Defined in awkward.operations.convert on line 171.

ak.to_numpy(array, allow_missing=True)

Converts array (many types supported, including all Awkward Arrays and Records) into a NumPy array, if possible.

If the data are numerical and regular (nested lists have equal lengths in each dimension, as described by the #type), they can be losslessly converted to a NumPy array and this function returns without an error.

Otherwise, the function raises an error. It does not create a NumPy array with dtype "O" for np.object_ (see the note on object_ type) since silent conversions to dtype "O" arrays would not only be a significant performance hit, but would also break functionality, since nested lists in a NumPy "O" array are severed from the array and cannot be sliced as dimensions.

If array is a scalar, it is converted into a NumPy scalar.

If allow_missing is True; NumPy masked arrays are a possible result; otherwise, missing values (None) cause this function to raise an error.

See also ak.from_numpy and ak.to_cupy.