Add `-t/--target` flag for `uv pip install`

[imdoroshenko]

This option is used a lot for vendoring and for custom build systems.

From pip install --help:

  -t, --target <dir>          Install packages into <dir>. By
                              default this will not replace
                              existing files/folders in <dir>. Use
                              --upgrade to replace existing
                              packages in <dir> with new versions.

[pfmoore]

I'd recommend not following pip's design here, as --target has some undesirable behaviours (it doesn't properly support uninstalls and upgrades, for example, even though the docs suggest it's OK). The use case is important to support, but I'd design a solution from scratch rather than simply taking pip's approach.

In particular, pip's choice of where to put binaries, scripts and include files is essentially arbitrary and may not be the best approach.

[^1]: I should say that it may be that uv can cleanly support uninstalls and upgrades, and that the weirdness in pip is because of how pip works internally.

[rgilton]

I'd like to add that a key application of this is to enable the building of standalone zipapps that contain all of their dependencies. I have some workflows that use pip at the moment for this, and they would be massively accelerated if uv supported -t.

[jcollingj]

Added a thumbs up. I am also currently using -t from pip and would love to use uv for that use case instead!

[imdoroshenko]

I'd recommend not following pip's design here, as --target has some undesirable behaviours (it doesn't properly support uninstalls and upgrades, for example, even though the docs suggest it's OK). The use case is important to support, but I'd design a solution from scratch rather than simply taking pip's approach.

In particular, pip's choice of where to put binaries, scripts and include files is essentially arbitrary and may not be the best approach.

As mentioned by other people, -t is mainly used in a very controlled way that does not expect uninstalls or upgrades. Like in vendoring tools (example) and build systems for Zip Apps. Or, In my case, for an in-house build system.

Creating another solution from scratch is OK, but then UV should call itself "Opinionated replacement for pip" rather than drop-in replacement.

[pfmoore]

As mentioned by other people, -t is mainly used in a very controlled way that does not expect uninstalls or upgrades.

That doesn't match with our experience on pip, where we have had a number of requests for better support for upgrades, etc. Another issue is https://github.com/pypa/pip/issues/10110, which seems to revolve around people incrementally adding to a directory populated using -t.

But if uv is willing to only support the case where the directory specified in -t is empty, then yes, this is fine.

but then UV should call itself "Opinionated replacement for pip" rather than drop-in replacement.

I don't think uv is a "drop in replacement" for pip, nor should it try to be one. It should aim to be the best installer it can, and not be constrained by pip's legacy behaviours.

[shayanhoshyari]

I also heavily use this feature to make stand alone envs. In my use case they are used to bootstrap workers in a cloud service. I too am only costumer of this use case the directory specified in -t is empty.

Other past alternatives were conda pack and embedding in container which were both even slower than pip!

Now desperately looking at this issue to see when I can reduce our 40 min env packing time when everything changes (there are various envs for various workers) to minutes or perhaps seconds :)

For context, we already started using uv for our dev env pip sync (which does not need -t support), and it went from 6 min to 16 sec. pip compile time went from 2-3 min to a few secs! ❤️

[matthew-chambers-pushly]

We utilize pip's -t | --target to vendor packages for Lambda@EDGE deployments, it would be nice to have this supported as an option, or to have some way of programmatically copying the packages from the cache without needing to script it ourselves.

[Tankanow]

I second @matthew-chambers-pushly, @shayanhoshyari, et al. We do something similar to package for AWS Lambda.

I think the general use case is:

I would like to use uv outside a virtual environment to install dependencies into a directory consumable by common Python runtimes. This can be vendored format or otherwise, though vendored format may be useful for backwards compatibility.

Essentially what I want is something equivalent to this script:

function uv.target(){
  local target=${1?} ; shift
  local args=("$@")
  uv venv
  # shellcheck source=/dev/null
  source ".venv/bin/activate"
  uv pip install "${args[@]}"
  rm -rf "${target}" || true
  mkdir -p "${target}/"
  cp -r .venv/bin "${target}/"
  cp -r .venv/lib/python3.*/site-packages/* "${target}/"
  deactivate || true
  rm -rf .venv
}

[mpderbec]

But if uv is willing to only support the case where the directory specified in -t is empty, then yes, this is fine.

FWIW, this matches our use case: The directory is empty. (Largely because of all the limitations described above regarding upgrade/uninstall.)

[henryiii]

This is the recipe for zip apps:

$ mkdir tmp
$ pip install --no-compile --target=tmp . dep_1 dep_2
$ cd tmpdir
$ python -m zipapp --compress --python=/usr/bin/env python3 --main=myapp.__main__:main --output=../myapp.pyz

Would be quite happy in this case to have the extra dirs (like bin) simply ignored, since they won't show up in the zipapp.

[acatalucci-synth]

without --prefix or --target it's really challenging to build multi stage images, my use case is copying packages to the final image. is there any workaround, waiting for any of these mechanisms to be supported?

