How do I add python3 kernel to jupyter (IPython)

This worked for me on Ubuntu 16.04:

python2 -m pip install ipykernel
python2 -m ipykernel install --user

python3 -m pip install ipykernel
python3 -m ipykernel install --user

Reference to the documentation:
Kernels for Python 2 and 3. Installing the IPython kernel - IPython Docs.

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Make sure you have ipykernel installed and use ipython kernel install to drop the kernelspec in the right location for python2. Then ipython3 kernel install for Python3. Now you should be able to chose between the 2 kernels regardless of whether you use jupyter notebook, ipython notebook or ipython3 notebook (the later two are deprecated).

Note that if you want to install for a specific Python executable you can use the following trick:

path/to/python -m ipykernel install <options>

This works when using environments (venv,conda,...) and the <options> let you name your kernel (see --help). So you can do

conda create -n py36-test python=3.6
source activate py36-test
python -m ipykernel install --name py36-test
source deactivate

And now you get a kernel named py36-test in your dropdown menus, along the other ones.

See Using both Python 2.x and Python 3.x in IPython Notebook which has more recent information.

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Got ipython notebook with Python2 (on Windows7) upgrade to Jupyter with pip install -U jupyter install Python3 install Jupyter again using pip3 install jupyter install Python3 kernel using ipython3 kernelspec install-self I finally got 2 working kernels.

https://i.stack.imgur.com/TF5uW.png

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for recent versions of jupyter/ipython: use jupyter kernelspec

Full doc: https://ipython.readthedocs.io/en/latest/install/kernel_install.html

list current kernels

$ jupyter kernelspec list
Available kernels:
  python2    .../Jupyter/kernels/python2
  python3    .../Jupyter/kernels/python3

In my case, the python3 kernel setup was broken because the py3.5 linked was no longer there, replaced by a py3.6

add/remove kernels

Remove:

$ jupyter kernelspec uninstall python3

Add a new one: Using the Python you wish to add and pointing to the python which runs your jupiter:

$ /path/to/kernel/env/bin/python -m ipykernel install --prefix=/path/to/jupyter/env --name 'python-my-env'

See more examples in https://ipython.readthedocs.io/en/6.5.0/install/kernel_install.html#kernels-for-different-environments

List again:

$ jupyter kernelspec list
Available kernels:
  python3    /usr/local/lib/python3.6/site-packages/ipykernel/resources
  python2    /Users/stefano/Library/Jupyter/kernels/python2

Doc: https://jupyter-client.readthedocs.io/en/latest/kernels.html#kernelspecs

Details

Kernels available are listed under the kernels folder in Jupyter DATA DIRECTORY (see http://jupyter.readthedocs.io/en/latest/projects/jupyter-directories.html for details).

For instance on macosx that would be /Users/YOURUSERNAME/Library/Jupyter/kernels/

the kernel is simply described by a kernel.json file, eg. for /Users/me/Library/Jupyter/kernels/python3/kernel.json

{
 "argv": [
  "/usr/local/opt/python3/bin/python3.5",
  "-m",
  "ipykernel",
  "-f",
  "{connection_file}"
 ],
 "language": "python",
 "display_name": "Python 3"
}

Rather then manipulating that by hand, you can use the kernelspec command (as above). It was previously available through ipython now through jupyter (http://ipython.readthedocs.io/en/stable/install/kernel_install.html#kernels-for-different-environments - https://jupyter-client.readthedocs.io/en/latest/kernels.html#kernelspecs).

$ jupyter kernelspec help
Manage Jupyter kernel specifications.

Subcommands
-----------

Subcommands are launched as `jupyter kernelspec cmd [args]`. For information on
using subcommand 'cmd', do: `jupyter kernelspec cmd -h`.

list
    List installed kernel specifications.
install
    Install a kernel specification directory.
uninstall
    Alias for remove
remove
    Remove one or more Jupyter kernelspecs by name.
install-self
    [DEPRECATED] Install the IPython kernel spec directory for this Python.

To see all available configurables, use `--help-all`

Kernels for other languages

By the way, not strictly related to this question but there's a lot of other kernels available... https://github.com/jupyter/jupyter/wiki/Jupyter-kernels

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If you are using the anaconda distribution, this worked for me (on a macintosh):

$ conda create -n py3k python=3 anaconda

$ source activate py3k

$ ipython kernelspec install-self

Just a note for the last command:

(py3k)Monas-MacBook-Pro:cs799 mona$ ipython kernelspec install-self
[TerminalIPythonApp] WARNING | Subcommand `ipython kernelspec` is deprecated and will be removed in future versions.
[TerminalIPythonApp] WARNING | You likely want to use `jupyter kernelspec` in the future
[InstallNativeKernelSpec] WARNING | `jupyter kernelspec install-self` is DEPRECATED as of 4.0. You probably want `ipython kernel install` to install the IPython kernelspec.
[InstallNativeKernelSpec] Installed kernelspec python3 in /usr/local/share/jupyter/kernels/python3
(py3k)Monas-MacBook-Pro:cs799 mona$ ipython kernel install 
Installed kernelspec python3 in /usr/local/share/jupyter/kernels/python3

https://i.stack.imgur.com/wnXuH.png

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Following command works for me, on macOS Sierra(10.12.3)

python3 -m pip install ipykernel
python3 -m ipykernel install --user

check it with jupyter kernelspec list Available kernels: python3 /Users/admin/Library/Jupyter/kernels/python3 python2 /anaconda2/share/jupyter/kernels/python2

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I successfully installed python3 kernel on macOS El Capitan (ipython version: 4.1.0) with following commands.

python3 -m pip install ipykernel
python3 -m ipykernel install --user

You can see all installed kernels with jupyter kernelspec list.

