uv 0.1.13

An extremely fast Python package installer and resolver, written in Rust.

uv

An extremely fast Python package installer and resolver, written in Rust. Designed as a drop-in replacement for pip and pip-compile.

uv is backed by Astral, the creators of Ruff.

Highlights

• ⚖️ Drop-in replacement for common pip, pip-tools, and virtualenv commands.
• ⚡️ 10-100x faster than pip and pip-tools (pip-compile and pip-sync).
• 💾 Disk-space efficient, with a global cache for dependency deduplication.
• 🐍 Installable via curl, pip, pipx, etc. uv is a static binary that can be installed without Rust or Python.
• 🧪 Tested at-scale against the top 10,000 PyPI packages.
• 🖥️ Support for macOS, Linux, and Windows.
• 🧰 Advanced features such as dependency version overrides and alternative resolution strategies.
• ⁉️ Best-in-class error messages with a conflict-tracking resolver.
• 🤝 Support for a wide range of advanced pip features, including editable installs, Git dependencies, direct URL dependencies, local dependencies, constraints, source distributions, HTML and JSON indexes, and more.

Getting Started

Install uv with our standalone installers, or from PyPI:

# On macOS and Linux.
curl -LsSf https://astral.sh/uv/install.sh | sh

# On Windows.
powershell -c "irm https://astral.sh/uv/install.ps1 | iex"

# With pip.
pip install uv

# With pipx.
pipx install uv

# With Homebrew.
brew install uv

# With Pacman.
pacman -S uv

To create a virtual environment:

uv venv  # Create a virtual environment at .venv.

To activate the virtual environment:

# On macOS and Linux.
source .venv/bin/activate

# On Windows.
.venv\Scripts\activate

To install a package into the virtual environment:

uv pip install flask                # Install Flask.
uv pip install -r requirements.txt  # Install from a requirements.txt file.
uv pip install -e .                 # Install the current project in editable mode.
uv pip install "package @ ."        # Install the current project from disk
uv pip install "flask[dotenv]"      # Install Flask with "dotenv" extra.

To generate a set of locked dependencies from an input file:

uv pip compile pyproject.toml -o requirements.txt   # Read a pyproject.toml file.
uv pip compile requirements.in -o requirements.txt  # Read a requirements.in file.

To sync a set of locked dependencies with the virtual environment:

uv pip sync requirements.txt  # Install from a requirements.txt file.

uv's pip-install and pip-compile commands support many of the same command-line arguments as existing tools, including -r requirements.txt, -c constraints.txt, -e . (for editable installs), --index-url, and more.

Limitations

uv does not support the entire pip feature set. Namely, uv does not (and does not plan to) support the following pip features:

• .egg dependencies
• Editable installs for Git and direct URL dependencies (editable installs are supported for local dependencies)

On the other hand, uv plans to (but does not currently) support:

• Hash-checking mode
• URL requirements without package names (e.g., https://... instead of package @ https://...)

Like pip-compile, uv generates a platform-specific requirements.txt file (unlike, e.g., poetry and pdm, which generate platform-agnostic poetry.lock and pdm.lock files). As such, uv's requirements.txt files may not be portable across platforms and Python versions.

Roadmap

uv is an extremely fast Python package resolver and installer, designed as a drop-in replacement for pip, pip-tools (pip-compile and pip-sync), and virtualenv.

uv represents an intermediary goal in our pursuit of a "Cargo for Python": a comprehensive project and package manager that is extremely fast, reliable, and easy to use.

Think: a single binary that bootstraps your Python installation and gives you everything you need to be productive with Python, bundling not only pip, pip-tools, and virtualenv, but also pipx, tox, poetry, pyenv, ruff, and more.

Our goal is to evolve uv into such a tool.

In the meantime, though, the narrower pip-tools scope allows us to solve the low-level problems involved in building such a tool (like package installation) while shipping something immediately useful with a minimal barrier to adoption.

Advanced Usage

Python discovery

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.

When running pip sync or 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.

When running pip compile, uv does not require a virtual environment and will search for a Python interpreter 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.
• The Python interpreter available as python3 on macOS and Linux, or python.exe on Windows.

