`product` is deprecated as of NumPy 1.25.0

[emanuel-schmid]

Most of the warnings raised during tests are about product being deprecated as of Numpy 1.25.

Whithin climada, they are raised here:

warning	module	lineno
product is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use prod instead.	climada.hazard.io	1149
product is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use prod instead.	climada.hazard.io	1169
product is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use prod instead.	climada.hazard.centroids.centr	1003
product is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use prod instead.	climada.hazard.centroids.centr	1004
product is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use prod instead.	climada.hazard.centroids.centr	1022
product is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use prod instead.	climada.util.hdf5_handler	68
product is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use prod instead.	climada.hazard.centroids.centr	1006
product is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use prod instead.	climada.hazard.centroids.centr	1007

The cause of this is h5py being restricted to <=3.8, because eccodes is pinned to 2.27.
It happens wherever np.array(obj) is called on a obj that is a h5py Store or Dataset.

The solution is to unpin eccodes, as requested in PR #947

Alternatively, all lines with np.array(obj) could be replaced by obj[:] (https://github.com/CLIMADA-project/climada_python/tree/feature/avoid_product_in_h5py)

[emanuel-schmid]

Quite likely the Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation that is raised here:

module	lineno
climada.util.hdf5_handler	92
climada.util.finance	218
climada.hazard.tc_tracks_synth	1052

will also disappear with h5py > 3.8