More info is available here

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open terminal(or cmd for window), then run following commands: (On window, drop "source" in the second line.)

conda create -n py35 python=3.5
source activate py35
conda install notebook ipykernel
ipython kernel install --user --name=python3.5

I tried some method but It doesnt work, then I found this way. It worked with me. Hoping it can help.

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I had Python 2.7 and wanted to be able to switch to Python 3 inside of Jupyter.

These steps worked for me on a Windows Anaconda Command Prompt:

conda update conda
conda create -n py33 python=3.3 anaconda
activate py33
ipython kernelspec install-self
deactivate

Now after opening ipython notebook with the usual command for Python2.7, Python3.3 is also available when creating a new notebook.

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Shortest and best solution from my side

conda create --name py3-ml python=3.6
conda install ipykernel

source activate py3-ml # or conda activate py3-ml
python -m ipykernel install --user --name py3-ml

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sudo apt-get install python3-pip python3-dev
pip3 install -U jupyter

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For the current Python Launcher

If you have Py3 installed but default to py2

py -3 -m pip install ipykernel
py -3 -m ipykernel install --user

If you have Py2 installed but default to py3

py -2 -m pip install ipykernel
py -2 -m ipykernel install --user

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On Ubuntu 14.04 I had to use a combination of previous answers.

First, install pip3 apt-get install python-pip3

Then with pip3 install jupyter pip3 install jupyter

Then using ipython3 install the kernel ipython3 kernel install

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None of the other answers were working for me immediately on ElementaryOS Freya (based on Ubuntu 14.04); I was getting the

[TerminalIPythonApp] WARNING | File not found: 'kernelspec'

error that quickbug described under Matt's answer. I had to first do:

sudo apt-get install pip3, then

sudo pip3 install ipython[all]

At that point you can then run the commands that Matt suggested; namely: ipython kernelspec install-self and ipython3 kernelspec install-self

Now when I launch ipython notebook and then open a notebook, I am able to select the Python 3 kernel from the Kernel menu.

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I managed to install a Python3 kernel besides the Python2. Here is the way I did it:

open a new notebook in Jupyter

copy and run the two cells here: Enable-Python-3-kernel

The latest working link can be found here.

The actual code is:

! mkdir -p ~/.ipython/kernels/python3
%%file ~/.ipython/kernels/python3/kernel.json

{
 "display_name": "IPython (Python 3)", 
 "language": "python", 
 "argv": [
  "python3", 
  "-c", "from IPython.kernel.zmq.kernelapp import main; main()", 
  "-f", "{connection_file}"
 ], 
 "codemirror_mode": {
  "version": 2, 
  "name": "ipython"
 }
}

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Adding kernel means you want to use Jupyter Notebook with versions of python which are not showing up in the list.

Simple approach- Start notebook with required python version, suppose I have python3.7 installed then use below command from terminal (cmd) to run notebook:

python3.7 -m notebook

Sometimes instead of python3.7 it's install with alias of py, py3.7, python.

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The solution is well documented in the official docs: https://ipython.readthedocs.org/en/latest/install/kernel_install.html

I tried the first approach. Since I already had ipykernel installed, simply running python3 -m ipykernel install --user solved the problem.

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I was facing the same issue. Whenever I would start jupyter notebook using the following command, I would not see an option to create a new Python 3 Notebook.

I solved the issue by the running the following command.

pip install notebook

After that I started notebook with the same command as before

jupyter notebook

I was able to see the my home directory and create new python3 notebooks.

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To add specific python into the jupyter kernel, first check the paths of the available python or python3 using the following command

$ where python3

Let's say you have '/usr/local/bin/python3' as one of the paths. To create a kernel for this version of python with name 'name_to_new_kernel' which will showup in jupyter,

$ /usr/local/bin/python3 -m pip install ipykernel
$ /usr/local/bin/python3 -m ipykernel install --user --name name_to_new_kernel

To check if the new kernel with name 'name_to_new_kernel' added to jupyter run the following command

jupyter kernelspec list

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This answer explains how to create a Python 3, Jupyter 1, and ipykernel 5 workflow with Poetry dependency management. Poetry makes creating a virtual environment for Jupyter notebooks easy. I strongly recommend against running python3 commands. Python workflows that install global dependencies set you up for dependency hell.

