Available Software Toggle submenu visibility.OSC Custom Commands Toggle submenu visibility.HOWTO: Use ulimit command to set soft limits. ![]() HOWTO: Use an Externally Hosted License.HOWTO: Use a Conda/Virtual Environment With Jupyter.HOWTO: Deploy your own endpoint on a server.HOWTO: Use Globus (Overview) Toggle submenu visibility.HOWTO: Use Docker and Apptainer/Singularity Containers at OSC.HOWTO: Use Cron and OSCusage for Regular Emailed Reports.HOWTO: Submit multiple jobs using parameters.HOWTO: Submit Homework to Repository at OSC.HOWTO: Manage Access Control List (ACLs) Toggle submenu visibility.HOWTO: Identify users on a project account and check status.HOWTO: Establish durable SSH connections.HOWTO: Use GPU with Tensorflow and PyTorch.HOWTO: Install Python packages from source.HOWTO: Create and Manage Python Environments Toggle submenu visibility.HOWTO: Collect performance data for your program.HOW TO: Look at requested time accuracy using XDMoD.Classroom Project Resource Guide Toggle submenu visibility.Budgets and Accounts Toggle submenu visibility.Getting Started Toggle submenu visibility.If the envirnoment is rebuilt or renamed, users may want to erase any custom jupyter kernel installations. you can enable debug mode at upper-right kernel of the notebook Remove kernel open a notebook with the debugger kernel.Ĥ. ![]() Once the debugger kernel is done, you can use it:Ģ. You should see a kernelspec 'conda_jupyterlab-debugger' created in home directory. $ ~support/classroom/tools/create_jupyter_kernel conda jupyterlab-debugger $ conda create -n jupyterlab-debugger -c conda-forge "ipykernel>=6" xeus-python Please create your own kernel with conda using the following commands: Install Jupyterlab Debugger kernelĪccording to Jupyterlab page, debugger requires ipykernel >= 6. This results in the kernel name "My Research Project" in the Jupyter kernel list. ![]() ~support/classroom/tools/create_jupyter_kernel conda MYENV "My Research Project" You can change the display name by appending a preferred name in the above commands. The resulting kernel name appears as "MYENV " in the Jupyter kernel list. ~support/classroom/tools/create_jupyter_kernel venv /path/to/MYENV If the Python virtual environment was created via python3 -m venv /path/to/MYENV command, use the following command ~support/classroom/tools/create_jupyter_kernel conda /path/to/MYENV If the Conda environment was created via conda create -n /path/to/MYENV command, use the following command: ~support/classroom/tools/create_jupyter_kernel conda MYENV If the Conda environment was created via conda create -n MYENV command, use the following command: Replace "MYENV" with the name of your Conda environment or the path to the environment. Run one of the following commands based on how your Conda/virtual environment was created. You can check available Python versions by using the command: Replace "python" or "miniconda3" with the appropriate version, which could be the version you used to create your Conda/venv environment. Load the preferred version of Python or Miniconda3 using the command: *See create conda/virtual environment if there is not already an environment that has been created.
0 Comments
Leave a Reply. |
Details
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |