Can changing constraints be used with the scikit-optimize API?

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The canonical use case for scikit-optimize is an optimization objective given a fixed set of hyperparameters, where skopt is given full control to explore the space. However, one may wish to simultaneously expose a variable to skopt and fix it to a certain value on a subsequent iteration because it is outside of one's control. Is this possible using the current API?

Hypothetical use case:

We wish to maximize bike sale profit. Price is a free parameter to be optimized. The rain forecast is outside of our control, but we wish to control for it in skopt.

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