Setting conda virtual environment /jupyter kernel for all users in jupyterhub

I am the admin for the jupyterhub environment have added close to 50 users and have install anaconda latest version on the ubuntu server with a jupyterhub environment running on it. I have created a condo virtual environment through the terminal and installed nb conda kernel, ipykernel for the same so it gets listed in my notebook and Jupyterhub. I am able to see the virtual environment listed in the jupyterhub/notebook and use them without any issues. I want to replicate the conda virtual environment across all the users. I can manually install the environment which is time/space consuming. Need to know is there a way to replicate the virtual environment which is in admin user to other non-admin users in jupyterhub. Any pointers and suggestions would be appreciated.

Any help/pointers on this would be helpful.
Thanks

Do you need to replicate the environment so users can modify it, or could all users use the same (read-only) conda environment?

Hi Manics,

Thanks a ton for your response. Users should use as read only environment( since Admin will set up the virtual environment for them).

Regards,
Prakash

You should be able to use the same environment as the one created by the admin. If this doesn’t work please could you show us your full config? Thanks!

Sorry I am a starter in this how to get the full config any command needs to be executed or any configuration file (saved in the system) that you are looking for kindly provide the instructions to get the config details.

Regards,

Since you’re new to JupyterHub I recommend following a guide such as The Littlest JupyterHub which has full instructions on installing JupyterHub and configuring your user environment:
https://tljh.jupyter.org/en/latest/

Thanks for the reference. I followed the same to while setting up the environment which helped to setup the environment with out any issues . Any way i figured it out moved the kernels installed for environments in opt/anaconda/envs to this /opt/tljh/user/share/jupyter/kernels resolved this issue.