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    • Python Heapq

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    Question 1

    What is the primary characteristic of a min-heap data structure?

    • A

      The smallest element is at the leaf nodes.

    • B

      Each parent node is larger than its children.

    • C

      The smallest element is always at the root.

    • D

      Elements are stored in a random order.

    Question 2

    Which function in the heapq module is used to add an element while maintaining the heap property?

    • A

      heapq.pop()

    • B

      heapq.insert()

    • C

      heapq.heappush()

    • D

      heapq.add()

    Question 3

    What operation does the heapq.heapreplace() function perform?

    • A

      It only adds an element to the heap.

    • B

      It pops the largest element from the heap.

    • C

      It pops the smallest element and adds a new element.

    • D

      It merges two heaps into one.

    Question 4

    Which of the following functions allows retrieval of the n largest elements from a heap?

    • A

      heapq.nlargest()

    • B

      heapq.getlargest()

    • C

      heapq.maxelements(n)

    • D

      heapq.retrievelargest()

    Question 5

    What is a disadvantage of using a heap queue?

    • A

      It supports random access to elements.

    • B

      It allows efficient sorting of all elements.

    • C

      It is not thread-safe.

    • D

      It requires more memory than linked lists.

    Question 6

    In Python's heapq module, which function is used to merge multiple sorted iterables into a single sorted heap?

    • A

      heapq.combine()

    • B

      heapq.merge()

    • C

      heapq.concat()

    • D

      heapq.join()

    Question 7

    When using the heappop() function, what is the result?

    • A

      It adds a new element to the heap.

    • B

      It returns the largest element in the heap.

    • C

      It removes and returns the smallest element in the heap.

    • D

      It checks the size of the heap.

    Question 8

    Which of the following statements about heaps is true?

    • A

      Heaps can be implemented using binary trees only.

    • B

      Heaps support random access to elements efficiently.

    • C

      Heaps do not allow duplicate elements.

    • D

      Heaps can be implemented using lists in Python.

    Question 9

    What is the time complexity of the heappush() operation in a heap?

    • A

      O(1)

    • B

      O(n)

    • C

      O(log n)

    • D

      O(n log n)

    Question 10

    Which heap operation is more efficient when replacing the smallest element with a new value?

    • A

      Using heappop() followed by heappush()

    • B

      Using heapq.replace()

    • C

      Using heappushpop()

    • D

      Using heapq.merge()

    There are 11 questions to complete.

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