This includes some initial work on adding Pyodide support (issue
#12729). It is enough to get
```
uv pip compile -p /path/to/pyodide --extra-index-url file:/path/to/simple-index
```
to work which should already be quite useful.
## Test Plan
* added a unit test for `pyodide_platform`
* integration tested manually with:
```
cargo run pip install \
-p /home/rchatham/Documents/programming/tmp/pyodide-venv-test/.pyodide-xbuildenv-0.29.3/0.27.4/xbuildenv/pyodide-root/dist/python \
--extra-index-url file:/home/rchatham/Documents/programming/tmp/pyodide-venv-test/.pyodide-xbuildenv-0.29.3/0.27.4/xbuildenv/pyodide-root/package_index \
--index-strategy unsafe-best-match --target blah --no-build \
numpy pydantic
```
---------
Co-authored-by: konsti <konstin@mailbox.org>
Co-authored-by: Zanie Blue <contact@zanie.dev>
## Summary
If you use `--torch-backend=auto`, we want to avoid selecting (e.g.) a
`+cu124` build of `torch` alongside a `+cu126` build of `torchvision`.
## Summary
It's possible that the PyTorch version the user depends on isn't in the
latest index. These indexes are equally trusted, so we should override
the policy.
Closes#12357.
## Summary
This is a prototype that I'm considering shipping under `--preview`,
based on [`light-the-torch`](https://github.com/pmeier/light-the-torch).
`light-the-torch` patches pip to pull PyTorch packages from the PyTorch
indexes automatically. And, in particular, `light-the-torch` will query
the installed CUDA drivers to determine which indexes are compatible
with your system.
This PR implements equivalent behavior under `--torch-backend auto`,
though you can also set `--torch-backend cpu`, etc. for convenience.
When enabled, the registry client will fetch from the appropriate
PyTorch index when it sees a package from the PyTorch ecosystem (and
ignore any other configured indexes, _unless_ the package is explicitly
pinned to a different index).
Right now, this is only implemented in the `uv pip` CLI, since it
doesn't quite fit into the lockfile APIs given that it relies on feature
detection on the currently-running machine.
## Test Plan
On macOS, you can test this with (e.g.):
```shell
UV_TORCH_BACKEND=auto UV_CUDA_DRIVER_VERSION=450.80.2 cargo run \
pip install torch --python-platform linux --python-version 3.12
```
On a GPU-enabled EC2 machine:
```shell
ubuntu@ip-172-31-47-149:~/uv$ UV_TORCH_BACKEND=auto cargo run pip install torch -v
Finished `dev` profile [unoptimized + debuginfo] target(s) in 0.31s
Running `target/debug/uv pip install torch -v`
DEBUG uv 0.6.6 (e95ca063b 2025-03-14)
DEBUG Searching for default Python interpreter in virtual environments
DEBUG Found `cpython-3.13.0-linux-x86_64-gnu` at `/home/ubuntu/uv/.venv/bin/python3` (virtual environment)
DEBUG Using Python 3.13.0 environment at: .venv
DEBUG Acquired lock for `.venv`
DEBUG At least one requirement is not satisfied: torch
warning: The `--torch-backend` setting is experimental and may change without warning. Pass `--preview` to disable this warning.
DEBUG Detected CUDA driver version from `/sys/module/nvidia/version`: 550.144.3
...
```
Charlie Marsh
Hood Chatham