If a --python-version is provided to pip compile (e.g., --python-version=3.7), uv will search for a Python interpreter matching that version 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.
• The Python interpreter available as, e.g., python3.7 on macOS and Linux.
• The Python interpreter available as python3 on macOS and Linux, or python.exe on Windows.
• On Windows, the Python interpreter returned by py --list-paths that matches the requested version.

Since uv has no dependency on Python, it can even 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, no matter where uv is installed.

Finally, uv can also install into non-virtual environments by providing a --python argument 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, as an approximate shorthand for, e.g., uv pip install --python=$(which python3). Though we generally recommend the use of virtual environments for dependency management, --system is intended to enable the use of uv in continuous integration and containerized environments.

Git authentication

uv allows packages to be installed from Git and supports the following schemes for authenticating with private repositories.

Using SSH:

• git+ssh://git@<hostname>/... (e.g. git+ssh://[e-mail]/astral-sh/uv)
• git+ssh://git@<host>/... (e.g. git+ssh://[e-mail]-key-2/astral-sh/uv)

See the GitHub SSH documentation for more details on how to configure SSH.

Using a password or token:

• git+https://<user>:<token>@<hostname>/... (e.g. git+https://git:[e-mail]/astral-sh/uv)
• git+https://<token>@<hostname>/... (e.g. git+https://[e-mail]/astral-sh/uv)
• git+https://<user>@<hostname>/... (e.g. git+https://[e-mail]/astral-sh/uv)

When using a GitHub personal access token, the username is arbitrary. GitHub does not support logging in with password directly, although other hosts may. If a username is provided without credentials, you will be prompted to enter them.

If there are no credentials present in the URL and authentication is needed, the Git credential helper will be queried.

Dependency caching

uv uses aggressive caching to avoid re-downloading (and re-building dependencies) that have already been accessed in prior runs.

The specifics of uv's caching semantics vary based on the nature of the dependency:

• For registry dependencies (like those downloaded from PyPI), uv respects HTTP caching headers.
• For direct URL dependencies, uv respects HTTP caching headers, and also caches based on the URL itself.
• For Git dependencies, uv caches based on the fully-resolved Git commit hash. As such, uv pip compile will pin Git dependencies to a specific commit hash when writing the resolved dependency set.
• For local dependencies, uv caches based on the last-modified time of the setup.py or pyproject.toml file.

If you're running into caching issues, uv includes a few escape hatches:

• To force uv to revalidate cached data for all dependencies, run uv pip install --refresh ....
• To force uv to revalidate cached data for a specific dependency, run, e.g., uv pip install --refresh-package flask ....
• To force uv to ignore existing installed versions, run uv pip install --reinstall ....
• To clear the global cache entirely, run uv cache clean.

Resolution strategy

By default, uv follows the standard Python dependency resolution strategy of preferring the latest compatible version of each package. For example, uv pip install flask>=2.0.0 will install the latest version of Flask (at time of writing: 3.0.0).

However, uv's resolution strategy can be configured to support alternative workflows. With --resolution=lowest, uv will install the lowest compatible versions for all dependencies, both direct and transitive. Alternatively, --resolution=lowest-direct will opt for the lowest compatible versions for all direct dependencies, while using the latest compatible versions for all transitive dependencies. This distinction can be particularly useful for library authors who wish to test against the lowest supported versions of direct dependencies without restricting the versions of transitive dependencies.

For example, given the following requirements.in file:

flask>=2.0.0

Running uv pip compile requirements.in would produce the following requirements.txt file:

# This file was autogenerated by uv via the following command:
#    uv pip compile requirements.in
blinker==1.7.0
    # via flask
click==8.1.7
    # via flask
flask==3.0.0
itsdangerous==2.1.2
    # via flask
jinja2==3.1.2
    # via flask
markupsafe==2.1.3
    # via
    #   jinja2
    #   werkzeug
werkzeug==3.0.1
    # via flask

However, uv pip compile --resolution=lowest requirements.in would instead produce:

# This file was autogenerated by uv via the following command:
#    uv pip compile requirements.in --resolution=lowest
click==7.1.2
    # via flask
flask==2.0.0
itsdangerous==2.0.0
    # via flask
jinja2==3.0.0
    # via flask
markupsafe==2.0.0
    # via jinja2
werkzeug==2.0.0
    # via flask

Pre-release handling

By default, uv will accept pre-release versions during dependency resolution in two cases:

1. If the package is a direct dependency, and its version markers include a pre-release specifier (e.g., flask>=2.0.0rc1).
2. If all published versions of a package are pre-releases.

