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CheezItMan
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Jan 11, 2022
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Nice work Saejin, you hit the learning goals here. Well done.
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| # Time Complexity: On | ||
| # Space Complexity: O1 | ||
| def add(self, key, value = None): |
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👍 However space complexity is O(log n) if the tree is balanced and O(n) otherwise due to the recursive call stack.
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| # Time Complexity: On | ||
| # Space Complexity: O1 | ||
| def find(self, key): |
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👍 However space complexity is O(log n) if the tree is balanced and O(n) otherwise due to the recursive call stack.
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| # Time Complexity: On | ||
| # Space Complexity: On | ||
| def inorder(self): |
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| # Time Complexity: On | ||
| # Space Complexity: On | ||
| def preorder(self): |
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| # Time Complexity: On | ||
| # Space Complexity: On | ||
| def postorder(self): |
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| # # Time Complexity: On | ||
| # # Space Complexity: O1 | ||
| def height(self): |
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👍 however the space complexity is O(log n ) for a balanced tree and O(n) for an unbalanced tree.
This is due to the recursive call stack.
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| # # Time Complexity: On | ||
| # # Space Complexity: On | ||
| def bfs(self): |
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