Python/graphs/depth_first_search.py
Du Yuanchao d6bff5c133
Renamed files and fixed Doctest (#2421)
* * Renamed files
* Fiexed doctest

* fixup! Format Python code with psf/black push

Co-authored-by: github-actions <${GITHUB_ACTOR}@users.noreply.github.com>
2020-09-13 13:27:20 +02:00

50 lines
1.4 KiB
Python

"""Non recursive implementation of a DFS algorithm."""
from typing import Dict, Set
def depth_first_search(graph: Dict, start: str) -> Set[int]:
"""Depth First Search on Graph
:param graph: directed graph in dictionary format
:param vertex: starting vertex as a string
:returns: the trace of the search
>>> G = { "A": ["B", "C", "D"], "B": ["A", "D", "E"],
... "C": ["A", "F"], "D": ["B", "D"], "E": ["B", "F"],
... "F": ["C", "E", "G"], "G": ["F"] }
>>> start = "A"
>>> output_G = list({'A', 'B', 'C', 'D', 'E', 'F', 'G'})
>>> all(x in output_G for x in list(depth_first_search(G, "A")))
True
>>> all(x in output_G for x in list(depth_first_search(G, "G")))
True
"""
explored, stack = set(start), [start]
while stack:
v = stack.pop()
explored.add(v)
# Differences from BFS:
# 1) pop last element instead of first one
# 2) add adjacent elements to stack without exploring them
for adj in reversed(graph[v]):
if adj not in explored:
stack.append(adj)
return explored
G = {
"A": ["B", "C", "D"],
"B": ["A", "D", "E"],
"C": ["A", "F"],
"D": ["B", "D"],
"E": ["B", "F"],
"F": ["C", "E", "G"],
"G": ["F"],
}
if __name__ == "__main__":
import doctest
doctest.testmod()
print(depth_first_search(G, "A"))