# Contributing

We have issues labeled as
[Good First Issue](https://github.com/astral-sh/uv/issues?q=is%3Aopen+is%3Aissue+label%3A%22good+first+issue%22)
and
[Help Wanted](https://github.com/astral-sh/uv/issues?q=is%3Aopen+is%3Aissue+label%3A%22help+wanted%22)
which are good opportunities for new contributors.

## Setup

[Rust](https://rustup.rs/), 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:

```shell
sudo apt install build-essential cmake
```

### macOS

You can install CMake with Homebrew:

```shell
brew install cmake
```

See the [Python](#python) section for instructions on installing the Python versions.

### Windows

You can install CMake from the [installers](https://cmake.org/download/) or with
`pipx install cmake`.

## Testing

For running tests, we recommend [nextest](https://nexte.st/).

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:

```shell
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:

```shell
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](https://github.com/astral-sh/uv/pull/941) to bypass this problem
during testing. We recommend bumping the stack size from the default of 1MB to 2MB, for example:

```powershell
$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](https://moyix.blogspot.com/2022/09/someones-been-messing-with-my-subnormals.html),
["nvidia-pyindex" on PyPI](https://pypi.org/project/nvidia-pyindex/)), which can even occur when
just resolving requirements. To prevent this, there's a Docker container you can run commands in:

```console
$ 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](https://github.com/astral-sh/ruff/blob/main/CONTRIBUTING.md#profiling-projects),
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:

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

### Analyzing concurrency

You can use [tracing-durations-export](https://github.com/konstin/tracing-durations-export) to
visualize parallel requests and find any spots where uv is CPU-bound. Example usage, with `uv` and
`uv-dev` respectively:

```shell
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
```

```shell
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.

```shell
RUST_LOG=trace uv
```

## Documentation

To preview any changes to the documentation locally:

1. Install the [Rust toolchain](https://www.rust-lang.org/tools/install).

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

3. Run the development server with:

   ```shell
   # For contributors.
   uvx --with-requirements docs/requirements.txt -- mkdocs serve -f mkdocs.public.yml

   # For members of the Astral org, which has access to MkDocs Insiders via sponsorship.
   uvx --with-requirements docs/requirements-insiders.txt -- mkdocs serve -f mkdocs.insiders.yml
   ```

The documentation should then be available locally at
[http://127.0.0.1:8000/uv/](http://127.0.0.1:8000/uv/).

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

```shell
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](https://github.com/astral-sh/docs) repository, which itself deploys via
Cloudflare Pages.

After making changes to the documentation, format the markdown files with:

```shell
npx prettier --prose-wrap always --write "**/*.md"
```

## 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](https://github.com/astral-sh/uv/actions/workflows/release.yml) with the version
tag. **Do not include a leading `v`**. The release will automatically be created on GitHub after
everything else publishes.
