You can pass a Git repository URL which contains an environment.yml file in the root folder when starting JupyterLab, the conda environment will automatically be installed at the start of your container, and available in the JupyterLab Launcher page. With the ghcr.io/maastrichtu-ids/jupyterlab:latest image, you can easily start notebooks from the JupyterLab Launcher page using installed conda environments, at the condition nb_conda_kernels and ipykernel are installed in those environments. You can also build your own image, we recommend to use this repository as example to extend a JupyterLab image: □️ Manage dependencies with Conda jupyter/all-spark-notebook: if you want to run Spark locally in the notebook.jupyter/pyspark-notebook: if you want to connect to a Spark cluster.jupyter/tensorflow-notebook: with tensorflow package pre-installed.jupyter/datascience-notebook: with Julia kernel.jupyter/scipy-notebook: some packages for science are preinstalled.ghcr.io/maastrichtu-ids/jupyterlab:knowledge-graph: custom image for working with knowledge graph on the DSRI, with SPARQL kernel and OpenRefine.ghcr.io/maastrichtu-ids/jupyterlab:latest: custom image for data science on the DSRI, with additional kernels (Java), conda integration, VisualStudio Code, and autocomplete for Python Vertex AI Workbench user-managed notebooks instances let you create and manage deep learning virtual machine (VM) instances that are prepackaged with JupyterLab. GPULab is a turnkey JupyterLab Notebook environment atop a feature-packed Ubuntu.With this template you can use any image based on the official Jupyter docker stack: You can find the persistent volumes in the DSRI web UI, go to the Administrator view > Storage > Persistent Volume Claims. The DSRI will automatically create a persistent volume to store data you will put in the /home/jovyan/work folder (the folder used by the notebook interface). Your git username and email to automatically configure git.Docker image to use for the notebook (see below for more details on customizing the docker image).Optionally you can provide a git repository to be automatically cloned in the JupyterLab (if there is a requirements.txt packages will be automatically installed with pip).When instantiating the template you can provide a few parameters, such as: You can start a container using the JupyterLab template in the Catalog web UI (make sure the Templates checkbox is checked) Start a JupyterLab container based on the official Jupyter docker stacks (debian), with sudo privileges to install anything you need (e.g.
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