Garbage collection and array references in NumPy - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a NumPy array named 'arr' with values from 1 to 5.

NumPy

import numpy as np
arr = np.array([1])

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A(1, 2, 3, 4, 5)

B[1, 2, 3, 4, 5]

Crange(1, 6)

D{1, 2, 3, 4, 5}

Attempts:

3 left

💡 Hint

Common Mistakes

Using a tuple instead of a list.

Using a set which is unordered.

Using range object directly without converting to list.

The correct way to create a NumPy array with specific values is to pass a list of those values to np.array(). Here, [1, 2, 3, 4, 5] is a list.

2fill in blank

medium

Complete the code to create a new variable 'ref' that references the same NumPy array as 'arr'.

NumPy

ref = [1]

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Aarr

Barr.view()

Carr.copy()

Dnp.array(arr)

Attempts:

3 left

💡 Hint

Common Mistakes

Using copy() which creates a new array.

Using view() which creates a shallow copy.

Creating a new array with np.array() which duplicates data.

Assigning ref = arr makes ref point to the same array object as arr. No new array is created.

3fill in blank

hard

Fix the error in the code to delete the original array and check if 'ref' still exists.

NumPy

import gc
arr = np.array([1, 2, 3])
ref = arr
[1]  # Delete arr
print(ref)

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Aarr = None

Barr.clear()

Cgc.collect()

Ddel arr

Attempts:

3 left

💡 Hint

Common Mistakes

Using arr.clear() which is invalid for NumPy arrays.

Calling gc.collect() without deleting references first.

Setting arr to None but not deleting the name.

Using del arr removes the name arr but does not delete the array if other references exist. ref still points to the array.

4fill in blank

hard

Fill both blanks to create a copy of 'arr' and then delete the original reference.

NumPy

copy_arr = arr[1]()
del [2]

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Acopy

Barr

Cref

Dview

Attempts:

3 left

💡 Hint

Common Mistakes

Using view() instead of copy() which creates a shallow copy.

Deleting the wrong variable name.

Not deleting any variable.

Calling arr.copy() creates a new array copy. Then deleting arr removes the original reference but copy_arr remains.

5fill in blank

hard

Fill all three blanks to create a view of 'arr', modify it, and then check if 'arr' changed.

NumPy

view_arr = arr[1]()
view_arr[0] = [2]
print(arr[0] == [3])

Drag options to blanks, or click blank then click option'

Aview

B10

Dcopy

Attempts:

3 left

💡 Hint

Common Mistakes

Using copy() which does not affect the original array.

Setting the wrong value in the view.

Comparing to a wrong value in the print statement.

Creating a view with arr.view() means changes to view_arr affect arr. Setting view_arr[0] = 10 changes arr[0] to 10, so the print outputs True.