Topological Sort
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"""Topological Sort on Directed Acyclic Graph(DAG)
https://en.wikipedia.org/wiki/Topological_sorting
https://en.wikipedia.org/wiki/Directed_acyclic_graph
Note: topological_sort() sorts a directed acyclic graph so topological_sort(2, 1, 3)
should fail.
"""
# a
# / \
# b c
# / \
# d e
edges: dict[str, list[str]] = {
"a": ["c", "b"],
"b": ["d", "e"],
"c": [],
"d": [],
"e": [],
}
vertices: list[str] = ["a", "b", "c", "d", "e"]
# Perform topological sort on a DAG starting from the specified node
def topological_sort(start: str, visited: list[str], sort: list[str]) -> list[str]:
"""
Perform topological sort on a directed acyclic graph.
>>> topological_sort('a', [], [])
['c', 'd', 'e', 'b', 'a']
>>> topological_sort("a", "b", "c")
Traceback (most recent call last):
...
ValueError: visited must be a list
>>> topological_sort("a", [], "c")
Traceback (most recent call last):
...
ValueError: sort must be a list
"""
if not isinstance(visited, list):
raise ValueError("visited must be a list")
if not isinstance(sort, list):
raise ValueError("sort must be a list")
current = start
# Mark the current node as visited
visited.append(current)
# List of all neighbors of current node
neighbors = edges[current]
# Traverse all neighbors of the current node
for neighbor in neighbors:
# Recursively visit each unvisited neighbor
if neighbor not in visited:
sort = topological_sort(neighbor, visited, sort)
# After visiting all neighbors, add the current node to the sorted list
sort.append(current)
# If there are some nodes that were not visited (disconnected components)
if len(visited) != len(vertices):
for vertex in vertices:
if vertex not in visited:
sort = topological_sort(vertex, visited, sort)
# Return sorted list
return sort
if __name__ == "__main__":
# Topological Sorting from node "a" (Returns the order in bottom up approach)
sort = topological_sort("a", [], [])
# Reversing the list to get the correct topological order (Top down approach)
sort.reverse()
print(sort)