Within each user workspace where JupyterLab is provisioned, a dedicated Conda Store is also available.
Conda Store enables users to define and manage reproducible Python environments. This ensures consistent execution across sessions and allows developers to control the underlying libraries and dependencies for their workflows.
Figure 1:Conda store User interface
Dedicated environments can be created based on user permissions, either for an individual user or for an entire workspace, and shared with colleagues or other users.
Conda Store supports a GUI or YAML syntax for environment creation. Examples and how-to guides can be found in the official documentation.
Figure 2:Conda store environment creation