pip-build-standalone

Use uv to build a pip within a standalone Python installation


License
MIT
Install
pip install pip-build-standalone==0.1.3

Documentation

py-app-standalone

py-app-standalone builds a standalone, relocatable Python installation with a set of packages included. It's like a modern alternative to PyInstaller that leverages the newer uv ecosystem.

It's a wrapper around uv that creates a standalone Python installation, runs uv pip install, and then makes the required platform-specific changes so you have a fully self-contained install directory (packagable and runnable from any directory on a machine of the same platform).

Background

Typically, Python installations are not relocatable or transferable between machines, even if they are on the same platform, because often there are variable, dynamic library dependencies oand because scripts and libraries contain absolute file paths (i.e., many scripts or libs include absolute paths that reference your home folder or system paths on your machine).

Now Gregory Szorc and Astral solved a lot of the challenge with standalone Python distributions, which handles static linking and various other issues—see the technical notes. uv also supports relocatable venvs, so it's possible to move a venv. But at least currently, the actual Python installations created by uv can still have absolute paths inside them in the dynamic libraries or scripts, as discussed in this issue.

This tool is my quick attempt at fixing this, so you basically are using uv but have a fully self-contained installation, with your chosen version of Python and any packages you wish.

The idea is this pre-built binary package can then be used on any machine of a given platform withou any external dependencies, not even Python or uv. And the the directory is relocatable. So you could for example put it inside a desktop app.

This should work for any platform. You just need to build on the same platform you want to run on.

Warning: Experimental! This is a new tool. I've used it on macOS and it's very lightly tested on Ubuntu and Windows, but obviously there are many possibilities for subtle incompatibilities within a given platform.

Alternatives

PyInstaller is the classic solution for this and has a lot of features beyond this little tool, but is far more complex and does not build on uv.

shiv and pex are mature options that focus on zipping up your app, but not the Python installation.

PyApp is a more recent effort on top of uv that creates a Rust-built standalone binary that downloads/installs Python and dependencies at runtime.

Usage

Requires uv to run. Do a uv self update to make sure you have a recent uv (I'm currently testing on v0.6.14).

Then:

uvx py-app-standalone --help
uvx py-app-standalone cowsay  # whatever packages you wish

As an example, let's create a full standalone Python 3.13 environment with the cowsay package.

After this is done, the ./py-standalone directory will work without being tied to a specific machine, your home folder, or any other system-specific paths. Binaries can now be put wherever and run:

$ uvx py-app-standalone cowsay
Creating a new Python installation at: py-standalone

▶ uv python install --managed-python --install-dir /Users/levy/wrk/github/py-app-standalone/py-standalone 3.13
Installed Python 3.13.3 in 2.78s
 + cpython-3.13.3-macos-aarch64-none
⏱ Call to run took 2.80s

Creating temporary venv (you can ignore this step. It is just a trick to get a uv pyvenv.cfg file)...

▶ uv venv --relocatable --python py-standalone/cpython-3.13.3-macos-aarch64-none py-standalone/bare-venv
Using CPython 3.13.3 interpreter at: py-standalone/cpython-3.13.3-macos-aarch64-none/bin/python3
Creating virtual environment at: py-standalone/bare-venv
Activate with: source py-standalone/bare-venv/bin/activate
⏱ Call to run took 628ms

Temporary venv config: py-standalone/cpython-3.13.3-macos-aarch64-none/pyvenv.cfg
Now installing packages directly into the original installation: py-standalone/cpython-3.13.3-macos-aarch64-none

▶ uv pip install cowsay --python py-standalone/cpython-3.13.3-macos-aarch64-none --break-system-packages
Using Python 3.13.3 environment at: py-standalone/cpython-3.13.3-macos-aarch64-none
Resolved 1 package in 39ms
Installed 1 package in 7ms
 + cowsay==6.1
⏱ Call to run took 59.77ms

macOS: Updating dylib ids to be relocatable...
Found macos dylib, will update its id to remove any absolute paths: py-standalone/cpython-3.13.3-macos-aarch64-none/lib/libpython3.13.dylib

