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--- techsupport:services:jupyter [2023/02/22 19:47] – kjohns23
+++ techsupport:services:jupyter [2023/02/22 20:44] (current) – kjohns23
@@ Line 24: / Line 24: @@
 ==== Jupyter Environments ====
-=== Minimal===
-This is a basic Jupyter environment to support Python notebooks. Details of all installed utilities can be found in the [[https://jupyter-docker-stacks.readthedocs.io/en/latest/using/selecting.html#jupyter-minimal-notebook|Jupyter documentation]].
 === Datascience===
 This Jupyer environment includes libraries for data analysis from the Julia, Python, and R communities. Details of installed utilites can be found in the [[https://jupyter-docker-stacks.readthedocs.io/en/latest/using/selecting.html#jupyter-datascience-notebook|Jupyter documentation]].
@@ Line 64: / Line 61: @@
 This environment includes the [[http://beakerx.com/|BeakerX]] collection of kernels and utilities. Included are, Python3, Clojure, Java and Kotlin.
-==== Adding Libraries ====
+==== Adding Libraries and Environments ====
-You can add additional libraries to your own notebooks using "pip install package", "conda install package", or "install.packages()" for R. By default these packages only persist as long as your Jupyter session. If you find yourself installing the same package often, contact [[help@socs.uoguelph.ca|help@socs.uoguelph.ca]] and we will get it added to the default environment.
+You may want to create a separate environment that contains specific versions of packages. You can use Conda to set this up. Any environments you create will persist after logging out. To set up a basic environment open the Terminal through the Jupyter Launcher and enter one of the following.
+  * <code>conda create -n my_env_name ipykernel</code> - create a base python environment
+  * <code>conda create -n my_env_name r-ikernel</code> - create a base R environment
+Once you have set up your environment you can view it in the list of available kernels in the Jupyter Launcher. You can add additional packages/libraries to your environment through the Terminal. For more details on managing Conda environments and packages see the following:
+  * [[https://conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html|Manage Conda Environments]]
+  * [[https://conda.io/projects/conda/en/latest/user-guide/tasks/manage-pkgs.html|Manage Conda Packages]]
+==== Jupyterhub Extensions ====
+The following extensions have been installed and made available for the Jupyter Datascience Environment.
+=== nbgitpuller ===
+nbgitpuller allows you to distribute a git repository containing jupyter notebooks as a single link. For more details see: https://hub.jupyter.org/nbgitpuller/. This extension is "pull only".
+=== jupyterlab-git ===
+This git extension allows both push and pull operations to manage jupyter notebooks with git, however it is slightly more complex to use than nbgitpuller. Details on how to use this extension can be found here: https://github.com/jupyterlab/jupyterlab-git#readme
-==== Changing your Environment ====
+==== Changing your Jupyter Environment ====
-If you need to change to a different environment, you will need to stop your server and start a new one. First, click "File" and select "Hub Control Panel".
+If you need to change to a Jupyter different environment, you will need to stop your server and start a new one. First, click "File" and select "Hub Control Panel".
 {{:techsupport:services:jupyter_3_controlpanel.png?200|}}