Creating NumPy memory views: 1D and 3D array examples in Python

Python Memory Views Data Type: Exercise-3 with Solution

Write a Python program that creates a 1-dimensional and 3-dimensional memory view from a NumPy array.

Sample Solution:

Code:

import numpy as np

def main():
    try:
        # Create a NumPy array
        array_1_d = np.array([1, 2, 3, 4, 5, 6])
        array_3_d = np.array([[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]])
        
        # Create memory views from the NumPy arrays
        print("Memory views:")
        mem_view_1_d = memoryview(array_1_d)
        print(mem_view_1_d)
        mem_view_3_d = memoryview(array_3_d)
        print(mem_view_3_d)
        
        # Print the memory views
        print("\n1-D Memory View:")
        print(mem_view_1_d.tolist())
        
        print("\n3-D Memory View:")
        print(mem_view_3_d.tolist())
    except Exception as e:
        print("An error occurred:", e)

if __name__ == "__main__":
    main()

Output:

Memory views:
<memory at 0x00000266DBB4E108>
<memory at 0x00000266DBB085E8>

1-D Memory View:
[1, 2, 3, 4, 5, 6]

3-D Memory View:
[[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]]

The above exercise demonstrates how to create memory views from NumPy arrays and print their contents.

Flowchart:

Previous: Converting Python memory view to bytes: Function and example.
Next: Calculating average with NumPy memory view in Python.