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Mary Tian CS Fun Bipartition Graph #49

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37 changes: 36 additions & 1 deletion graphs/possible_bipartition.py
Original file line number Diff line number Diff line change
Expand Up @@ -8,5 +8,40 @@ def possible_bipartition(dislikes):
Time Complexity: ?
Space Complexity: ?
Comment on lines 8 to 9

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⏱🪐 Time and space complexity?

"""
pass
# this is a guard clause
if not dislikes:
return True

queue = deque()
visited = set()
red = set()
green = set()

if dislikes[0]:
start_node = 0
else:
start_node = 1
Comment on lines +20 to +23

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Consider the edge case where there are multiple disconnected nodes indexed at the beginning of dislikes

For example: `dislikes = [ [], [], [], [1,2] ]

How might you refactor your code to account for this edge case?


queue.append(start_node)
visited.add(start_node)
red.add(start_node)

while len(queue) != 0:

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🐩 Nice BFS approach

current = queue.popleft()

for neighbor in dislikes[current]:
if neighbor not in visited:
visited.add(neighbor)
queue.append(neighbor)
if current in red:
green.add(neighbor)
else:
red.add(neighbor)
elif neighbor in visited:
if current in red and neighbor in red:
return False
if current in green and neighbor in green:
return False

return True