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python3-jupyter-server-terminals-proxy-0.1.4-1.lbn36.noarch: Jupyter Server Terminals Proxy In one terminal/environment: pip install fps_uvicorn pip install fps_terminals pip install fps-noauth fps-uvicorn --port=8000 --no-open-browser In another terminal/environment: pip install jupyter_server_terminals_proxy pip install jupyterlab jupyter lab --port=8888 --ServerApp.terminals_enabled=False --TerminalsProxyExtensionApp.proxy_url='http:/127.0.0.1:8000' Terminals should now be served from http:/127.0.0.1:8000.

python3-jupyter-server-terminals-0.4.4-1.lbn36.noarch: Jupyter Server Terminals Jupyter Server Terminals is a Jupyter Server Extension providing support for terminals. Installation and Basic usage To install the latest release locally, make sure you have pip installed and run: pip install jupyter_server_terminals Jupyter Server Terminals currently supports Python>=3.6 on Linux, OSX and Windows. Testing See CONTRIBUTING. Contributing If you are interested in contributing to the project, see CONTRIBUTING.

python3-jupyter-server-proxy-noe-1.1-1.lbn36.noarch

python3-jupyter-server-proxy-4.1.0-1.lbn36.noarch: Jupyter Server Proxy Jupyter Server Proxy lets you run arbitrary external processes (such as RStudio, Shiny Server, Syncthing, PostgreSQL, Code Server, etc) alongside your notebook server and provide authenticated web access to them using a path like /rstudio next to others like /lab. Alongside the python package that provides the main functionality, the JupyterLab extension (@jupyterhub/jupyter-server-proxy) provides buttons in the JupyterLab launcher window to get to RStudio for example. Note: This project used to be called nbserverproxy. As nbserverproxy is an older version of jupyter-server-proxy, uninstall nbserverproxy before installing jupyter-server-proxy to avoid conflicts. The primary use cases are: Use with JupyterHub / Binder to allow launching users into web interfaces that have nothing to do with Jupyter - such as RStudio, Shiny, or OpenRefine. Allow access from frontend javascript (in classic notebook or JupyterLab extensions) to access web APIs of other processes

python3-jupyter-server-mathjax-0.2.6-1.lbn36.noarch: MathJax resources endpoints for Jupyter Server Basic Usage Install from PyPI: > pip install jupyter_server_mathjax This will automatically enable the extension in Jupyter Server. To test the installation, you can run Jupyter Server and visit the /static/jupyter_server_mathjax/MathJax.js endpoint: > jupyter server Maintenance Notes To install an editable install locally for development, first clone the repository locally, then run: `pip install -e .[test]` Note that the editable install will not install the data file that automatically configures the extension for use. To manually enable it, run: jupyter server extension enable --py jupyter_server_mathjax To build for distribution, use the build package: pip install build python -m build Then release using twine: twine check dist/* twine check dist/*

python3-jupyter-server-kernels-proxy-0.1.0-1.lbn36.noarch: Jupyter Server Kernels Proxy

python3-jupyter-server-kernels-0.1.2-1.lbn36.noarch: Jupyter Server Kernels Jupyter Server Kernels is a Jupyter Server Extension providing support for kernels.

python3-jupyter-server-fileid-0.9.0-1.lbn36.noarch: jupyter_server_fileid A Jupyter Server extension providing an implementation of the File ID service. Requirements Jupyter Server Install To install the extension, execute: pip install jupyter_server_fileid Uninstall To remove the extension, execute: pip uninstall jupyter_server_fileid Troubleshoot If you are seeing the frontend extension, but it is not working, check that the server extension is enabled: jupyter server extension list Contributing Development install pip install -e . You can watch the source directory and run your Jupyter Server-based application at the same time in different terminals to watch for changes in the extension's source and automatically rebuild the extension. For example, when running JupyterLab: jupyter lab --autoreload If your extension does not depend a part

python3-jupyter-server-2.14.1-1.lbn36.noarch: Jupyter Server The Jupyter Server provides the backend (i.e. the core services, APIs, and REST endpoints) for Jupyter web applications like Jupyter notebook, JupyterLab, and Voila. For more information, read our documentation here. Installation and Basic usage To install the latest release locally, make sure you have pip installed and run: pip install jupyter_server Jupyter Server currently supports Python>=3.6 on Linux, OSX and Windows. Versioning and Branches If Jupyter Server is a dependency of your project/application, it is important that you pin it to a version that works for your application. Currently, Jupyter Server only has minor and patch versions. Different minor versions likely include API-changes while patch versions do not change API. When a new minor version is released on PyPI, a branch for that version will be created in this repository, and the version of the main branch will be bumped to the next minor version number. That way, the main branch always reflects the

python3-jupyter-lsp-2.2.0-1.lbn36.noarch: jupyter-lspMulti-[Language Server][language-server] WebSocket proxy for your Jupyter notebook or lab server. For Python 3.6+.> See the parent of this repository, > [jupyterlab-lsp]( for the > reference client implementation for [JupyterLab][]. Language Serversjupyter-lsp does not come with any Language Servers! Learn more about installing and configuring [language servers][language servers...

python3-jupyter-jaeger-1.0.4-1.lbn36.noarch: This adds support for using the Jaeger distributed tracing tool with Jupyter. It facilitates the use case of tracking some process that starts in a kernel and is continued in a mime renderer. We are using it to profile and debug ibis-vega-transform which goes back and forth between the kernel and the frontend to interactively render charts with Altair. Installing this adds two Jupyter server extensions that start up the jaeger-all-in-one and jaeger-browser processes when you launch Jupyter. So to use it you must first instrument code in your kernel and/or in the frontend to record traces. It also provis a NPM Typescript plugin you can use to access the client from inside a JupyterLab extension.

