fix: handle empty numpy arrays in scalar proto conversion during materialization#6267
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When a scalar feature column contains an empty numpy array (np.array([])),
pd.isnull() returns an array instead of a scalar bool. Applying Python's
`not` operator to that array raises:
ValueError: The truth value of an empty array is ambiguous.
This adds a safe null-check helper (is_scalar_null) that handles
array-like values before falling through to pd.isnull(). Empty arrays
are treated as null values, consistent with None and np.nan.
The helper is used in _convert_scalar_values_to_proto to replace the
bare `pd.isnull()` calls that crash on array inputs.
Closes feast-dev#6255
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Closing — this is a duplicate of #6259 which was already opened by the issue author. Apologies for the noise.