mirror of
https://github.com/TheAlgorithms/Python.git
synced 2024-12-18 09:10:16 +00:00
bc8df6de31
* [pre-commit.ci] pre-commit autoupdate updates: - [github.com/astral-sh/ruff-pre-commit: v0.2.2 → v0.3.2](https://github.com/astral-sh/ruff-pre-commit/compare/v0.2.2...v0.3.2) - [github.com/pre-commit/mirrors-mypy: v1.8.0 → v1.9.0](https://github.com/pre-commit/mirrors-mypy/compare/v1.8.0...v1.9.0) * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
89 lines
2.3 KiB
Python
89 lines
2.3 KiB
Python
"""
|
|
https://en.wikipedia.org/wiki/Breadth-first_search
|
|
pseudo-code:
|
|
breadth_first_search(graph G, start vertex s):
|
|
// all nodes initially unexplored
|
|
mark s as explored
|
|
let Q = queue data structure, initialized with s
|
|
while Q is non-empty:
|
|
remove the first node of Q, call it v
|
|
for each edge(v, w): // for w in graph[v]
|
|
if w unexplored:
|
|
mark w as explored
|
|
add w to Q (at the end)
|
|
"""
|
|
|
|
from __future__ import annotations
|
|
|
|
from collections import deque
|
|
from queue import Queue
|
|
from timeit import timeit
|
|
|
|
G = {
|
|
"A": ["B", "C"],
|
|
"B": ["A", "D", "E"],
|
|
"C": ["A", "F"],
|
|
"D": ["B"],
|
|
"E": ["B", "F"],
|
|
"F": ["C", "E"],
|
|
}
|
|
|
|
|
|
def breadth_first_search(graph: dict, start: str) -> list[str]:
|
|
"""
|
|
Implementation of breadth first search using queue.Queue.
|
|
|
|
>>> ''.join(breadth_first_search(G, 'A'))
|
|
'ABCDEF'
|
|
"""
|
|
explored = {start}
|
|
result = [start]
|
|
queue: Queue = Queue()
|
|
queue.put(start)
|
|
while not queue.empty():
|
|
v = queue.get()
|
|
for w in graph[v]:
|
|
if w not in explored:
|
|
explored.add(w)
|
|
result.append(w)
|
|
queue.put(w)
|
|
return result
|
|
|
|
|
|
def breadth_first_search_with_deque(graph: dict, start: str) -> list[str]:
|
|
"""
|
|
Implementation of breadth first search using collection.queue.
|
|
|
|
>>> ''.join(breadth_first_search_with_deque(G, 'A'))
|
|
'ABCDEF'
|
|
"""
|
|
visited = {start}
|
|
result = [start]
|
|
queue = deque([start])
|
|
while queue:
|
|
v = queue.popleft()
|
|
for child in graph[v]:
|
|
if child not in visited:
|
|
visited.add(child)
|
|
result.append(child)
|
|
queue.append(child)
|
|
return result
|
|
|
|
|
|
def benchmark_function(name: str) -> None:
|
|
setup = f"from __main__ import G, {name}"
|
|
number = 10000
|
|
res = timeit(f"{name}(G, 'A')", setup=setup, number=number)
|
|
print(f"{name:<35} finished {number} runs in {res:.5f} seconds")
|
|
|
|
|
|
if __name__ == "__main__":
|
|
import doctest
|
|
|
|
doctest.testmod()
|
|
|
|
benchmark_function("breadth_first_search")
|
|
benchmark_function("breadth_first_search_with_deque")
|
|
# breadth_first_search finished 10000 runs in 0.20999 seconds
|
|
# breadth_first_search_with_deque finished 10000 runs in 0.01421 seconds
|