Hi really need help for this coding assignment in python3

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Hi really need help for this coding assignment in python3

Hi really need help for this coding assignment in python3
Module 9 Homework – Trees Prefix Trees A prefix tree, or a trie (from re-TRIE-ve), is a tree intended for storing a set of keys, often strings. The data structure is optimized for fast retrieval of the keys and for space. The nodes in a prefix tree do not store full keys directly. Instead, nodes store part of a key, with a node’s position defining the key it represents. We are going to implement a prefix tree dedicated to strings, where the keys are going to be valid words. Each node will store one character of a key. For instance, the valid keys [‘am’ , ‘at’ , ‘ate’ , ‘eat’ , ‘mat’ , ‘me’ , ‘met’ , ‘tea’ , ‘tee’ ] are represented by the blue nodes in the following prefix tree Note that the root node (in red) represents an empty string. Assignment We have implemented the prefix tree through a class WordTrie , using a node class TrieNode for the recursive structure. WordTrie is complete, you must implement the recursive functionality in TrieNode . Two important assumptions will arise as you complete this assignment: assume that the words contain only lowercase letters a-z assume that the words are given in alphabetical order, as a list of strings. The alphabetical ordering is relevant, as Python dictionaries maintain insertion order. WordTrie functionality (implemented for you) The WordTrie should be initialized using an alphabetically ordered list of strings >>> my_words = [ ‘am’ , ‘at’ , ‘ate’ , ‘eat’ , ‘mat’ , ‘me’ , ‘met’ , ‘tea’ , ‘tee’ ] >>> my_trie = WordTrie(my_words) get_words returns a generator of all words with a given prefix >>> for word in my_trie.get_words( ‘t’ ): print(word) tea tee The iter operator provides an iterator over all valid words >>> for word in my_trie: print(word, end= ‘ ‘ ) am at ate eat mat me met tea tee get_nb_words returns the number of words with a given prefix >>> my_trie.get_nb_words( ‘m’ ) 3 >>> my_trie.get_nb_words( ‘at’ ) 2 >>> my_trie.get_nb_words( ‘mt’ ) 0 len returns the number of valid words in the trie >>> len(my_trie) 9 The in operator works as expected >>> ‘eat’ in my_trie True >>> ‘ma’ in my_trie # ‘ma’ is a node but not a valid word False The above methods are fundamentally just a wrapper – the difficult recursive functionality, which you are responsible for implementing, is in the TrieNode class. TrieNode Attr ib ute s a d ded d urin g init Each node adds only the following two attributes during init (the methods described below are also attributes stored in each node object, but methods are not added to an object during init ). _children – a dictionary of children. K eys are letters, values are the nodes associated with those letters. For instance, the root node in the figure shown above would have a dictionary with 4 items: _root._children = { ‘a’ :some_node, ‘e’ :some_node, ‘m’ :some_node, ‘t’ :some_node} _is_word – a Boolean describing whether the current node marks the end of a valid word No other information is stored in the nodes. This includes: The prefix of the node The number of nodes in the subtree Deliverables Implement the following functions in the TrieNode class. You are free to add additional input paremeters and methods as you see fit, but do not change the attributes defined in a node’s init . init – initializes a new node. The only attributes you should add here are _children and _is_word , but feel free to adjust the list of input paramaters add_word(self, word) – adds a word (a string with one or more characters) to the T rie. Only used during initialization. find_node(self, prefix) – returns the node representing a given prefix (a string with zero or more characters) get_words(self, prefix) – returns a generator, which generates all the words with the given prefix (a string with zero or more characters) in the subtrie rooted at this node get_nb_words(self) – returns the number of words (with any prefix) in the subtrie rooted at this node Note o n G en era to rs A generator function uses the keyword yield rather than return . In recursive generator functions, we use yield from for recursive calls and yield to return the base case. For instance, the in_order function from lab: def in_order (self) : if self.left is not None : yield from self.left.in_order() # recursively go left yield self.key # return this key if self.right is not None : yield from self.right.in_order() # recursively go right Submission At a minimum, submit the following file: WordTrie.py Students must submit to Mimir individually by the due date (typically, the second W ednesday after this module opens at 11:59 pm EST) to receive credit. Grading We test the public interface in Mimir – the class WordTrie . You will find this assignment easier if you take some time to write test cases for the class TrieNode. 10 – init 5 – recursive implementation 5 – correctness of the implementation 20 – get_words 5 – implemented as a generator function 15 – functionality 20 – get_nb_words 5 – recursive 15 – functionality 15 – len 15 – functionality 15 – in 15 – functionality 20 – iterator 5 – implemented as a generator function 15 – functionality In order to ensure a correct implementation, all the hidden test cases enforce the rules given for the attributes in the TrieNode class. Feedback If you have any feedback on this assignment, please leave it here . W e check this feedback regularly. It has resulted in: A simplified, clear Submitting section on all assignments A simplified, clear Grading section on all assignments Clearer instructions on several assignments

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