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CheezItMan
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Apr 15, 2021
CheezItMan
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CheezItMan
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Nice work Alice, well done. You hit the learning goals here. I had some comments on time/space complexity. However this is well done.
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| # Time Complexity: O(log n) | ||
| # Space Complexity: O(1) | ||
| def add(key, value) |
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👍 The time complexity is O(log n) if the tree is balanced and O(n) if it's unbalanced.
The space complexity is the same (because of the recursion).
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| # Time Complexity: O(log n) | ||
| # Space Complexity: O(log n) | ||
| def find(key) |
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👍 The time complexity is O(log n) if the tree is balanced and O(n) if it's unbalanced.
The space complexity is the same (because of the recursion).
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| # Time Complexity: O(n) | ||
| # Space Complexity: O(n) | ||
| def preorder |
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| # Time Complexity: O(n) | ||
| # Space Complexity: O(n) | ||
| def postorder |
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| # Time Complexity: O(n) | ||
| # Space Complexity: O(n) | ||
| def height |
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👍 The space complexity (due to recursion) is O(log n) if the tree is balanced and O(n) if it's unbalanced.
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