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CheezItMan
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Well done Hannah, thanks for getting this in. I like how you did bfs, very compact. Solid work.
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| # Time Complexity: O(Log n) | ||
| # Space Complexity: O(1) | ||
| def add(key, value) |
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| # Time Complexity: O(Log n) | ||
| # Space Complexity: O(1) | ||
| def find(key) |
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| # Time Complexity: O(Log n) | ||
| # Space Complexity: O(n) | ||
| def inorder |
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👍 , interesting choice to make an inner function. That's a very JavaScripty thing to do here.
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| # Time Complexity: O(Log n) | ||
| # Space Complexity: O(n) | ||
| def preorder |
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| # Time Complexity: O(Log n) | ||
| # Space Complexity: O(n) | ||
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| def postorder |
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| # Time Complexity: | ||
| # Space Complexity: | ||
| def height |
| def innerfunc(node) | ||
| return 0 if node.nil? | ||
| return 1 if !node.left && !node.right | ||
| return [innerfunc(node.left) + 1, innerfunc(node.right) + 1].max |
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Very slightly more compact
Suggested change
| return [innerfunc(node.left) + 1, innerfunc(node.right) + 1].max | |
| return [innerfunc(node.left), innerfunc(node.right)].max + 1 |
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| # Time Complexity: | ||
| # Space Complexity: | ||
| def bfs |
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Nice work with BFS. Time and space complexity?
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