Creating, Migrating, and Managing Conda Virtual Environments Based on SFS
This topic describes how to migrate the Conda environment on a notebook instance to an SFS disk. In this way, the Conda environment will not be lost after the notebook instance is restarted.
The procedure is as follows:
- Creating a Virtual Environment and Saving It to the SFS Directory
- Cloning the Existing Virtual Environments to the SFS Disk
- Restarting the Image to Activate the Virtual Environment in the SFS Disk
- Saving and Sharing the Virtual Environment
Prerequisites
You have created a notebook instance by setting Resource Type to Dedicated resource pool and Storage to SFS and opened the terminal.
Creating a Virtual Environment and Saving It to the SFS Directory
Create a conda virtual environment.
# shell conda create --prefix /home/ma-user/work/envs/user_conda/sfs-new-env python=3.7.10 -y
View the existing conda virtual environments. The name of the newly created virtual environment may be empty in the output.
# shell conda env list
# conda environments:
#
base /home/ma-user/anaconda3
PyTorch-1.8 /home/ma-user/anaconda3/envs/PyTorch-1.8
python-3.7.10 * /home/ma-user/anaconda3/envs/python-3.7.10
/home/ma-user/work/envs/user_conda/sfs-new-env
Append the new virtual environment to conda envs.
# shell conda config --append envs_dirs /home/ma-user/work/envs/user_conda/
View the existing conda virtual environments. The new virtual environment is properly displayed, and you can switch to it by name.
# shell conda env list conda activate sfs-new-env
# conda environments: # base /home/ma-user/anaconda3 PyTorch-1.8 /home/ma-user/anaconda3/envs/PyTorch-1.8 python-3.7.10 * /home/ma-user/anaconda3/envs/python-3.7.10 sfs-new-env /home/ma-user/work/envs/user_conda/sfs-new-env
(Optional) Register the new virtual environment with the JupyterLab kernel, so that you can directly use it in JupyterLab.
# shell pip install ipykernel ipython kernel install --user --name=sfs-new-env rm -rf /home/ma-user/.local/share/jupyter/kernels/sfs-new-env/logo-*
Note: .local/share/jupyter/kernels/sfs-new-env is used as an example only. Replace it with the actual installation path.
Refresh the JupyterLab page. The new kernel is displayed.
After the notebook instance is restarted, the kernel needs to be registered again.
Cloning the Existing Virtual Environments to the SFS Disk
# shell conda create --prefix /home/ma-user/work/envs/user_conda/sfs-clone-env --clone PyTorch-1.8 -y
Source: /home/ma-user/anaconda3/envs/PyTorch-1.8 Destination: /home/ma-user/work/envs/user_conda/sfs-clone-env Packages: 20 Files: 39687 Preparing transaction: done Verifying transaction: done Executing transaction: done # # To activate this environment, use # # $ conda activate /home/ma-user/work/envs/user_conda/sfs-clone-env # # To deactivate an active environment, use # # $ conda deactivate
View the cloned virtual environments. If the name of the newly created virtual environment is empty, handle the issue according to Append the new virtual environment to conda envs.
# shell conda env list
# conda environments: # base /home/ma-user/anaconda3 PyTorch-1.8 /home/ma-user/anaconda3/envs/PyTorch-1.8 python-3.7.10 /home/ma-user/anaconda3/envs/python-3.7.10 sfs-clone-env /home/ma-user/work/envs/user_conda/sfs-clone-env sfs-new-env * /home/ma-user/work/envs/user_conda/sfs-new-env
(Optional) Register the new virtual environment with the JupyterLab kernel, so that you can directly use it in JupyterLab.
# shell pip install ipykernel ipython kernel install --user --name=sfs-clone-env rm -rf /home/ma-user/.local/share/jupyter/kernels/sfs-clone-env/logo-*
Note: .local/share/jupyter/kernels/sfs-clone-env is used as an example only. Replace it with the actual installation path.
Refresh the JupyterLab page. The new kernel is displayed.
Restarting the Image to Activate the Virtual Environment in the SFS Disk
Method 1: Use the complete conda env path.
# shell conda activate /home/ma-user/work/envs/user_conda/sfs-new-env
Method 2: Append the virtual environment to conda envs and activate it using its name.
# shell conda config --append envs_dirs /home/ma-user/work/envs/user_conda/ conda activate sfs-new-env
Method 3: Use Python or pip in the virtual environment.
# shell /home/ma-user/work/envs/user_conda/sfs-new-env/bin/pip list /home/ma-user/work/envs/user_conda/sfs-new-env/bin/python -V
Saving and Sharing the Virtual Environment
Package the virtual environment to be migrated.
# shell pip install conda-pack conda pack -n sfs-clone-env -o sfs-clone-env.tar.gz --ignore-editable-packages
Collecting packages... Packing environment at '/home/ma-user/work/envs/user_conda/sfs-clone-env' to 'sfs-clone-env.tar.gz' [########################################] | 100% Completed | 3min 33.9s
Decompress the package to the SFS directory.
# shell mkdir /home/ma-user/work/envs/user_conda/sfs-tar-env tar -zxvf sfs-clone-env.tar.gz -C /home/ma-user/work/envs/user_conda/sfs-tar-env
View the existing conda virtual environments.
# shell conda env list
# conda environments: # base /home/ma-user/anaconda3 PyTorch-1.8 * /home/ma-user/anaconda3/envs/PyTorch-1.8 python-3.7.10 /home/ma-user/anaconda3/envs/python-3.7.10 sfs-clone-env /home/ma-user/work/envs/user_conda/sfs-clone-env sfs-new-env /home/ma-user/work/envs/user_conda/sfs-new-env sfs-tar-env /home/ma-user/work/envs/user_conda/sfs-tar-env test-env /home/ma-user/work/envs/user_conda/test-env
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