▶ install_name_tool -id @executable_path/../lib/libpython3.13.dylib py-standalone/cpython-3.13.3-macos-aarch64-none/lib/libpython3.13.dylib
⏱ Call to run took 38.14ms

Making sure all the scripts are relocatable...
Inserting relocatable shebangs on scripts in:
    py-standalone/cpython-3.13.3-macos-aarch64-none/bin/*
Replaced shebang in: py-standalone/cpython-3.13.3-macos-aarch64-none/bin/cowsay
...
Replaced shebang in: py-standalone/cpython-3.13.3-macos-aarch64-none/bin/pydoc3
Replacing remaining absolute paths...

Replacing all absolute paths in:
    py-standalone/cpython-3.13.3-macos-aarch64-none/bin/* py-standalone/cpython-3.13.3-macos-aarch64-none/lib/**/*.py:
    `/Users/levy/wrk/github/py-app-standalone/py-standalone` -> `py-standalone`
Replaced 27 occurrences in: py-standalone/cpython-3.13.3-macos-aarch64-none/lib/python3.13/_sysconfigdata__darwin_darwin.py
Replaced 27 total occurrences in 1 files total
Compiling all python files in: py-standalone...
Sanity checking if any absolute paths remain (including in binary files)...
Great! No absolute paths found in the installed files.

✔ Success: Created standalone Python environment for packages ['cowsay'] at: py-standalone

$ ./py-standalone/cpython-3.13.3-macos-aarch64-none/bin/cowsay -t 'im moobile'
  __________
| im moobile |
  ==========
          \
           \
             ^__^
             (oo)\_______
             (__)\       )\/\
                 ||----w |
                 ||     ||

$ # Now let's confirm it runs in a different location!
$ mv ./py-standalone /tmp

$ /tmp/py-standalone/cpython-3.13.3-macos-aarch64-none/bin/cowsay -t 'udderly moobile'
  _______________
| udderly moobile |
  ===============
               \
                \
                  ^__^
                  (oo)\_______
                  (__)\       )\/\
                      ||----w |
                      ||     ||

$

How it Works

It creates true (not venv) Python installation with the given packages installed, with zero absolute paths encoded in any of the Python scripts or libraries.

It does this by:

  • Installing a new standalone/relocatable Python installation with uv

  • Ensuring all scripts in bin/ have relocatable shebangs (normally they are absolute)

  • Cleaning up a few other places source directories are baked into text files (like the sysconfigdata .py file)

  • On macOS, fixing the hard-coded absolute path inside the Python .dylib file to be relative using install_name_tool and its @executable_path var. (On Linux and Windows something like this doesn't seem to be necessary.)

It seems to work. So in theory, the resulting binary folder should be installable as at any location on a machine with compatible architecture.

More Notes

  • I've only tested this with PyPI packages but it should work for any package name that works with uv pip (so should work with private packages/indexes that work with uv).

  • The good thing is this does work to encapsulate binary builds and libraries, as long as the binaries are included in the package. It doesn't address the problem of external dependencies that traditionally need to be installed outside the Python ecosystem (like ffmpeg). (For this, pixi seems promising.)

  • This by default pre-compiles all files to create __pycache__ .pyc files. This means the build should start faster and could run on a read-only filesystem. Use --source-only to have a source-only build.

FAQ

  • Hasn't this been solved before? Yes, by PyInstaller and other tools (see above). But not as far as I know with the modern uv ecosystem, which has a lot of advantages over legacy Python tooling. The fact that this is so much simpler than PyInstaller arguably shows that a lot of heavy lifting is being done by uv tooling.

  • Why not just use Docker? If you can, you probably should! But there are lots of situations, such as in building apps for end-users on macOS and Windows, where Docker is too heavyweight a solution. And there are situations where you still want a single, portable package or distribution that doesn't require runtime installs.


This project was built from simple-modern-uv.