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CONTRIBUTING.md

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Contributing

We have issues labeled as Good First Issue and Help Wanted which are good opportunities for new contributors.

Setup

Rust, a C compiler, and CMake are required to build uv.

Linux

On Ubuntu and other Debian-based distributions, you can install the C compiler and CMake with:

sudo apt install build-essential cmake

macOS

You can install CMake with Homebrew:

brew install cmake

See the Python section for instructions on installing the Python versions.

Windows

You can install CMake from the installers or with pipx install cmake.

Testing

For running tests, we recommend nextest.

If tests fail due to a mismatch in the JSON Schema, run: cargo dev generate-json-schema.

Python

Testing uv requires multiple specific Python versions; they can be installed with:

cargo run python install

The storage directory can be configured with UV_PYTHON_INSTALL_DIR.

Local testing

You can invoke your development version of uv with cargo run -- <args>. For example:

cargo run -- venv
cargo run -- pip install requests

Testing on Windows

When testing debug builds on Windows, the stack can overflow resulting in a STATUS_STACK_OVERFLOW error code. This is due to a small stack size limit on Windows that we encounter when running unoptimized builds — the release builds do not have this problem. We added a UV_STACK_SIZE variable to bypass this problem during testing. We recommend bumping the stack size from the default of 1MB to 2MB, for example:

$Env:UV_STACK_SIZE = '2000000'

Running inside a Docker container

Source distributions can run arbitrary code on build and can make unwanted modifications to your system ("Someone's Been Messing With My Subnormals!" on Blogspot, "nvidia-pyindex" on PyPI), which can even occur when just resolving requirements. To prevent this, there's a Docker container you can run commands in:

docker buildx build -t uv-builder -f builder.dockerfile --load .
# Build for musl to avoid glibc errors, might not be required with your OS version
cargo build --target x86_64-unknown-linux-musl --profile profiling
docker run --rm -it -v $(pwd):/app uv-builder /app/target/x86_64-unknown-linux-musl/profiling/uv-dev resolve-many --cache-dir /app/cache-docker /app/scripts/popular_packages/pypi_10k_most_dependents.txt

We recommend using this container if you don't trust the dependency tree of the package(s) you are trying to resolve or install.

Profiling and Benchmarking

Please refer to Ruff's Profiling Guide, it applies to uv, too.

We provide diverse sets of requirements for testing and benchmarking the resolver in scripts/requirements and for the installer in scripts/requirements/compiled.

You can use scripts/benchmark to benchmark predefined workloads between uv versions and with other tools, e.g., from the scripts/benchmark directory:

uv run resolver \
    --uv-pip \
    --poetry \
    --benchmark \
    resolve-cold \
    ../scripts/requirements/trio.in

Analyzing concurrency

You can use tracing-durations-export to visualize parallel requests and find any spots where uv is CPU-bound. Example usage, with uv and uv-dev respectively:

RUST_LOG=uv=info TRACING_DURATIONS_FILE=target/traces/jupyter.ndjson cargo run --features tracing-durations-export --profile profiling -- pip compile scripts/requirements/jupyter.in
RUST_LOG=uv=info TRACING_DURATIONS_FILE=target/traces/jupyter.ndjson cargo run --features tracing-durations-export --bin uv-dev --profile profiling -- resolve jupyter

Trace-level logging

You can enable trace level logging using the RUST_LOG environment variable, i.e.

RUST_LOG=trace uv

Documentation

To preview any changes to the documentation locally:

  1. Install the Rust toolchain.

  2. Run cargo dev generate-all, to update any auto-generated documentation.

  3. Install MkDocs and Material for MkDocs with:

    uv venv

# For contributors.
uv pip install -r docs/requirements.txt

# Or, for members of the Astral org, which has access to MkDocs Insiders via sponsorship.
uv pip install -r docs/requirements-insiders.txt

  4. Activate the virtual environment with:

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

# On Windows.
.venv\Scripts\activate

  5. Run the development server with:

    # For contributors.
mkdocs serve -f mkdocs.public.yml

# For members of the Astral org, which has access to MkDocs Insiders via sponsorship.
mkdocs serve -f mkdocs.insiders.yml

The documentation should then be available locally at http://127.0.0.1:8000/uv/.

To update the documentation dependencies, edit docs/requirements.in and docs/requirements-insiders.in, then run:

uv pip compile docs/requirements.in -o docs/requirements.txt --universal -p 3.12
uv pip compile docs/requirements-insiders.in -o docs/requirements-insiders.txt --universal -p 3.12

Documentation is deployed automatically on release by publishing to the Astral documentation repository, which itself deploys via Cloudflare Pages.

Releases

Releases can only be performed by Astral team members.

Changelog entries and version bumps are automated. First, run:

./scripts/release.sh

Then, editorialize the CHANGELOG.md file to ensure entries are consistently styled.

Then, open a pull request e.g. Bump version to ....

Binary builds will automatically be tested for the release.

After merging the pull request, run the release workflow with the version tag. Do not include a leading v. The release will automatically be created on GitHub after everything else publishes.