Can someone explain a non-project based workflow/configuration for uv? I get creating a bespoke folder, repo, and uv venv for certain long-lived projects (like creating different apps?).
But most of my work, since I adopted conda 7ish years ago, involves using the same ML environment across any number of folders or even throw-away notebooks on the desktop, for instance. I’ll create the environment and sometimes add new packages, but rarely update it, unless I feel like a spring cleaning. And I like knowing that I have the same environment across all my machines, so I don’t have to think about if I’m running the same script or notebook on a different machine today.
The idea of a new environment for each of my related “projects” just doesn’t make sense to me. But, I’m open to learning a new workflow.
Addition: I don’t run other’s code, like pretrained models built with specific package requirements.
But most of my work, since I adopted conda 7ish years ago, involves using the same ML environment across any number of folders or even throw-away notebooks on the desktop, for instance. I’ll create the environment and sometimes add new packages, but rarely update it, unless I feel like a spring cleaning. And I like knowing that I have the same environment across all my machines, so I don’t have to think about if I’m running the same script or notebook on a different machine today.
The idea of a new environment for each of my related “projects” just doesn’t make sense to me. But, I’m open to learning a new workflow.
Addition: I don’t run other’s code, like pretrained models built with specific package requirements.