If dependency resolution fails due to a transitive pre-release, uv will prompt the user to re-run with --prerelease=allow, to allow pre-releases for all dependencies.

Alternatively, you can add the transitive dependency to your requirements.in file with pre-release specifier (e.g., flask>=2.0.0rc1) to opt in to pre-release support for that specific dependency.

Pre-releases are notoriously difficult to model, and are a frequent source of bugs in other packaging tools. uv's pre-release handling is intentionally limited and intentionally requires user intervention to opt in to pre-releases to ensure correctness, though pre-release handling will be revisited in future releases.

Dependency overrides

Historically, pip has supported "constraints" (-c constraints.txt), which allows users to narrow the set of acceptable versions for a given package.

uv supports constraints, but also takes this concept further by allowing users to override the acceptable versions of a package across the dependency tree via overrides (--override overrides.txt).

In short, overrides allow the user to lie to the resolver by overriding the declared dependencies of a package. Overrides are a useful last resort for cases in which the user knows that a dependency is compatible with a newer version of a package than the package declares, but the package has not yet been updated to declare that compatibility.

For example, if a transitive dependency declares pydantic>=1.0,<2.0, but the user knows that the package is compatible with pydantic>=2.0, the user can override the declared dependency with pydantic>=2.0,<3 to allow the resolver to continue.

While constraints are purely additive, and thus cannot expand the set of acceptable versions for a package, overrides can expand the set of acceptable versions for a package, providing an escape hatch for erroneous upper version bounds.

Multi-version resolution

uv's pip-compile command produces a resolution that's known to be compatible with the current platform and Python version. Unlike Poetry, PDM, and other package managers, uv does not yet produce a machine-agnostic lockfile.

However, uv does support resolving for alternate Python versions via the --python-version command line argument. For example, if you're running uv on Python 3.9, but want to resolve for Python 3.8, you can run uv pip compile --python-version=3.8 requirements.in to produce a Python 3.8-compatible resolution.

Platform support

uv has Tier 1 support for the following platforms:

• macOS (Apple Silicon)
• macOS (x86_64)
• Linux (x86_64)
• Windows (x86_64)

uv is continuously built, tested, and developed against its Tier 1 platforms. Inspired by the Rust project, Tier 1 can be thought of as "guaranteed to work".

uv has Tier 2 support ("guaranteed to build") for the following platforms:

• Linux (PPC64)
• Linux (PPC64LE)
• Linux (aarch64)
• Linux (armv7)
• Linux (i686)
• Linux (s390x)

uv ships pre-built wheels to PyPI for its Tier 1 and Tier 2 platforms. However, while Tier 2 platforms are continuously built, they are not continuously tested or developed against, and so stability may vary in practice.

Beyond the Tier 1 and Tier 2 platforms, uv is known to build on i686 Windows, and known not to build on aarch64 Windows, but does not consider either platform to be supported at this time.

uv supports and is tested against Python 3.8, 3.9, 3.10, 3.11, and 3.12.

Acknowledgements

uv's dependency resolver uses PubGrub under the hood. We're grateful to the PubGrub maintainers, especially Jacob Finkelman, for their support.

uv's Git implementation is based on Cargo.

Some of uv's optimizations are inspired by the great work we've seen in pnpm, Orogene, and Bun. We've also learned a lot from Nathaniel J. Smith's Posy and adapted its trampoline for Windows support.

License

uv is licensed under either of

• Apache License, Version 2.0, (LICENSE-APACHE or https://www.apache.org/licenses/LICENSE-2.0)
• MIT license (LICENSE-MIT or https://opensource.org/licenses/MIT)

at your option.

Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in uv by you, as defined in the Apache-2.0 license, shall be dually licensed as above, without any additional terms or conditions.