Support policy¶

What you can rely on from version 1.0.0 on.

Versions of Python and of the packages¶

The library runs on Python 3.10 to 3.14, with numpy 1.26 or any 2.x. Every push runs the tests on Ubuntu 22.04 with Python 3.10 and on Ubuntu 24.04 with Python 3.12 and 3.14, with numpy 1.26 and with 2.x (3.14 with 2.x only). One more job runs them on Python 3.10 with the oldest versions the library allows: numpy 1.26, SciPy 1.11, CasADi 3.6 and matplotlib 3.8. Before a release the tests also run on macOS and Windows, and we have run them from a fresh clone on 3.11 and 3.13. PyTorch, which only the models exported as PyTorch code need, is tried with its newest release.

A Python version is dropped, in a minor release and with a line in the changelog, once it has reached the end of its life. The same goes for the oldest numpy, SciPy, CasADi and matplotlib that the library asks for.

The tests also run on macOS and Windows, on request: they are not part of every push.

Versions of the library¶

Versions follow semantic versioning. A minor or patch release does not break the public API, and a name that is going away warns with a DeprecationWarning for at least one minor release before a major release removes it.

The public API is what the reference lists: the names in the __all__ of a module. Names that start with an underscore, and modules the reference does not list, are internal and may change at any time.

A fix can change numbers. When it does, the changelog says so, with what changed and from which version, as it did for the arc formula of the soft arm’s kinematics. An experiment that must run the same way always has to pin the version (Installation).

Run logs carry the library’s version and a version of their layout. A log of an older layout is read by newer versions, and a log of a newer layout is refused with a message that says to update. The changelog lists a change to the layout of the configuration files.

Safety¶

The library gives no guarantee of safety on a real robot. Nothing limits a torque unless you add the output stage that does, and a controller that is passive in theory can still go unstable with the delay and the sampling of your loop. Read “Before the first run” in Real-time runs before the first run on a robot.

Problems¶

Report a bug, or a page that does not work as written, on the issue tracker, with the output of pip show virtualmodelcontrol and of python -c "import casadi, numpy; print(casadi.__version__, numpy.__version__)".