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CheezItMan
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Well done Andrea, you hit the learning goals here. Let me know what questions you have on my feedback.
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| # Time Complexity: O(log n) | ||
| # Space Complexity: O(log n) | ||
| def add(self, key, value = None): |
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| # Time Complexity: O(n) | ||
| # Space Complexity: O(n) | ||
| def find(self, key): |
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👍 However the space complexity is O(1) because it's an iterative solution (no call stack).
The time complexity is O(log n) if the tree is balanced and O(n) worst-case.
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| # Time Complexity: O(n) | ||
| # Space Complexity: O(n) | ||
| def inorder(self): |
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| # Time Complexity: O(n) | ||
| # Space Complexity: O(n) | ||
| def preorder(self): |
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| # Time Complexity: O(n) | ||
| # Space Complexity: O(n) | ||
| def postorder(self): |
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| # Time Complexity: O(n) | ||
| # Space Complexity: O(h) | ||
| def height(self): |
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