Merge pull request #10923 from takluyver/doc-kernel-install-code-blk

Fix rst for code block

docs/source/install/kernel_install.rst

@@ -1,106 +1,106 b''
 .. _kernel_install:
 
 Installing the IPython kernel
 =============================
 
 .. seealso::
 
    :ref:`Installing Jupyter <jupyter:install>`
      The IPython kernel is the Python execution backend for Jupyter.
 
 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 after
 checking your version of pip is greater than 9.0::
 
     python2 -m pip --version
 
 Then install with ::
 
     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
 
 .. note::
 
     IPython 6.0 stopped support for Python 2, so
     installing IPython on Python 2 will give you an older version (5.x series).
 
 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.
 
 .. _multiple_kernel_install:
 
 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.
 
 Make sure you have ipykernel installed in your environement. If you are using
 ``pip`` to install ``ipykernel`` in a conda env, make sure ``pip`` is
-installed::
+installed:
 
 .. sourcecode:: bash
 
     source activate myenv
     conda install pip
     conda install ipykernel # or pip install ipykernel
 
 For example, using conda environments, install a ``Python (myenv)`` Kernel in a first
 environment:
 
 .. sourcecode:: bash
 
     source activate myenv
     python -m ipykernel install --user --name myenv --display-name "Python (myenv)"
 
 And in a second environment, after making sure ipykernel is installed in it:
 
 .. sourcecode:: bash
 
     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.
 
 Using virtualenv or conda envs, you can make your IPython kernel in one env available to Jupyter in a different env. To do so, run ipykernel install from the kernel's env, with --prefix pointing to the Jupyter env:
 
 .. sourcecode:: bash
 
     /path/to/kernel/env/bin/python -m ipykernel install --prefix=/path/to/jupyter/env --name 'python-my-env'
 
 Note that this command will create a new configuration for the kernel in one of the prefered location (see ``jupyter --paths`` command for more details):
 
 * system-wide (e.g. /usr/local/share),
 * in Jupyter's env (sys.prefix/share),
 * per-user (~/.local/share or ~/Library/share)
 
 If you want to edit the kernelspec before installing it, you can do so in two steps.
 First, ask IPython to write its spec to a temporary location:
 
 .. sourcecode:: bash
 
     ipython kernel install --prefix /tmp
 
 edit the files in /tmp/share/jupyter/kernels/python3 to your liking, then when you are ready, tell Jupyter to install it (this will copy the files into a place Jupyter will look):
 
 .. sourcecode:: bash
 
     jupyter kernelspec install /tmp/share/jupyter/kernels/python3