[pfmoore]

is there any workaround

It depends how careful you want to be. If you don't mind being somewhat imprecise, the script from the comment above looks reasonable. It's Unix-specific and would need some tweaking for Windows because the lib directory on Windows is structured differently. But it's likely good enough for most use cases.

If you want to handle wheels that have both purelib and platlib sections, on a target system where purelib != platlib, you might need some extra complexity. If you want to install other sections of the wheel, like headers, scripts or data, or you want to handle script wrappers (usually placed outside of the lib directory), then you'll need to do some more work. But these are the sorts of complicated questions that are part of the reason that (a) this isn't a simple feature to add, and (b) I'm advising the uv developers not to blindly follow what pip does (because I'm not sure pip gets the answers to these questions right...)

[acatalucci-synth]

Thanks for the extensive and fast answer! I'm basically trying to understand best practice for docker multi stage builds and uv, the script above won't quite do it as i cannot activate virtualenvs straight from dockerfiles. So far the only thing i managed to get working is:

FROM public.ecr.aws/docker/library/python:3.10-slim-bullseye AS build_artifacts
RUN pip install uv
RUN mkdir /workspace
RUN chown 1000 /workspace
WORKDIR /workspace
USER 1000
RUN uv venv
ENV PATH="/workspace/.venv/bin:$PATH"
COPY setup.py /workspace/
RUN uv pip install --no-cache-dir --quiet .

FROM public.ecr.aws/docker/library/python:3.10-slim-bullseye
RUN mkdir /workspace
RUN chown 1000 /workspace
WORKDIR /workspace
USER 1000
RUN mkdir /workspace/.venv
COPY --from=build_artifacts /workspace/.venv /workspace/.venv
ENV PATH="/workspace/.venv/bin:$PATH"
RUN python app.py

is this the recommended way of doing it? are there any caveats I might stumble onto? i've tried multiple avenues but the lack of support for both --user and --target closed off all the alternatives i could think about

[pfmoore]

I can't speak for uv, but my feeling is that there's no "recommended" way. If you want --target support, you can

1. Use pip, and live with the fact that it's slower.
2. Wait for uv to implement --target, which I'm sure won't be that far off given the pace of development here 🙂
3. Work out some sort of solution that does what you want for now, and accept that it's clumsy and might break in edge cases.

I'm not able to comment on your solution, as I don't really know what "i cannot activate virtualenvs straight from dockerfiles" means. ENV PATH="/workspace/.venv/bin:$PATH" is pretty much all you need to activate a virtual environment anyway, and you could even just do RUN /workspace/.venv/bin/python app.py. Activation is only a command line convenience, after all...

[acatalucci-synth]

i meant that i cannot source the activate script and that's why i do that ENV-setting. From your answer i understand that this should do it for now (which apparently isn't going to be long! 👍 )

[tonnico]

You do not need to source the script. You can do export VIRTUAL_ENV=.venv to have something similar.

[konstin]

I second RUN /workspace/.venv/bin/python app.py, this also ensures that all subprocess calls have the correct python environment. @acatalucci-synth As for general docker+python best practices, your dockerfile looks great.

[acatalucci-synth]

thanks for the suggestions and compliments for the Dockerfile! I'll be waiting for --target support 👍

[Pixel-Minions]

Hi,

I am bringing a thumbs up for a target or equivalent workflow here. In my company we store independently each package, because we have a different package resolver. I am loving UV and I hope a workflow to offer freedom could be present in the roadmap.

[charliermarsh]

I'm tempted to treat --target as, roughly, the root of a virtual environment, rather than its site-packages directory. I think that would lead to logical and consistent locations for binaries, purelib vs. platlib, etc.

[pfmoore]

That’s more like pip’s --root option. In my experience (and for my use cases) the key benefit of --target is that the directory specified is the one that is put directly on sys.path. The --root option (and it’s similar but subtly different partner --prefix) is far less commonly used than --target.

With your proposal I would need to:

1. Install to a temporary target.
2. Locate the site-packages (which is in an OS and interpreter dependent location).
3. Move that site-packages to my final target.

This is basically what pip does internally to implement --target. (And is why anything beyond “install to an empty target directory” is incompletely supported).

[Scrat94]

@charliermarsh I would also like to share our use case and why your tempted approach might not be suitable for us.

For AWS Lambda Functions you need to bundle dependencies locally or in CI. For example if you need the requests library as part of your AWS Lambda Python Function, you need to install requests inside your Lambda Function Folder besides having it already in your .venv on root directory. That leads to the requirement of calling pip install -r "path-to-aws-function/requirements.txt" --target "path-to-aws-function".

We mainly use the --target in our CI to install the respective dependencies for the Lambda Function and deploy it to AWS. So locally we completely switched to UV already, but in our CI we rely on a hybrid approach right now (uv used to install all dependencies in order to run e.g. pytest and pip for installing dependencies in the target AWS Lambda Functions folder for deployment).

So its the last puzzle for us to get completely rid of pip. Big thanks to your effort, UV is already amazing and a productivity booster!

