[Python] How to create a numpy dtype object array from a python list without copying data?

As the numpy docs describe for the object dtype, arrays created with the object dtype are simply references to an underlying data store like a python list. The tobytes() method on such an object returns pointers to this data store.

I was wondering if it's possible to create an ndarray object from a python list without creating a copy on creation.

For example, trying to create an ndarray from a list then assigning copy=False to np.asarray raises an exception:

import numpy as np

l = ['spam', 'eggs']
arr = np.asarray(l, dtype='object', copy=False) # raises ValueError


I don't know how numpy is storing the underlying data, but it seems like it should be very similar (if not identical) to a python list.

Continue reading...