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python3-gunicorn-23.0.0-1.lbn36.noarch

Gunicorn Gunicorn ‘Green Unicorn’ is a Python WSGI HTTP Server for UNIX. It’s a pre-fork worker model ported from Ruby’s Unicorn project. The Gunicorn server is broadly compatible with various web frameworks, simply implemented, light on server resource usage, and fairly speedy. Feel free to join us in #gunicorn on Libera.chat. Documentation The documentation is hosted at https:/docs.gunicorn.org. Installation Gunicorn requires Python 3.x >= 3.7. Install from PyPI: $ pip install gunicorn Usage Basic usage: $ gunicorn [OPTIONS] APP_MODULE Where APP_MODULE is of the pattern $(MODULE_NAME):$(VARIABLE_NAME). The module name can be a full dotted path. The variable name refers to a WSGI callable that should be found in the specified module. Example with test app: $ cd examples $ gunicorn --workers=2 test:app Contributing See our complete contributor’s guide for more details. License Gunicorn is released under the MIT License. See the LICENSE file for more details.

python3-jupyter-client-8.4.0-1.lbn36.noarch

Jupyter Client jupyter_client contains the reference implementation of the Jupyter protocol. It also provides client and kernel management APIs for working with kernels. It also provides the jupyter kernelspec entrypoint for installing kernelspecs for use with Jupyter frontends. Development Setup The Jupyter Contributor Guides provide extensive information on contributing code or documentation to Jupyter projects. The limited instructions below for setting up a development environment are for your convenience. Coding You'll need Python and pip on the search path. Clone the Jupyter Client git repository to your computer, for example in /my/project/jupyter_client cd /my/projects/ git clone git@github.com:jupyter/jupyter_client.git Now create an editable install and download the dependencies of code and test suite by executing: cd /my/projects/jupyter_client/ pip install -e ".[test]" pytest The last command runs the test suite to verify the setup. During development, you can pass file

python3-jupyter-client-8.4.0-1.lbn36.noarch

Jupyter Client jupyter_client contains the reference implementation of the Jupyter protocol. It also provides client and kernel management APIs for working with kernels. It also provides the jupyter kernelspec entrypoint for installing kernelspecs for use with Jupyter frontends. Development Setup The Jupyter Contributor Guides provide extensive information on contributing code or documentation to Jupyter projects. The limited instructions below for setting up a development environment are for your convenience. Coding You'll need Python and pip on the search path. Clone the Jupyter Client git repository to your computer, for example in /my/project/jupyter_client cd /my/projects/ git clone git@github.com:jupyter/jupyter_client.git Now create an editable install and download the dependencies of code and test suite by executing: cd /my/projects/jupyter_client/ pip install -e ".[test]" pytest The last command runs the test suite to verify the setup. During development, you can pass file

python3-jupyter-console-6.6.3-1.lbn36.noarch

Jupyter Console A terminal-based console frontend for Jupyter kernels. This code is based on the single-process IPython terminal. Install with pip: pip install jupyter-console Install with conda: conda install -c conda-forge jupyter_console Start: jupyter console Help: jupyter console -h Jupyter Console allows for console-based interaction with non-python Jupyter kernels such as IJulia, IRKernel. To start the console with a particular kernel, ask for it by name:: jupyter console --kernel=julia-0.4 A list of available kernels can be seen with:: jupyter kernelspec list Release build: $ pip install pep517 $ python -m pep517.build . Resources Project Jupyter website Documentation for Jupyter Console [PDF] Documentation for Project Jupyter [PDF] Issues Technical support - Jupyter Google Group 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 coordi

python3-jupyter-console-6.6.3-1.lbn36.noarch

Jupyter Console A terminal-based console frontend for Jupyter kernels. This code is based on the single-process IPython terminal. Install with pip: pip install jupyter-console Install with conda: conda install -c conda-forge jupyter_console Start: jupyter console Help: jupyter console -h Jupyter Console allows for console-based interaction with non-python Jupyter kernels such as IJulia, IRKernel. To start the console with a particular kernel, ask for it by name:: jupyter console --kernel=julia-0.4 A list of available kernels can be seen with:: jupyter kernelspec list Release build: $ pip install pep517 $ python -m pep517.build . Resources Project Jupyter website Documentation for Jupyter Console [PDF] Documentation for Project Jupyter [PDF] Issues Technical support - Jupyter Google Group 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 coordi

python3-jupyter-core-5.7.2-1.lbn36.noarch

There is no reason to install this package on its own.

python3-jupyter-core-5.7.2-1.lbn36.noarch

There is no reason to install this package on its own.

python3-jupyter-kernel-singular-0.9.9-8.fc36.noarch

This package contains a Jupyter kernel for Singular, to enable using Jupyter as the front end for Singular.

python3-jupyter-kernel-test-0.6.0-1.lbn36.noarch

jupyter_kernel_test is a tool for testing Jupyter kernels. It tests kernels for successful code execution and conformance with the Jupyter Messaging Protocol (currently 5.0). Install Install it with pip (python3.4 or greater required): pip3 install jupyter_kernel_test Usage To use it, you need to write a (python) unittest file containing code samples in the relevant language which test various parts of the messaging protocol. A short example is given below, and you can also refer to the test_ipykernel.py and test_irkernel.py files for complete examples. Some parts of the messaging protocol are relevant only to the browser-based notebook (rich display) or console interfaces (code completeness, history searching). Only parts of the spec for which you provide code samples are tested. Run this file directly using python, or use nosetests or py.test to find and run it. Example import unittest import jupyter_kernel_test class MyKernelTests(jupyter_kernel_test.KernelTests):

python3-jupyter-kernel-test-0.6.0-1.lbn36.noarch

jupyter_kernel_test is a tool for testing Jupyter kernels. It tests kernels for successful code execution and conformance with the Jupyter Messaging Protocol (currently 5.0). Install Install it with pip (python3.4 or greater required): pip3 install jupyter_kernel_test Usage To use it, you need to write a (python) unittest file containing code samples in the relevant language which test various parts of the messaging protocol. A short example is given below, and you can also refer to the test_ipykernel.py and test_irkernel.py files for complete examples. Some parts of the messaging protocol are relevant only to the browser-based notebook (rich display) or console interfaces (code completeness, history searching). Only parts of the spec for which you provide code samples are tested. Run this file directly using python, or use nosetests or py.test to find and run it. Example import unittest import jupyter_kernel_test class MyKernelTests(jupyter_kernel_test.KernelTests):