetFunc()ContactKyoungjun Park -kyoungjun_park@tmax.co.kr(https://kyoungjunpark.github.io/)AcknowledgementsImg Shields