Branches, C. Gutierrez #43
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CheezItMan
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Feb 27, 2020
CheezItMan
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CheezItMan
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Nice work, you hit the basic learning goals, with some issues on space/time complexity, otherwise well done. Check out my comments and let me know if you have any questions.
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| # Time Complexity: O(log n) | ||
| # Space Complexity: O(n) | ||
| def add(key, value) |
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Space complexity n? Why?
Otherwise the method works.
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| # Time Complexity: O(log n) | ||
| # Space Complexity: O(n) | ||
| def find(key) |
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Similar to add with space complexity.
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| # Time Complexity: O(n) | ||
| # Space Complexity: O(n) | ||
| def inorder |
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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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You're visiting each node so the time complexity is O(n), but because the call stack doesn't go deeper than the height of the tree the space complexity is O(log n) for a balanced tree and O(n) for an unbalanced one.
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