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  1. PO
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    <pre><code>#!/usr/bin/env python import sys class Node: def __init__(self): self.next = {} #Initialize an empty hash (python dictionary) self.word_marker = False # There can be words, Hot and Hottest. When search is performed, usually state transition upto leaf node is peformed and characters are printed. # Then in this case, only Hottest will be printed. Hot is intermediate state. Inorder to mark t as a state where word is to be print, a word_marker is used def add_item(self, string): ''' Method to add a string the Trie data structure''' if len(string) == 0: self.word_marker = True return key = string[0] #Extract first character string = string[1:] #Create a string by removing first character # If the key character exists in the hash, call next pointing node's add_item() with remaining string as argument if self.next.has_key(key): self.next[key].add_item(string) # Else create an empty node. Insert the key character to hash and point it to newly created node. Call add_item() in new node with remaining string. else: node = Node() self.next[key] = node node.add_item(string) def dfs(self, sofar=None): '''Perform Depth First Search Traversal''' # When hash of the current node is empty, that means it is a leaf node. # Hence print sofar (sofar is a string containing the path as character sequences through which state transition occured) if self.next.keys() == []: print "Match:",sofar return if self.word_marker == True: print "Match:",sofar # Recursively call dfs for all the nodes pointed by keys in the hash for key in self.next.keys(): self.next[key].dfs(sofar+key) def search(self, string, sofar=""): '''Perform auto completion search and print the autocomplete results''' # Make state transition based on the input characters. # When the input characters becomes exhaused, perform dfs() so that the trie gets traversed upto leaves and print the state characters if len(string) &gt; 0: key = string[0] string = string[1:] if self.next.has_key(key): sofar = sofar + key self.next[key].search(string,sofar) else: print "No match" else: if self.word_marker == True: print "Match:",sofar for key in self.next.keys(): self.next[key].dfs(sofar+key) def fileparse(filename): '''Parse the input dictionary file and build the trie data structure''' fd = open(filename) root = Node() line = fd.readline().strip('\r\n') # Remove newline characters \r\n while line !='': root.add_item(line) line = fd.readline().strip('\r\n') return root if __name__ == '__main__': if len(sys.argv) != 2: print "Usage: ", sys.argv[0], "dictionary_file.txt" sys.exit(2) root = fileparse(sys.argv[1]) print "Input:", input=raw_input() root.search(input) </code></pre>
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    1. POwriting trie implementation
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    1. USbrooklynchick
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    1. This table or related slice is empty.
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    1. This table or related slice is empty.
 

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Detail views are divided into sections. All the information in the data section comes from columns in the selected row. The other sections display data from other, related rows.

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