mirror of
https://github.com/astral-sh/uv
synced 2026-01-22 14:00:11 -05:00
f487b2e8c1
* Document good first issues * Document `scripts` directory, as far as useful for contributors * Remove compare with pip script, we don't need it anymore I think this closes #817. --------- Co-authored-by: Jo <10510431+j178@users.noreply.github.com>
135 lines
4.7 KiB
Markdown
135 lines
4.7 KiB
Markdown
# Contributing
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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.
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## Setup
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[Rust](https://rustup.rs/), a C compiler, and CMake are required to build uv.
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### Linux
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On Ubuntu and other Debian-based distributions, you can install the C compiler and CMake with
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```shell
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sudo apt install build-essential cmake
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```
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### macOS
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CMake may be installed with Homebrew:
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```shell
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brew install cmake
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```
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The Python bootstrapping script requires `coreutils` and `zstd`; we recommend installing them with Homebrew:
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```shell
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brew install coreutils zstd
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```
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See the [Python](#python) section for instructions on installing the Python versions.
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### Windows
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You can install CMake from the [installers](https://cmake.org/download/) or with `pipx install cmake`
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(make sure that the pipx install path is in `PATH`, pipx complains if it isn't).
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## Testing
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For running tests, we recommend [nextest](https://nexte.st/).
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### Python
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Testing uv requires multiple specific Python versions. You can install them into
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`<project root>/bin` via our bootstrapping script:
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```shell
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pipx run scripts/bootstrap/install.py
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```
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Alternatively, you can install `zstandard` from PyPI, then run:
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```shell
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python3.12 scripts/bootstrap/install.py
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```
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You can configure the bootstrapping directory with `UV_BOOTSTRAP_DIR`.
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### Local testing
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You can invoke your development version of uv with `cargo run -- <args>`. For example:
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```shell
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cargo run -- venv
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cargo run -- pip install requests
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```
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## Running inside a docker container
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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:
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```bash
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docker buildx build -t uv-builder -f builder.dockerfile --load .
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# Build for musl to avoid glibc errors, might not be required with your OS version
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cargo build --target x86_64-unknown-linux-musl --profile profiling --features vendored-openssl
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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
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```
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We recommend using this container if you don't trust the dependency tree of the package(s) you are trying to resolve or install.
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## Profiling and Benchmarking
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Please refer to Ruff's [Profiling Guide](https://github.com/astral-sh/ruff/blob/main/CONTRIBUTING.md#profiling-projects), it applies to uv, too.
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We provide diverse sets of requirements for testing and benchmarking the resolver in `scripts/requirements` and for the installer in `scripts/requirements/compiled`.
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You can use `scripts/bench` to benchmark predefined workloads between uv versions and with other tools, e.g.
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```
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python -m scripts.bench \
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--uv-path ./target/release/before \
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--uv-path ./target/release/after \
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./scripts/requirements/jupyter.in --benchmark resolve-cold --min-runs 20
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```
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### Analysing concurrency
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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:
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```shell
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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
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```
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```shell
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RUST_LOG=uv=info TRACING_DURATIONS_FILE=target/traces/jupyter.ndjson cargo run --features tracing-durations-export --bin uv-dev --profile profiling -- resolve jupyter
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```
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### Trace-level logging
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You can enable `trace` level logging using the `RUST_LOG` environment variable, i.e.
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```shell
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RUST_LOG=trace uv …
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```
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## Releases
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Releases can only be performed by Astral team members.
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Changelog entries and version bumps are automated. First, run:
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```
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./scripts/release/bump.sh
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```
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Then, editorialize the `CHANGELOG.md` file to ensure entries are consistently styled.
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Then, open a pull request e.g. `Bump version to ...`.
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Binary builds will automatically be tested for the release.
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After merging the pull request, run the [release workflow](https://github.com/astral-sh/uv/actions/workflows/release.yml)
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with the version tag. **Do not include a leading `v`**.
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The release will automatically be created on GitHub after everything else publishes.
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