venvstacks 0.1.0rc1

Use layered Python virtual environment stacks to share large dependencies

Layered Virtual Environment Stacks for Python

The venvstacks project uses Python's sitecustomize.py environment setup feature to chain together three layers of Python virtual environments:

• "Runtime" layers: environment containing the desired version of a specific Python runtime
• "Framework" layers: environments containing desired versions of key Python frameworks
• "Application" layers: environments containing components to be launched directly

Application layer environments may include additional unpackaged Python launch modules or packages for invocation with python's -m switch.

This project does NOT support combining arbitrary virtual environments with each other. Instead, it allows larger integrated applications to split up their Python dependencies into distinct layers, without needing to download and install multiple copies of large dependencies (such as the pytorch ML/AI framework). The environment stack specification and build process helps ensure that shared dependencies are kept consistent across layers, while unshared dependencies are free to vary across the application components that need them.

As an example, the main sample project used in the test suite defines the following layers:

• cpython@3.11: CPython 3.11 base runtime
• cpython@3.12: CPython 3.12 base runtime
• framework-scipy: example framework layer (based on 3.11 runtime)
• framework-sklearn example framework layer (based on 3.12 runtime)
• framework-http-client: example framework layer (based on 3.11 runtime)
• app-scipy-import: example app layer with a single framework and a simple launch module
• app-scipy-client: example app layer with two frameworks and a multi-file launch package
• app-sklearn-import: example of defining a platform specific app layer

Refer to tests\sample_project\venvstacks.toml for the full definition of this example.

To avoid relying on the Python ecosystem's still limited support for cross-platform component installation, the stack build processes need to be executed on the target platform (for example, by using an OS matrix in GitHub Actions).

Interactions with other packaging tools

The base runtime environment layers are installed with pdm (with the installed runtimes coming from the python-build-standalone project). pdm is also used to manage the development of the venvstacks project itself.

The layered framework and app environments are created with the standard library's venv module.

The Python packages in each layer are currently being installed directly with pip, but are expected to eventually move to being installed with uv to reduce environment setup times during builds.

Platform-specific environment locking for each layer is performed using uv pip compile. Refer to pyproject.toml for the specific issues preventing the adoption of uv for additional purposes.

venvstacks expects precompiled wheel archives to be available for all included Python distribution packages. When this is not the case, other projects like wagon or fromager may be useful in generating the required input archives.

Caveats and Limitations

• the venvstacks Python API is not yet stable. Any interface not specifically declared as stable in the documentation may be renamed or relocated without a deprecation period. API stabilisation (mostly splitting up the overly large venvstacks.stacks namespace) will be the trigger for the 1.0 milestone release.
• while the venvstacks CLI is broadly stable, there are still some specific areas where changes may occur (such as in the handling of relative paths).
• dynamic library dependencies across layers currently only work on Windows. There is a proposal in place for resolving that limitation, but it has not yet been implemented.
• local exports to filesystems which do not support symlinks (such as VFAT and FAT32) are nominally supported (with symlinks being replaced by the files they refer to), but this support is not currently tested.

Project History

The initial (and ongoing) development of the venvstacks project is being funded by LM Studio, where it serves as the foundation of LM Studio's support for local execution of Python AI frameworks such as Apple's MLX.

The use of "🐸" (frog) and "🦎" (newts are often mistaken for lizards and vice-versa!) as the Unicode support test characters is a reference to the internal LM Studio project that initially built and continues to maintain venvstacks: Project Amphibian.