One common use case for a workspace is that the codebase grows large, and eventually you want some
modules to become independent packages with their own dependency specification. Other use cases are
separating parts of the codebase with different responsibilities, e.g. in a repository with a
library package and CLI package, where the CLI package makes features of the library available but
has additional dependencies, a webserver with a backend and an ingestion package, or a library that
has a performance-critical subroutine implemented in a native language.
Workspaces are not suited when you don't want to install all members together, members have
conflicting requirements, or you simply want individual virtual environments per project. In this
case, use regular (editable) relative path dependencies.
Currently, workspace don't properly support different members having different `requires-python`
values, we apply the highest of all `requires-python` lower bounds to the entire workspace. You need
to use a `uv pip` to install individual member in an older virtual environment.
!!! note
As Python does not provide dependency isolation, uv can't ensure that a package uses only the dependencies it has declared, and not also imports a package that was installed for another dependency. For workspaces specifically, uv can't ensure that packages don't import dependencies declared by another workspace member.
## Usage
A workspace can be created by adding a `tool.uv.workspace` table to a `pyproject.toml` that will
become the workspace root. This table contains `members` (mandatory) and `exclude` (optional), with