Re-add user env files

This commit is contained in:
Jordan Bradford
2023-05-22 20:33:07 -04:00
parent 14af23ea2e
commit 5803e2ab3b
4 changed files with 283 additions and 3 deletions

View File

@@ -19,9 +19,9 @@ content/share-data
:caption: The user environment
:titlesonly: true
env/user-environment
env/notebook-interfaces
env/server-resources
user-env/user-environment
user-env/notebook-interfaces
user-env/server-resources
```
## Authentication
@@ -31,6 +31,7 @@ with your JupyterHub. For more information on Authentication, see
[](/topic/authenticator-configuration)
```{toctree}
:caption: Authentication
:titlesonly: true
auth/dummy

View File

@@ -0,0 +1,57 @@
(howto/user-env/notebook-interfaces)=
# Change default User Interface
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.
1. To launch **JupyterLab** when users log in, run the following in an
admin console:
```bash
sudo tljh-config set user_environment.default_app jupyterlab
```
2. Alternatively, to launch **nteract** when users log in, run the
following in the admin console:
```bash
sudo tljh-config set user_environment.default_app nteract
```
3. Apply the changes by restarting JupyterHub. This should not disrupt
current users.
```bash
sudo tljh-config reload hub
```
If this causes problems, check the [logs](#troubleshoot-logs-jupyterhub) for
clues on what went wrong.
Users might have to restart their servers from control panel to get the
new interface.

View File

@@ -0,0 +1,8 @@
(howto/user-env/server-resources)=
# Configure resources available to users
To configure the resources that are available to your users (such as
RAM, CPU and Disk Space), see the section [](#tljh-set-user-limits).
For information on **resizing** the environment available to users *after* you\'ve created
your JupyterHub, see [](#howto-admin-resize).

View File

@@ -0,0 +1,214 @@
(howto/user-env/user-environment)=
# Install conda, pip or apt packages
`TLJH (The Littlest JupyterHub)`{.interpreted-text role="abbr"} 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 [admin rights](#howto-admin-admin-users)
can install packages easily.
(howto/user-env/user-environment-pip)=
## Installing pip packages
[pip](https://pypi.org/project/pip/) is the recommended 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.
![New Terminal button under New menu](../../images/notebook/new-terminal-button.png)
If you already have a terminal open as an admin user, that should
work too!
2. Install a package!
```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/user-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.
![New Terminal button under New menu](../../images/notebook/new-terminal-button.png)
If you already have a terminal open as an admin user, that should
work too!
2. Install a package!
```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/user-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.
![New Terminal button under New menu](../../images/notebook/new-terminal-button.png)
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.
```bash
sudo apt update
```
3. Install the packages you want.
```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 environment 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 `$PATH` environment variable for all
JupyterHub users, so everything installed in the user environment is
available to them automatically. If you are using `ssh` to access your
server instead, you can get access to the same environment with:
```bash
export PATH=/opt/tljh/user/bin:${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 `$PATH` environment variable is usually reset, for
security reasons. This leads to error messages like:
```bash
sudo conda install -c conda-forge gdal
sudo: conda: command not found
```
The most common & portable way to fix this when using `ssh` is:
```bash
sudo PATH=${PATH} conda install -c conda-forge gdal
```
## Upgrade to a newer Python version
All new TLJH installs use miniconda 4.7.10, which comes with a Python
3.7 environment for the users. The previously TLJH installs came with
miniconda 4.5.4, which meant a Python 3.6 environment.
To upgrade the Python version of the user environment, one can:
- **Start fresh on a machine that doesn\'t have TLJH already
installed.**
See the [](#install-installing) section about how to install TLJH.
- **Upgrade Python manually.**
Because upgrading Python for existing installs can break packages
already installed under the old Python, upgrading your current TLJH
installation, will NOT upgrade the Python version of the user
environment, but you may do so manually.
**Steps:**
1. Activate the user environment, if using ssh. If the terminal was
started with JupyterHub, this step can be skipped:
```bash
source /opt/tljh/user/bin/activate
```
2. Get the list of currently installed pip packages (so you can
later install them under the new Python):
```bash
pip freeze > pip_pkgs.txt
```
3. Update all conda installed packages in the environment:
```bash
sudo PATH=${PATH} conda update --all
```
4. Update Python version:
```bash
sudo PATH=${PATH} conda install python=3.7
```
5. Install the pip packages previously saved:
```bash
pip install -r pip_pkgs.txt
```