Here's a summary of the clean, reliable Poetry workflow:

Install the dependencies with poetry add pandas jupyter ipykernel

Open a shell within the virtual environment with poetry shell

Open the Jupyter notebook with access to all the virtual environment dependencies with jupyter notebook

There are clean Conda workflows as well. Watch out for a lot of the answers in this thread - they'll set you down a path that'll cause a lot of pain & suffering.

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INSTALLING MULTIPLE KERNELS TO A SINGLE VIRTUAL ENVIRONMENT (VENV)

Most (if not all) of these answers assume you are happy to install packages globally. This answer is for you if you:

use a *NIX machine

don't like installing packages globally

don't want to use anaconda <-> you're happy to run the jupyter server from the command line

want to have a sense of what/where the kernel installation 'is'.

(Note: this answer adds a python2 kernel to a python3-jupyter install, but it's conceptually easy to swap things around.)

Prerequisites You're in the dir from which you'll run the jupyter server and save files python2 is installed on your machine python3 is installed on your machine virtualenv is installed on your machine Create a python3 venv and install jupyter Create a fresh python3 venv: python3 -m venv .venv Activate the venv: . .venv/bin/activate Install jupyterlab: pip install jupyterlab. This will create locally all the essential infrastructure for running notebooks. Note: by installing jupyterlab here, you also generate default 'kernel specs' (see below) in $PWD/.venv/share/jupyter/kernels/python3/. If you want to install and run jupyter elsewhere, and only use this venv for organizing all your kernels, then you only need: pip install ipykernel You can now run jupyter lab with jupyter lab (and go to your browser to the url displayed in the console). So far, you'll only see one kernel option called 'Python 3'. (This name is determined by the display_name entry in your kernel.json file.) Add a python2 kernel Quit jupyter (or start another shell in the same dir): ctrl-c Deactivate your python3 venv: deactivate Create a new venv in the same dir for python2: virtualenv -p python2 .venv2 Activate your python2 venv: . .venv2/bin/activate Install the ipykernel module: pip install ipykernel. This will also generate default kernel specs for this python2 venv in .venv2/share/jupyter/kernels/python2 Export these kernel specs to your python3 venv: python -m ipykernel install --prefix=$PWD/.venv. This basically just copies the dir $PWD/.venv2/share/jupyter/kernels/python2 to $PWD/.venv/share/jupyter/kernels/ Switch back to your python3 venv and/or rerun/re-examine your jupyter server: deactivate; . .venv/bin/activate; jupyter lab. If all went well, you'll see a Python 2 option in your list of kernels. You can test that they're running real python2/python3 interpreters by their handling of a simple print 'Hellow world' vs print('Hellow world') command. Note: you don't need to create a separate venv for python2 if you're happy to install ipykernel and reference the python2-kernel specs from a global space, but I prefer having all of my dependencies in one local dir

TL;DR

Optionally install an R kernel. This is instructive to develop a sense of what a kernel 'is'. From the same dir, install the R IRkernel package: R -e "install.packages('IRkernel',repos='https://cran.mtu.edu/')". (This will install to your standard R-packages location; for home-brewed-installed R on a Mac, this will look like /usr/local/Cellar/r/3.5.2_2/lib/R/library/IRkernel.) The IRkernel package comes with a function to export its kernel specs, so run: R -e "IRkernel::installspec(prefix=paste(getwd(),'/.venv',sep=''))". If you now look in $PWD/.venv/share/jupyter/kernels/ you'll find an ir directory with kernel.json file that looks something like this:

{
  "argv": ["/usr/local/Cellar/r/3.5.2_2/lib/R/bin/R", "--slave", "-e", "IRkernel::main()", "--args", "{connection_file}"],
  "display_name": "R",
  "language": "R"
}

In summary, a kernel just 'is' an invocation of a language-specific executable from a kernel.json file that jupyter looks for in the .../share/jupyter/kernels dir and lists in its interface; in this case, R is being called to run the function IRkernel::main(), which will send messages back and forth to the Jupiter server. Likewise, the python2 kernel just 'is' an invocation of the python2 interpreter with module ipykernel_launcher as seen in .venv/share/jupyter/kernels/python2/kernel.json, etc.

Here is a script if you want to run all of these instructions in one fell swoop.

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Here's a Windows/non command line method I found, which worked for me: Find the folder where the kernel files are stored (on my machine - C:\ProgramData\jupyter\kernels - note that ProgramData is a hidden folder), create a copy of the existing kernel's folder, change the name and edit the json file within to point to the new kernel's directory. In this json you can also edit the kernel name that is displayed in ipython (e.g. instead of just python 2 you can specify 2.7.9 if you need to further distinguish for some reason).

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When you use conda managing your python envs, follow these two steps:

activate py3 (on Windows or source activate py3 on Linux) conda install notebook ipykernel or just use conda install jupyter

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I was getting same error with python-2. I wanted to run python-2 jupyter notebook session but by default I was getting python-3. So easiest work around is open Anaconda terminal for python-2 and type 'jupyter notebook' , it will launch jupyter-notebook session without any problem. Similary it could be tried with python-3

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I am pretty sure all you have to do is run

pip3 install jupyter

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