how to avoid float/int casting error with to_reduced_units() on integer arrays

[CagtayFabry]

What is the best approach to avoid casting errors when working with integer arrays? Is there any way to enforce casting to float for unit conversions?

The following example works with to_base_units() on all inputs but fails with to_reduced_units() once any kind of array gets introduced:

import pint
ureg = pint.UnitRegistry()
Q_ = ureg.Quantity

Q_(3, "s * ms").to_base_units() # works
Q_([3,4], "s * ms").to_base_units() # works, results are float

Q_(3, "s * ms").to_reduced_units() # works
Q_([3,4], "s * ms").to_reduced_units() # fails

UFuncTypeError: Cannot cast ufunc 'multiply' output from dtype('float64') to dtype('int32') with casting rule 'same_kind'

to_reduced_units() seems call ito_reduced_units() almost immediately which produces the error.

With force_ndarray_like=True it obviously stops working for scalar inputs as well.

import pint
ureg = pint.UnitRegistry(force_ndarray_like=True)
Q_ = ureg.Quantity

Q_(3, "s * ms").to_reduced_units()

UFuncTypeError: Cannot cast ufunc 'multiply' output from dtype('float64') to dtype('int32') with casting rule 'same_kind'

If possible I would like to catch this behavior as early as possible because it can be quite confusing for new users who might not consider explicitly casting their inputs as float and encounter this error at some later point during their analysis.