uv-project-runner

You can manage Python dependencies for multiple scripts by centralizing them in a workspace-level `pyproject.toml` file. This ensures all scripts run from a single virtual environment using the `uv` package manager for consistency.

A unified virtual environment reduces disk space and ensures consistent dependency versions across all Python scripts. By using a single `.venv` at the workspace root, you avoid conflicting package installations.

To run a Python script in a shared workspace, navigate to the workspace root and execute the command `uv run python path/to/your/script.py`. This runs the script within the unified virtual environment.

Yes, `uv` works directly with `pyproject.toml` and generates a `uv.lock` file to manage dependencies. This centralizes Python package management for the entire workspace within the shared virtual environment.

Yes, you can run Python scripts for tasks like PDF extraction or CSV conversion using `uv run`. This executes them within the shared workspace environment, ensuring all required packages are managed efficiently.

Using a single virtual environment for a Python workspace means all skills share the exact same dependency versions. This limits running scripts that require conflicting package versions simultaneously within the same workspace.