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3798168
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2010-09-26T14:14:40.490
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2010-09-26T14:14:40.490
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<p>I had used something similar in order to build somithing similar <a href="http://en.wikipedia.org/wiki/Trie" rel="nofollow">Trie</a> for an application. I hope it helps.</p> <pre><code>class Trie: """ A Trie is like a dictionary in that it maps keys to values. However, because of the way keys are stored, it allows look up based on the longest prefix that matches. """ def __init__(self): # Every node consists of a list with two position. In # the first one,there is the value while on the second # one a dictionary which leads to the rest of the nodes. self.root = [0, {}] def insert(self, key): """ Add the given value for the given key. >>> a = Trie() >>> a.insert('kalo') >>> print(a) [0, {'k': [1, {'a': [1, {'l': [1, {'o': [1, {}]}]}]}]}] >>> a.insert('kalo') >>> print(a) [0, {'k': [2, {'a': [2, {'l': [2, {'o': [2, {}]}]}]}]}] >>> b = Trie() >>> b.insert('heh') >>> b.insert('ha') >>> print(b) [0, {'h': [2, {'a': [1, {}], 'e': [1, {'h': [1, {}]}]}]}] """ # find the node to append the new value. curr_node = self.root for k in key: curr_node = curr_node[1].setdefault(k, [0, {}]) curr_node[0] += 1 def find(self, key): """ Return the value for the given key or None if key not found. >>> a = Trie() >>> a.insert('ha') >>> a.insert('ha') >>> a.insert('he') >>> a.insert('ho') >>> print(a.find('h')) 4 >>> print(a.find('ha')) 2 >>> print(a.find('he')) 1 """ curr_node = self.root for k in key: try: curr_node = curr_node[1][k] except KeyError: return 0 return curr_node[0] def __str__(self): return str(self.root) def __getitem__(self, key): curr_node = self.root for k in key: try: curr_node = curr_node[1][k] except KeyError: yield None for k in curr_node[1]: yield k, curr_node[1][k][0] if __name__ == '__main__': a = Trie() a.insert('kalo') a.insert('kala') a.insert('kal') a.insert('kata') print(a.find('kala')) for b in a['ka']: print(b) print(a) </code></pre>
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1. POPython: Easily access deeply nested dict (get and set)
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1. USDimitris Leventeas
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