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

# 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.

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