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jupyter_cki

Jupyter Custom Kernel Installer

English

This software can install Python and R kernels in Jupyter (notebook, lab or hub).

This software, that uses the ipykernel utility for Python kernels and r-irkernel for R kernels, installs a new kernel for Jupyter. With this you can have multiple kernels (hand-managed or by software like Conda) with distinct libraries or packages, not merging the environments.

Requirements:

  • Python 2 or 3.
  • Environment with package ipykernel or r-irkernel installed.

Example:

We have a Conda installation on /opt/conda with three environments:

  • jupyterhub
  • python35
  • python36
  • ir
/opt/conda/envs
|-- python35/
|-- python36/
|-- ir/
`-- jupyterhub/

[root@vm /root/jupyter_cki] python jupyter_cki.py python --jupyter /opt/conda/envs/jupyterhub --kernel /opt/conda/envs/python36 --kernel_name python36
Installed kernelspec python36 in /opt/conda/envs/tools/share/jupyter/kernels/python36
Kernel installed

[root@vm /root/jupyter_cki] python jupyter_cki.py python --jupyter /opt/conda/envs/jupyterhub --kernel /opt/conda/envs/python35 --kernel_name python35
Installed kernelspec python35 in /opt/conda/envs/tools/share/jupyter/kernels/python35
Kernel installed

[root@vm /root/jupyter_cki] python jupyter_cki.py ir --jupyter /opt/conda/envs/jupyterhub --kernel /opt/conda/envs/ir
Kernel installed

You can check if it's working correctly: first open Jupyter, select a custom kernel and execute this to check the Python version running.

import sys
print(sys.version)

Bug report:

If you have found a bug, please let me know with the Issues tool from GitHub.

License:

This software is distributed under GNU GPL v3. You can read the terms here.

Español

Este software permite instalar más kernels de Python o R en Jupyter (notebook, lab o hub).

Este software, que usa la utilidad ipykernel para núcleos Python y r-irkernel para núcleos R, instala un nuevo kernel para Jupyter. Con esto puede tener múltiples núcleos (administrados manualmente o por software como Conda) con distintas bibliotecas o paquetes, sin fusionar los entornos.

Requisitos:

  • Python 2 o 3.
  • Entorno con paquete ipykernel o r-irkernel instalado.

Ejemplo:

Tenemos una instalación de Conda en /opt/conda con tres entornos:

  • jupyterhub
  • python35
  • python36
  • ir
/opt/conda/envs
|-- python35/
|-- python36/
|-- ir/
`-- jupyterhub/

[root@vm /root/jupyter_cki] python jupyter_cki.py python --jupyter /opt/conda/envs/jupyterhub --kernel /opt/conda/envs/python36 --kernel_name python36
Installed kernelspec python36 in /opt/conda/envs/tools/share/jupyter/kernels/python36
Kernel installed

[root@vm /root/jupyter_cki] python jupyter_cki.py python --jupyter /opt/conda/envs/jupyterhub --kernel /opt/conda/envs/python35 --kernel_name python35
Installed kernelspec python35 in /opt/conda/envs/tools/share/jupyter/kernels/python35
Kernel installed

[root@vm /root/jupyter_cki] python jupyter_cki.py ir --jupyter /opt/conda/envs/jupyterhub --kernel /opt/conda/envs/ir
Kernel installed

Puedes verificar si está funcionando correctamente: primero abre Jupyter, selecciona un kernel personalizado y ejecuta esto para verificar la versión de Python que se está ejecutando.

import sys
print(sys.version)

Reporte de errores:

Si has encontrado un error, házmelo saber con la herramienta de errores de GitHub.

Licencia:

Este software se distribuye bajo GNU GPL v3. Puedes leer los términos aquí.