Hi! The to_numpy <https://arrow.apache.org/docs/python/generated/pyarrow.Array.html#pyarrow.Array.to_numpy> method on the Array class and subclasses is marked as experimental in the documentation. Is that still the case? In particular I'm most interested in what would be the current recommended way of converting a TimestampArray or Date32Array to a numpy datetime64 array. Going through to_pandas <https://arrow.apache.org/docs/python/generated/pyarrow.Array.html#pyarrow.Array.to_pandas> isn't ideal as there might be values that are supported in Arrow and numpy but are outside of the range supported by pandas nanosecond resolution Timestamp.
I did a quick search on Jira and I found this old resolved issue <https://issues.apache.org/jira/browse/ARROW-6749> which mentions you can just use np.array(arr) where arr is a Timestamp('us') and that seems to work. Would that be recommended over to_numpy or are they doing the same thing? Thanks! Michael
