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59 lines
1.8 KiB
Python
59 lines
1.8 KiB
Python
"""The DFS function simply calls itself recursively for every unvisited child of
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its argument. We can emulate that behaviour precisely using a stack of iterators.
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Instead of recursively calling with a node, we'll push an iterator to the node's
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children onto the iterator stack. When the iterator at the top of the stack
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terminates, we'll pop it off the stack.
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Pseudocode:
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all nodes initially unexplored
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mark s as explored
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for every edge (s, v):
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if v unexplored:
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DFS(G, v)
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"""
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from typing import Dict, Set
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def depth_first_search(graph: Dict, start: str) -> Set[int]:
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"""Depth First Search on Graph
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:param graph: directed graph in dictionary format
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:param vertex: starting vectex as a string
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:returns: the trace of the search
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>>> G = { "A": ["B", "C", "D"], "B": ["A", "D", "E"],
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... "C": ["A", "F"], "D": ["B", "D"], "E": ["B", "F"],
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... "F": ["C", "E", "G"], "G": ["F"] }
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>>> start = "A"
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>>> output_G = list({'A', 'B', 'C', 'D', 'E', 'F', 'G'})
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>>> all(x in output_G for x in list(depth_first_search(G, "A")))
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True
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>>> all(x in output_G for x in list(depth_first_search(G, "G")))
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True
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"""
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explored, stack = set(start), [start]
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while stack:
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v = stack.pop()
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# one difference from BFS is to pop last element here instead of first one
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for w in graph[v]:
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if w not in explored:
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explored.add(w)
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stack.append(w)
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return explored
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G = {
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"A": ["B", "C", "D"],
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"B": ["A", "D", "E"],
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"C": ["A", "F"],
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"D": ["B", "D"],
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"E": ["B", "F"],
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"F": ["C", "E", "G"],
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"G": ["F"],
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}
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if __name__ == "__main__":
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import doctest
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doctest.testmod()
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print(depth_first_search(G, "A"))
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