/tag/jupyter

  • Custom Jupyter Kernels

    You can create custom kernels from an Anaconda environment or a Singularity container. In both cases you’ll need to install the ipykernel package. Jupyter kernel based on Anaconda environment To create a custom kernel of the Anaconda environment myenv that uses Python 3.7: module load anaconda/2019.10-py3.7 conda create -n myenv python=3.7 ipykernel <other_packages> source activate myenv python -m ipykernel install –user –name myenv –display-name "My Env" Note: You can customize the display name for your kernel. It is shown when you hover over a tile in JupyterLab. If you do not specify a display name, the default Python [conda env:<ENV_NAME>] will be shown.
  • Ivy Secure Environment

    Ivy Ivy is a secure computing environment for researchers consisting of virtual machines (Linux and Windows). Researchers can use Ivy to process and store sensitive data with the confidence that the environment is secure and meets HIPAA or CUI requirements. Overview Ivy consists of both virtual computing environments and secure storage. In order to obtain access to either system, users must 1. Submit an account request, 2. Complete the Information Security Awareness Training, and 3. Ensure their personal computer meets all High Security VPN requirements. Requesting Access Training High Security VPN Virtual Machines JupyterLab Notebooks Data Transfer In/Out of Ivy HIPAA Compliance Requesting Access University of Virginia tenure stream and academic general faculty, research faculty, research scientists, and postdoctoral associates may request an account on Ivy.