Morgan - Leaves #34
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Morgan - Leaves #34
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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. 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(log (n)) | ||
| def add(key, value) |
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| # Time Complexity: O(n) | ||
| # Space Complexity: O(n) | ||
| def find(key) |
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If the tree is balanced this is O(log n) for both time & space and O(n) if it's not.
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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 right, but the space complexity (for a balanced tree) is O(log n ) because your call stack will never get greater than the height of the tree.
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