{"id":7840,"date":"2025-06-12T18:17:40","date_gmt":"2025-06-12T17:17:40","guid":{"rendered":"https:\/\/research.reading.ac.uk\/act\/?post_type=kbe_knowledgebase&#038;p=7840"},"modified":"2026-02-03T14:46:23","modified_gmt":"2026-02-03T14:46:23","slug":"jupyterhub-on-racc2","status":"publish","type":"kbe_knowledgebase","link":"https:\/\/research.reading.ac.uk\/act\/knowledgebase\/jupyterhub-on-racc2\/","title":{"rendered":"JupyterHub on RACC2"},"content":{"rendered":"<h2>Introduction<\/h2>\n<p style=\"margin: 0in; font-family: Calibri; font-size: 11.0pt;\"><span style=\"font-weight: bold;\">JupyterHub <\/span>is a shared, web-based platform that gives each user access to their own private Jupyter environment on a central server. It provides access to <span style=\"font-weight: bold;\">JupyterLab<\/span>, a modern interface for working with code, data, and documents \u2014 including <span style=\"font-weight: bold;\">Jupyter Notebooks<\/span>, which are interactive documents used for data analysis, scientific computing, and software development.<\/p>\n<p style=\"margin-top: 5pt; margin-bottom: 5pt; font-family: Calibri; font-size: 11.0pt;\"><span style=\"font-weight: bold;\">JupyterHub on the RACC2<\/span> removes the need to manually start a <span style=\"font-weight: bold;\">Jupyter Notebook<\/span> or <span style=\"font-weight: bold;\">JupyterLab <\/span>session and then open it in a web browser. Instead, you can use a browser on your local machine (on campus network, on VPN, or via NX) to log in to a persistent web portal\u00a0<a href=\"https:\/\/racc.rdg.ac.uk\/jupyterhub\">https:\/\/racc.rdg.ac.uk\/jupyterhub<\/a>.<\/p>\n<p style=\"margin-top: 5pt; margin-bottom: 5pt; font-family: Calibri; font-size: 11.0pt;\">Under the hood, sessions are transparently scheduled on the <span style=\"font-weight: bold;\">interactive login nodes<\/span>, in the same way as SSH login sessions, with the same generous resource limits: <span style=\"font-weight: bold;\">12 CPUs<\/span> and <span style=\"font-weight: bold;\">256\u00a0GB of RAM <\/span>per user session. Please be considerate with memory usage. The memory limit is intended to prevent an individual user from accidentally overwhelming the server, not to ensure strict fairness or protect against total memory exhaustion.<\/p>\n<p>&nbsp;<\/p>\n<h2>JupyterHub on RACC2 via NX<\/h2>\n<p>Use the following procedure to start a JupyterHub session on the RACC2:<\/p>\n<ol>\n<li>Start an <a href=\"https:\/\/research.reading.ac.uk\/act\/knowledgebase_category\/desktop-guide\/\">NX managed desktop<\/a> session. Or, if you&#8217;re on the campus network, you can go directly to step 2 and open a web browser.<\/li>\n<li>Open a web browser such as Firefox. You can find these under Applications &gt; Internet in the top left menu.<\/li>\n<li>Navigate to the URL: <a style=\"font-family: Calibri; font-size: 11pt;\" href=\"https:\/\/racc.rdg.ac.uk\/jupyterhub\">https:\/\/racc.rdg.ac.uk\/jupyterhub<\/a><\/li>\n<\/ol>\n<h3><\/h3>\n<h3>Kernels:<\/h3>\n<p style=\"margin-top: 5pt; margin-bottom: 5pt; font-family: Calibri; font-size: 11.0pt;\">In a JupyterLab session launched via JupyterHub, you will find <span style=\"font-weight: bold;\">kernels<\/span> corresponding to relevant <span style=\"font-weight: bold;\">centrally managed Conda environments<\/span>. A <span style=\"font-weight: bold;\">kernel<\/span> is the backend process that runs your code in a notebook. Each kernel is tied to a programming language and software environment. You can also register your <span style=\"font-weight: bold;\">personal environments <\/span>as kernels.<\/p>\n<p style=\"margin-top: 5pt; margin-bottom: 5pt; font-family: Calibri; font-size: 11.0pt;\">Instructions for creating personal Conda environments can be found here: <a href=\"https:\/\/research.reading.ac.uk\/act\/knowledgebase\/python-on-the-academic-computing-cluster\/\">https:\/\/research.reading.ac.uk\/act\/knowledgebase\/python-on-the-academic-computing-cluster\/<\/a><\/p>\n<p>&nbsp;<\/p>\n<h4>To register your personal Conda environment in JupyterHub:<\/h4>\n<ol>\n<li style=\"list-style-type: none;\">\n<ol>\n<li><b>Open a Terminal<\/b> from the JupyterHub interface:<br \/>\n<i>File &gt; New &gt; Terminal<\/i><\/li>\n<li><b>Activate your environment<\/b>, for example:\n<pre class=\"\">module load anaconda\r\nsource activate myenv<\/pre>\n<\/li>\n<li><b>Install the Jupyter kernel package<\/b> in your environment (if not already installed):\n<pre class=\"\">conda install ipykernel<\/pre>\n<\/li>\n<li><b>Register your environment as a Jupyter kernel<\/b>:\n<pre class=\"\">python -m ipykernel install --user --name myenv --display-name \"myenv\"<\/pre>\n<\/li>\n<\/ol>\n<p>After completing these steps, your personal environment will appear in the <b>Kernel &gt; Change Kernel<\/b> menu in JupyterLab under the name &#8220;myenv&#8221;, and as an icon to start a Notebook, or Jupyter Console (you might need to reload your session).<\/li>\n<\/ol>\n<h3><\/h3>\n<h3>R<\/h3>\n<p style=\"margin: 0in; font-family: Calibri; font-size: 11.0pt;\">There is also an R environment available within JupyterHub. This is the same R environment which is available on the RACC2. R packages can be installed in your home directory. Advanced users might also use Conda to create multiple R environments, and install dependencies needed to build R packages. However, we are not routinely supporting R on JupyterHub at present.<\/p>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Introduction  JupyterHub is a shared, web-based platform that gives each user access to their own private Jupyter environment on a central server. It provides access to JupyterLab, a modern interface for working with code, data, and documents \u2014 including Jupyter Notebooks, which are interactive documents used for data analysis, scientific computing, and software development.<\/p>\n","protected":false},"author":421,"featured_media":7789,"template":"","meta":{"_acf_changed":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"__cvm_playback_settings":[],"__cvm_video_id":"","_links_to":"","_links_to_target":""},"kbe_taxonomy":[61],"kbe_tags":[],"class_list":["post-7840","kbe_knowledgebase","type-kbe_knowledgebase","status-publish","has-post-thumbnail","hentry","kbe_taxonomy-academic-cluster-articles"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.8.1 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>JupyterHub on RACC2 - Academic Computing Team<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/research.reading.ac.uk\/act\/knowledgebase\/jupyterhub-on-racc2\/\" \/>\n<meta property=\"og:locale\" content=\"en_GB\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"JupyterHub on RACC2 - Academic Computing Team\" \/>\n<meta property=\"og:description\" content=\"Introduction JupyterHub is a shared, web-based platform that gives each user access to their own private Jupyter environment on a central server. 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