
## Summary We want to have consistency between the Ruff and uv documentation for the upcoming release. We don't love the Ruff docs, but we'd rather have consistency and then work towards improving them both, rather than have two very-different documentation sites that both have weaknesses. The setup here is simpler than in Ruff as: (1) we don't yet generate any docs from Rust and (2) we don't try to reuse the README in the uv documentation (which adds a lot of complexity in Ruff). So the change here is mostly a 1-to-1 port to MkDocs. ## Test Plan 
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Python environments
Each Python installation has an environment that is active when Python is used. Packages can be installed into an environment to make their modules available from your Python scripts. Generally, it is considered best practice not to modify a Python installation's environment. This is especially important for Python installations that come with the operating system which often manage the packages themselves. A virtual environment is a lightweight way to isolate packages from a Python installation's environment. Unlike pip
, uv requires using a virtual environment by default.
Creating a virtual environment
uv supports creating virtual environments:
# Create a virtual environment at `.venv`
uv venv
A specific name or path can be specified:
# Create a virtual environment at `my-name`
uv venv my-name
A Python version can be requested:
# Create a virtual environment with Python 3.11
uv venv --python 3.11
Note this requires the requested Python version to be available on the system. However, in preview mode, uv will download Python for you. See the Python request documentation for more details on requesting Python versions.
Using a virtual environment
When using the default virtual environment name, uv will automatically find and use the virtual environment during subsequent invocations.
uv venv
# Install a package in the new virtual environment
uv pip install ruff
The virtual environment can be "activated" to make its packages available:
# On macOS and Linux.
source .venv/bin/activate
# On Windows.
.venv\Scripts\activate
Using arbitrary Python environments
Since uv has no dependency on Python, it can install into virtual environments other than
its own. For example, setting VIRTUAL_ENV=/path/to/venv
will cause uv to install into
/path/to/venv
, regardless of where uv is installed. Note that if VIRTUAL_ENV
is set to
a directory that is not a PEP 405 compliant
virtual environment, it will be ignored.
uv can also install into arbitrary, even non-virtual environments, with the --python
argument
provided to uv pip sync
or uv pip install
. For example, uv pip install --python=/path/to/python
will install into the environment linked to the /path/to/python
interpreter.
For convenience, uv pip install --system
will install into the system Python environment.
Using --system
is roughly equivalent to uv pip install --python=$(which python)
,
but note that executables that are linked to virtual environments will be skipped.
Although we generally recommend using virtual environments for dependency management,
--system
is appropriate in continuous integration and containerized environments.
The --system
flag is also used to opt in to mutating system environments. For example, the
the --python
argument can be used to request a Python version (e.g., --python 3.12
), and uv will
search for an interpreter that meets the request. If uv finds a system interpreter (e.g., /usr/lib/python3.12
),
then the --system
flag is required to allow modification of this non-virtual Python environment.
Without the --system
flag, uv will ignore any interpreters that are not in virtual environments.
Conversely, when the --system
flag is provided, uv will ignore any interpreters that are
in virtual environments.
Installing into system Python across platforms and distributions is notoriously difficult. uv
supports the common cases, but will not work in all cases. For example, installing into system
Python on Debian prior to Python 3.10 is unsupported due to the distribution's patching
of distutils
(but not sysconfig
).
While we always recommend the use of virtual environments, uv considers them to be required in
these non-standard environments.
If uv is installed in a Python environment, e.g., with pip
, it can still be used to modify
other environments. However, when invoked with python -m uv
, uv will default to using the parent
interpreter's environment. Invoking uv via Python adds startup overhead and is not recommended for
general usage.
uv itself does not depend on Python, but it does need to locate a Python environment to (1) install dependencies into the environment and (2) build source distributions.
Discovery of Python environments
When running a command that mutates an environment such as uv pip sync
or uv pip install
,
uv will search for a virtual environment in the following order:
- An activated virtual environment based on the
VIRTUAL_ENV
environment variable. - An activated Conda environment based on the
CONDA_PREFIX
environment variable. - A virtual environment at
.venv
in the current directory, or in the nearest parent directory.
If no virtual environment is found, uv will prompt the user to create one in the current
directory via uv venv
.
If the --system
flag is included, uv will skip virtual environments and search for:
- The Python interpreter available as
python3
on macOS and Linux, orpython.exe
on Windows. - On Windows, the Python interpreter returned by
py --list-paths
that matches the requested version.
If a specific Python version is requested, e.g., --python 3.7
, additional executable names are included:
- The Python interpreter available as, e.g.,
python3.7
on macOS and Linux.
When running a command that does not mutate the environment such as uv pip compile
, uv does not
require a virtual environment. Instead, it needs a Python toolchain to create ephemeral environments.
See the documentation on toolchain discovery for details on discovery.