python3-jupyter-events-0.10.0-1.lbn36.noarch: Jupyter Events An event system for Jupyter Applications and extensions. Jupyter Events enables Jupyter Python Applications (e.g. Jupyter Server, JupyterLab Server, JupyterHub, etc.) to emit events—structured data describing things happening inside the application. Other software (e.g. client applications like JupyterLab) can listen and respond to these events. Install Install Jupyter Events directly from PyPI: pip install jupyter_events or conda-forge: conda install -c conda-forge jupyter_events Documentation Documentation is available at jupyter-events.readthedocs.io. About the Jupyter Development Team The Jupyter Development Team is the set of all contributors to the Jupyter project. This includes all of the Jupyter subprojects. The core team that coordinates development on GitHub can be found here: https:/github.com/jupyter/. Our Copyright Policy Jupyter uses a shared copyright model. Each contributor maintains copyright over their contributions to Jupyter. But, it is important

python3-jupyter-cache-0.5.0-1.lbn36.noarch: jupyter-cache[![Github-CI][github-ci]][github-link] [![Coverage Status][codecov-badge]][codecov-link] [![Documentation Status][rtd-badge]][rtd- link] [![Code style: black][black-badge]][black-link] [![PyPI][pypi- badge]][pypi-link]A defined interface for working with a cache of jupyter notebooks. Why use jupyter-cache?If you have a number of notebooks whose execution outputs you want to...

python3-jupyter-c-kernel-1.2.2-14.fc36.noarch: Minimalistic C kernel for Jupyter

python3-microsoft-security-utilities-secret-masker-1.0.0~b3-1.lbn36.noarch: Microsoft Security Utilities - Secret Masker microsoft-security-utilities-secret-masker is part of the Microsoft Security Utilities used internally. You can find the related .NET SDK package here. This Secret Masker Python library focuses on: providing some built-in detection rules in json format detecting sensitive data for given input masking sensitive data with simple symbols or sha256 hash for given input Installation You can install the package via pip: pip install microsoft-security-utilities-secret-masker Usage You can use the SecretMasker class to detect and mask sensitive data in your input. Here is an example: from microsoft_security_utilities_secret_masker import SecretMasker, load_regex_patterns_from_json_file precisely_classified_regex_patterns = load_regex_patterns_from_json_file('PreciselyClassifiedSecurityKeys.json') unclassified_regex_patterns = load_regex_patterns_from_json_file('UnclassifiedPotentialSecurityKeys.json')

python3-microsoft-kiota-serialization-text-1.9.6-1.lbn36.noarch: Microsoft Kiota Text Serialization library The Microsoft Kiota Text Serialization Library is a python implementation to serialize/deserialize text/plain. A Kiota generated project will need a reference to a json serialization package to handle json payloads from an API endpoint. Read more about Kiota here. Using the Microsoft Kiota Text Serialization library In order to use this library, install the package by running: pip install microsoft-kiota-serialization-text Contributing This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https:/cla.opensource.microsoft.com. When you submit a pull request, a CLA bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., status check, comment). Simply follow the instructions provided by the bot.

python3-microsoft-kiota-serialization-json-1.9.6-1.lbn36.noarch: Microsoft Kiota Serialization library for JSON The Microsoft Kiota Serialization Library for JSON is a python implementation to serialize/deserialize JSON. A Kiota generated project will need a reference to a json serialization package to handle json payloads from an API endpoint. Read more about Kiota here. Using the Microsoft Kiota Serialization JSON library In order to use this library, install the package by running: pip install microsoft-kiota-serialization-json Contributing This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https:/cla.opensource.microsoft.com. When you submit a pull request, a CLA bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., status check, comment). Simply follow the instructions provided by the bot

python3-microsoft-kiota-http-1.9.6-1.lbn36.noarch: Microsoft Kiota HTTP library The Microsoft Kiota HTTP Library is a python HTTP implementation with HTTPX library. A Kiota generated project will need a reference to a http package to to make HTTP requests to an API endpoint. Read more about Kiota here. Using the Microsoft Kiota HTTP library In order to use this library, install the package by running: pip install microsoft-kiota-http Contributing This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https:/cla.opensource.microsoft.com. When you submit a pull request, a CLA bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., status check, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA. This project ha

python3-microsoft-kiota-authentication-azure-1.9.6-1.lbn36.noarch: Microsoft Kiota Authentication Azure Library for Python The Microsoft Kiota Authentication Azure Library is an implementation to authenticate HTTP requests using @azure/identity. A Kiota generated project will need a reference to an authentication provider to make calls to an API endpoint. Read more about Kiota here. Using the Microsoft Kiota Authentication Azure library In order to use this library, install the package by running: pip install microsoft-kiota-authentication-azure Contributing This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https:/cla.opensource.microsoft.com. When you submit a pull request, a CLA bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., status check, comment). Simply follow the instructions provi

python3-microsoft-kiota-abstractions-1.9.6-1.lbn36.noarch: Microsoft Kiota Abstractions Library for Python The Microsoft Kiota abstractions library for Python is the python package defining the basic constructs Kiota projects need once an SDK has been generated from an OpenAPI definition. A Kiota generated project will need a reference to the abstraction package to build and run. Read more about Kiota here. Using the Abstractions Library In order to use this library, install the package by running: pip install microsoft-kiota-abstractions Contributing This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https:/cla.opensource.microsoft.com. When you submit a pull request, a CLA bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., status check, comment). Simply follow the instructions prov

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