-
python3-jupyter-client-5.3.1-1.lbn25.noarch
This package 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.
Located in
LBN
/
…
/
Big Data
/
BastionLinux 25
-
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
Located in
LBN
/
…
/
Big Data
/
BastionLinux 36
-
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
Located in
LBN
/
…
/
Core Linux
/
BastionLinux 36
-
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
Located in
LBN
/
…
/
Data Science
/
BastionLinux 36
-
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
Located in
LBN
/
…
/
Data Science
/
BastionLinux 36
-
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
Located in
LBN
/
…
/
Big Data
/
BastionLinux 36
-
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
Located in
LBN
/
…
/
Core Linux
/
BastionLinux 36
-
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
Located in
LBN
/
…
/
Data Science
/
BastionLinux 36
-
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
Located in
LBN
/
…
/
Data Science
/
BastionLinux 36
-
python3-jupyter-core-4.1.1-2.lbn19.noarch
Core common functionality of Jupyter projects.
This package contains base application classes and configuration inherited by
other projects.
Located in
LBN
/
…
/
Big Data
/
BastionLinux 19