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Rename 'envt' to 'env'

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Other option is the full blown 'environment'
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yuvipanda
2018-08-12 21:12:16 -07:00
parent 295b0683a2
commit d4b28bb62f
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.. _howto/env/notebook_interfaces:
=======================================
Change default User Interface for users
=======================================
By default, logging into TLJH puts you in the classic Jupyter Notebook interface
we all know and love. However, there are at least two other popular notebook
interfaces you can use:
1. `JupyterLab <http://jupyterlab.readthedocs.io/en/stable/>`_
2. `nteract <https://nteract.io/>`_
Both these interfaces are also shipped with tljh by default. You can try them
temporarily, or set them to be the default interface whenever you login.
Trying an alternate interface temporarily
=========================================
When you log in & start your server, by default the URL in your browser
will be something like ``/user/<username>/tree``. The ``/tree`` is what tells
the notebook server to give you the classic notebook interface.
* **For the JupyterLab interface**: change ``/tree`` to ``/lab``.
* **For the nteract interface**: change ``/tree`` to ``/nteract``
You can play around with them and see what fits your use cases best.
Changing the default user interface
===================================
You can change the default interface users get when they log in by modifying
``config.yaml`` as an admin user.
#. To launch **JupyterLab** when users log in, run the following in an admin console:
.. code-block:: yaml
sudo -E tljh-config set user_environment.default_app jupyterlab
#. Alternatively, to launch **nteract** when users log in, run the following in the admin console:
.. code-block:: yaml
sudo -E tljh-config set user_environment.default_app nteract
#. Apply the changes by restarting JupyterHub. This should not disrupt current users.
.. code-block:: yaml
sudo -E tljh-config reload
If this causes problems, check the :ref:`troubleshoot_logs_jupyterhub` for clues
on what went wrong.
Users might have to restart their servers from control panel to get the new interface.

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.. _howto/env/user_environment:
==================================
Install conda, pip or apt packages
==================================
:abbr:`TLJH (The Littlest JupyterHub)` starts all users in the same `conda <https://conda.io/docs/>`_
environment. Packages / libraries installed in this environment are available
to all users on the JupyterHub. Users with :ref:`admin rights <howto/admin/admin-users>` can install packages
easily.
.. _howto/env/user_environment_pip:
Installing pip packages
=======================
`pip <https://pypi.org/project/pip/>`_ is the recomended tool for installing packages
in Python from the `Python Packaging Index (PyPI) <https://pypi.org/>`_. PyPI has
almost 145,000 packages in it right now, so a lot of what you need is going to be there!
1. Log in as an admin user and open a Terminal in your Jupyter Notebook.
.. image:: ../../images/notebook/new-terminal-button.png
:alt: New Terminal button under New menu
If you already have a terminal open as an admin user, that should work too!
2. Install a package!
.. code-block:: bash
sudo -E pip install numpy
This installs the ``numpy`` library from PyPI and makes it available
to all users.
.. note::
If you get an error message like ``sudo: pip: command not found``,
make sure you are not missing the ``-E`` parameter after ``sudo``.
.. _howto/env/user_environment_conda:
Installing conda packages
=========================
Conda lets you install new languages (such as new versions of python, node, R, etc)
as well as packages in those languages. For lots of scientific software, installing
with conda is often simpler & easier than installing with pip - especially if it
links to C / Fortran code.
We recommend installing packages from `conda-forge <https://conda-forge.org/>`_,
a community maintained repository of conda packages.
1. Log in as an admin user and open a Terminal in your Jupyter Notebook.
.. image:: ../../images/notebook/new-terminal-button.png
:alt: New Terminal button under New menu
If you already have a terminal open as an admin user, that should work too!
2. Install a package!
.. code-block:: bash
sudo -E conda install -c conda-forge gdal
This installs the ``gdal`` library from ``conda-forge`` and makes it available
to all users. ``gdal`` is much harder to install with pip.
.. note::
If you get an error message like ``sudo: conda: command not found``,
make sure you are not missing the ``-E`` parameter after ``sudo``.
.. _howto/env/user_environment_apt:
Installing apt packages
=======================
`apt <https://help.ubuntu.com/lts/serverguide/apt.html.en>`_ is the official package
manager for the `Ubuntu Linux distribution <https://www.ubuntu.com/>`_. You can install
utilities (such as ``vim``, ``sl``, ``htop``, etc), servers (``postgres``, ``mysql``, ``nginx``, etc)
and a lot more languages than present in ``conda`` (``haskell``, ``prolog``, ``INTERCAL``).
Some third party software (such as `RStudio <https://www.rstudio.com/products/rstudio/download/>`_)
is distributed as ``.deb`` files, which are the files ``apt`` uses to install software.
You can search for packages with `Ubuntu Package search <https://packages.ubuntu.com/>`_ -
make sure to look in the version of Ubuntu you are using!
1. Log in as an admin user and open a Terminal in your Jupyter Notebook.
.. image:: ../../images/notebook/new-terminal-button.png
:alt: New Terminal button under New menu
If you already have a terminal open as an admin user, that should work too!
2. Update list of packages available. This makes sure you get the latest version of
the packages possible from the repositories.
.. code-block:: bash
sudo apt update
3. Install the packages you want.
.. code-block:: bash
sudo apt install mysql-server git
This installs (and starts) a ``MySQL <https://www.mysql.com/>`` database server
and ``git``.
User environment location
=========================
The user environment is a conda enviornment set up in ``/opt/tljh/user``, with
a Python3 kernel as the default. It is readable by all users, but writeable only
by users who have root access. This makes it possible for JupyterHub admins (who have
root access with ``sudo``) to install software in the user environment easily.
Accessing user environment outside JupyterHub
=============================================
We add ``/opt/tljh/user/bin`` to the ``$PATH`` environment variable for all JupyterHub
users, so everything installed in the user environment is available to them automatically.
If you are using ``ssh`` to access your server instead, you can get access to the same
environment with:
.. code-block:: bash
export PATH=/opt/tljh/user/bin:${PATH}
Whenever you run any command now, the user environment will be searched first before
your system environment is. So if you run ``python3 <somefile>``, it'll use the ``python3``
installed in the user environment (``/opt/tljh/user/bin/python3``) rather than the ``python3``
installed in your system environment (``/usr/bin/python3``). This is usually what you want!
To make this change 'stick', you can add the line to the end of the ``.bashrc`` file in
your home directory.
When using ``sudo``, the ``PATH`` environment variable is usually reset, for security
reasons. This leads to error messages like:
.. code-block:: console
$ sudo conda install -c conda-forge gdal
sudo: conda: command not found
The most common & portable way to fix this when using ``ssh`` is:
.. code-block:: bash
sudo PATH=${PATH} conda install -c conda-forge gdal