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Backport PR #10198: Correctly deprecate limit_to_all...
Backport PR #10198: Correctly deprecate limit_to_all At least emit a warning. Should likely be backported to 5.x.

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kernel_install.rst
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Installing the IPython kernel

The Jupyter Notebook and other frontends automatically ensure that the IPython kernel is available. However, if you want to use a kernel with a different version of Python, or in a virtualenv or conda environment, you'll need to install that manually.

Kernels for Python 2 and 3

If you're running Jupyter on Python 3, you can set up a Python 2 kernel like this:

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

Or using conda, create a Python 2 environment:

conda create -n ipykernel_py2 python=2 ipykernel
source activate ipykernel_py2    # On Windows, remove the word 'source'
python -m ipykernel install --user

If you're running Jupyter on Python 2 and want to set up a Python 3 kernel, follow the same steps, replacing 2 with 3.

The last command installs a :ref:`kernel spec <jupyterclient:kernelspecs>` file for the current python installation. Kernel spec files are JSON files, which can be viewed and changed with a normal text editor.

Kernels for different environments

If you want to have multiple IPython kernels for different virtualenvs or conda environments, you will need to specify unique names for the kernelspecs.

For example, using conda environments:

source activate myenv
python -m ipykernel install --user --name myenv --display-name "Python (myenv)"
source activate other-env
python -m ipykernel install --user --name other-env --display-name "Python (other-env)"

The --name value is used by Jupyter internally. These commands will overwrite any existing kernel with the same name. --display-name is what you see in the notebook menus.