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expeople1 [14]
2 years ago
5

This idea enhances wollstonecraft’s argument by insisting that women deserve to be educated despite their inferior capacity for

learning. Suggesting that women’s natural curiosity will lead to trickery if it is not nurtured through education. Asserting that domestic chores offer fulfillment because they require a vast knowledge of the world. Claiming that women who excel in domestic roles should be called upon to serve as world leaders
SAT
2 answers:
saul85 [17]2 years ago
7 0

Answer:

b

Explanation:

mash [69]2 years ago
5 0

<em>A vindication of the rights of women</em> by Mary Wollstonecraft is a political philosophy. In the excerpt, the author implies that a woman's inquisitiveness will lead to trickery.

<h3>What is the theme of A Vindication of the rights?</h3>

<em>A vindication of the rights of women</em> is a dedication work to Charles. M. Talleyrand. It depicts the major denial and oppression faced by a woman in society and women's education.

The narrator suggests that if women are forced to only the domestic work then they will resort to clever and tricky ways like visiting fortune tellers, rivalries, and engaging in silly activities.

Therefore, option B. suggests that women can assort in tricky and clever ways.

Learn more about Wollstonecraft's argument here:

brainly.com/question/14846238

#SPJ1

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Once you have your heap structure created, next you must use it as a backing structure to a priority queue. Develop a PriorityQu
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Using the knowledge in computational language in python it is possible to write a code that Develop a PriorityQueue data structure in a file.

<h3>Writting the code in python:</h3>

<em>import sys</em>

<em>class Node:</em>

<em>def __init__(self,key):</em>

<em>self.left = None</em>

<em>self.right = None</em>

<em>self.val = key</em>

<em>self.parent = None</em>

<em>class MinHeap:</em>

<em>def __init__(self, maxsize):</em>

<em>self.maxsize = maxsize</em>

<em>self.size = 0</em>

<em>self.Heap = Node(-1 * sys.maxsize )</em>

<em>self.FRONT = self.Heap</em>

<em># A utility function to do inorder tree traversal</em>

<em>def isLeaf(self, node):</em>

<em>if node.left == None and node.right == Node:</em>

<em>return True</em>

<em>return False</em>

<em># Function to swap two nodes of the heap</em>

<em>def swap(self, node1, node2):</em>

<em>node1.data, node2.data = node2.data, node1.data</em>

<em># Function to heapify the node at pos</em>

<em>def minHeapify(self, node):</em>

<em># If the node is a non-leaf node and greater</em>

<em># than any of its child</em>

<em>if not self.isLeaf(node):</em>

<em>if (node.data > node.left.data or</em>

<em>node.data > node.right.data):</em>

<em># Swap with the left child and heapify</em>

<em># the left child</em>

<em>if node.left.data < node.right.data:</em>

<em>self.swap(node, node.left)</em>

<em>self.minHeapify(node.left)</em>

<em># Swap with the right child and heapify</em>

<em># the right child</em>

<em>else:</em>

<em>self.swap(node, node.right)</em>

<em>self.minHeapify(node.right)</em>

<em># Function to insert a node into the heap</em>

<em>def insert(self, element):</em>

<em>if self.size >= self.maxsize :</em>

<em>return</em>

<em>self.size+= 1</em>

<em>self.bst_insert(FRONT, element)</em>

<em>current = FRONT</em>

<em>while current.parent != None and current.data < current.parent.data:</em>

<em>self.swap(current, current.parent)</em>

<em>current = current.parent</em>

<em># Function to print the contents of the heap</em>

<em>def Print(self):</em>

<em>self.inorder()</em>

<em># Function to build the min heap using</em>

<em># the minHeapify function</em>

<em>def inorder(self, root):</em>

<em>if root:</em>

<em>inorder(root.left)</em>

<em>print(root.val)</em>

<em>inorder(root.right)</em>

<em>def bst_insert(self, root, node):</em>

<em>if root is None:</em>

<em>root = node</em>

<em>else:</em>

<em>root.next = node</em>

<em>self.FRONT = node</em>

<em># Driver Code</em>

<em>if __name__ == "__main__":</em>

<em>r = Node(50)</em>

<em>bst_insert(r,Node(30))</em>

<em>bst_insert(r,Node(20))</em>

<em>bst_insert(r,Node(40))</em>

<em>bst_insert(r,Node(70))</em>

<em>bst_insert(r,Node(60))</em>

<em>bst_insert(r,Node(80))</em>

<em># Print inoder traversal of the BST</em>

<em>inorder(r)</em>

<em>print('The minHeap is ')</em>

<em>minHeap = MinHeap(15)</em>

<em>minHeap.insert(5)</em>

<em>minHeap.insert(3)</em>

<em>minHeap.insert(17)</em>

<em>minHeap.insert(10)</em>

<em>minHeap.insert(84)</em>

<em>minHeap.insert(19)</em>

<em>minHeap.insert(6)</em>

<em>minHeap.insert(22)</em>

<em>minHeap.insert(9)</em>

<em>minHeap.minHeap()</em>

<em>minHeap.Print()</em>

<em>print("The Min val is " + str(minHeap.remove()))</em>

See more about python at brainly.com/question/13437928

#SPJ1

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