Installation¶

aigverse wraps mature C/C++ synthesis backends from the EPFL Logic Synthesis Libraries with an idiomatic Python interface for Python-first workflows. Optional adapters extend this core with graph and array interoperability for downstream ML and data science pipelines. The resulting Python package is available on PyPI and can be installed on all major operating systems and all active Python versions.

Tip

We highly recommend using uv for working with Python projects. It is an extremely fast Python package and project manager, written in Rust and developed by Astral (the same team behind ruff). It can act as a drop-in replacement for pip and virtualenv, and provides a more modern and faster alternative to the traditional Python package management tools. It automatically handles the creation of virtual environments and the installation of packages, and is much faster than pip. Additionally, it can even set up Python for you if it is not installed yet.

If you do not have uv installed yet, you can install it via:

macOS and Linux

$ curl -LsSf https://astral.sh/uv/install.sh | sh

Windows

$ powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"

Check out their excellent documentation for more information.

Core Library¶

To install the core aigverse library, you can use uv or pip.

uv (recommended)

$ uv pip install aigverse

pip

(.venv) $ python -m pip install aigverse

In most practical cases (under 64-bit Linux, macOS incl. Apple Silicon, and Windows), this requires no compilation and merely downloads and installs a platform-specific pre-built wheel.

Once installed, you can check if the installation was successful by running:

(.venv) $ python -c "import aigverse; print(aigverse.__version__)"

which should print the installed version of the library.

If you want to use the aigverse Python package in your own project, you can simply add it as a dependency to your pyproject.toml or setup.py file. This will automatically install the aigverse package and its dependencies when your project is installed.

uv (recommended)

$ uv add aigverse

pyproject.toml

[project]
# ...
dependencies = ["aigverse"]
# ...

setup.py

from setuptools import setup

setup(
    # ...
    install_requires=["aigverse"],
    # ...
)

Machine Learning Adapters¶

The base installation intentionally excludes ML and data science adapters so that core synthesis workflows remain lightweight and free of heavy optional dependencies. Install the aigverse[adapters] extra when you need graph or numeric interoperability in Python ML/data science pipelines:

uv (recommended)

$ uv pip install "aigverse[adapters]"

pip

(.venv) $ python -m pip install "aigverse[adapters]"

The same syntax applies to adding the aigverse package with adapters as a dependency to your own project.