PennyLane coordinates communication between classical computing libraries and quantum devices through a suite of plugins. Its core job is to manage the evaluation of parametrized quantum circuits (variational circuits) on quantum devices and expose them to machine learning libraries. PennyLane also provides access to gradients of quantum circuits, letting the machine learning library perform backpropagation through quantum circuits — an essential capability for optimizing and training hybrid quantum-classical models.