[charliermarsh]

@pfmoore - is there anywhere that I can read about the differences between --prefix and --root, and what use-cases they're intended to support?

[pfmoore]

Nothing much that I know of beyond the bare pip help information here. They both come from the original distutils install schemes, as far as I know. There's some discussion of the --prefix scheme in the old distutils docs, here. The --root option was in setuptools, but as the command line interface is deprecated, I couldn't find any documentation that said anything more than what pip install --help has.

From my understanding, --prefix is important for redistributors creating a standalone installation in a "fake root". Things like RPM builds use this, I think. It's possible --root is used in that situation as well. To my knowledge, neither is commonly used by end users, whereas --target is very commonly used by end users, for vendoring dependencies, creating library directories for deployment in situations like webapps or serverless environments, building embedded Python environments, etc.

My view is that --target is by far the most important case to support, and the key aspect of --target is installing all importable parts of a package (purelib and platlib) into the specified directory directly. I don't think installing scripts or headers is commonly needed, and while wheels can contain arbitrary data files, I think most packages these days put their runtime data in the package structure and use importlib.resources to access it.

This is why I'd suggest that you start with a minimal approach that targets[^1] the known use cases, and extend it based on user feedback. So, for me, I'd go with:

1. Install the purelib and platlib sections of the wheel to the target directory.
2. Require the target to be empty before the install (you can create the target directory if it doesn't exist, but you should support an existing, but empty, directory).
3. Don't support upgrades, uninstalls, or any other supporting features. No need for list, show, sync, or any other subcommands to grow a --target option.
4. If you want to, install scripts/entry point wrappers to a bin directory in the target. That's purely for pip compatibility. I don't think it's needed, and the binaries almost certainly won't actually work, but it may make people a little more comfortable as they expect that from pip. But I'd personally prefer it if you took a stand and said these aren't needed or supported, so you won't include them.

To be honest, just implementing that shouldn't be too difficult. The hardest part would probably be integrating it into the code, as it's nothing like a "normal" install[^2].

[^1]: Excuse the pun 🙂 [^2]: My long term idea for pip was to replace all of --root, --prefix, --target with a very generalised approach that let the user specify exactly what to do with each of the different subtrees in the wheel (see the "Spread" part of the spec here). Then maybe add back the existing options as convenience wrappers over that. But there are so many special cases in the existing pip codebase that it may not ever be practical. You might be able to do something like that in uv, because you don't have all the historical baggage that pip does, but I haven't looked at that part of the uv code, so I don't know.

[acatalucci-synth]

thanks, that sounds great! on 4 i'd recommend to still copy binaries. One example is "ddtrace", it does include a binary that one is supposed to call to wrap the python app to add telemetry - with my approach above that seems to work.

[charliermarsh]

Related to binaries, it looks like pip's --target will put anything in the data dir at the top-level (e.g., the notebook package has ../../share/jupyter/lab/schemas/@jupyter-notebook/application-extension/menus.json1 and friends, and those just end up at <target>/share/...).

[pfmoore]

Related to binaries, it looks like pip's --target will put anything in the data dir at the top-level

Correct. But I don't know if that is right or helpful, which is why I suggest not doing so until there's feedback from real use cases that confirms it works and is needed.

For example, I have no idea how Jupyter notebook could correctly find that path in a vendored situation - a brief search suggests that jupyterlab_widgets\__init__.py assumes the share directory will be located in sys.prefix, which simply won't be true in a vendored situation (or any situation I know of where --target would be appropriate).

[pfmoore]

Thinking further about binaries, and in particular script wrappers, I don't even see how those can work in the general case. Assuming uv works like pip, when it generates a script wrapper it hard codes the absolute path of the Python interpreter used to do the install. But in all of the key use cases for --target, that interpreter probably won't even be present at runtime:

• Building a deployment for a cloud provider - the cloud provider's Python interpreter will probably be in a different location.
• Vendoring dependencies to build a zipapp or a standalone application - the app will be distributed to users who won't necessarily have the interpreter in the same place as the maintainer (in the case of a standalone app, the user may not even have a standalone Python interpreter).
• Populating a library directory for an embedded interpreter - the embedded interpreter may well not be invokable as a standalone process.

So I'm unclear why there's any value in installing script wrappers, let alone worrying about where to save them.

By the way, I'm aware that all of these points apply equally to pip - the main constraint with pip is that even if there's clearly no use for these things, if we remove them, there's bound to be someone whose workflow will break - https://xkcd.com/1172/. But as a new application, uv doesn't need to worry about that (unless you insist on being bug-for-bug compatible with pip, which is obviously your prerogative, but I don't think is warranted in this case...)

[charliermarsh]

(By the way: I'm learning a lot from your comments and really appreciate you taking the time to provide input here. Thank you.)

[Tankanow]

This has been a lovely thread filled with informative helpful people. Kudos to @pfmoore, @charliermarsh, and the rest of the pip and uv teams actively helping out here. ❤️