Commit b0be304

john-liu2MaximSmolskiy

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authored

Use deque as queue in breadth_first_search_shortest_path_2.py (#12861)

* Fixes #12857 Use collections.deque as queue in graphs BFS shortest path 2 * Use collections.deque as queue in the correct syntax: queue = deque([start]) * Fix CI error due to HTTP 404 on https://finance.yahoo.com/quote/GOOG/\?p\=GOOG * Undo change in workflows/build.yml as it's fixed in PR 12864 --------- Co-authored-by: Maxim Smolskiy <mithridatus@mail.ru>

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- breadth_first_search_shortest_path_2.py

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`‎graphs/breadth_first_search_shortest_path_2.py`

Lines changed: 12 additions & 10 deletions

Original file line number	Diff line number	Diff line change
`@@ -1,10 +1,12 @@`
`1`		`-"""Breadth-first search shortest path implementations.`
	`1`	`+"""Breadth-first search the shortest path implementations.`
`2`	`2`	`doctest:`
`3`		`-python -m doctest -v bfs_shortest_path.py`
	`3`	`+python -m doctest -v breadth_first_search_shortest_path_2.py`
`4`	`4`	`Manual test:`
`5`		`-python bfs_shortest_path.py`
	`5`	`+python breadth_first_search_shortest_path_2.py`
`6`	`6`	`"""`
`7`	`7`
	`8`	`+from collections import deque`
	`9`	`+`
`8`	`10`	`demo_graph = {`
`9`	`11`	`"A": ["B", "C", "E"],`
`10`	`12`	`"B": ["A", "D", "E"],`
`@@ -17,7 +19,7 @@`
`17`	`19`
`18`	`20`
`19`	`21`	`def bfs_shortest_path(graph: dict, start, goal) -> list[str]:`
`20`		- """Find shortest path between `start` and `goal` nodes.
	`22`	+ """Find the shortest path between `start` and `goal` nodes.
`21`	`23`	`Args:`
`22`	`24`	`graph (dict): node/list of neighboring nodes key/value pairs.`
`23`	`25`	`start: start node.`
`@@ -36,7 +38,7 @@ def bfs_shortest_path(graph: dict, start, goal) -> list[str]:`
`36`	`38`	`# keep track of explored nodes`
`37`	`39`	`explored = set()`
`38`	`40`	`# keep track of all the paths to be checked`
`39`		`- queue = [[start]]`
	`41`	`+ queue = deque([[start]])`
`40`	`42`
`41`	`43`	`# return path if start is goal`
`42`	`44`	`if start == goal:`
`@@ -45,7 +47,7 @@ def bfs_shortest_path(graph: dict, start, goal) -> list[str]:`
`45`	`47`	`# keeps looping until all possible paths have been checked`
`46`	`48`	`while queue:`
`47`	`49`	`# pop the first path from the queue`
`48`		`- path = queue.pop(0)`
	`50`	`+ path = queue.popleft()`
`49`	`51`	`# get the last node from the path`
`50`	`52`	`node = path[-1]`
`51`	`53`	`if node not in explored:`
`@@ -68,13 +70,13 @@ def bfs_shortest_path(graph: dict, start, goal) -> list[str]:`
`68`	`70`
`69`	`71`
`70`	`72`	`def bfs_shortest_path_distance(graph: dict, start, target) -> int:`
`71`		- """Find shortest path distance between `start` and `target` nodes.
	`73`	+ """Find the shortest path distance between `start` and `target` nodes.
`72`	`74`	`Args:`
`73`	`75`	`graph: node/list of neighboring nodes key/value pairs.`
`74`	`76`	`start: node to start search from.`
`75`	`77`	`target: node to search for.`
`76`	`78`	`Returns:`
`77`		- Number of edges in shortest path between `start` and `target` nodes.
	`79`	+ Number of edges in the shortest path between `start` and `target` nodes.
`78`	`80`	`-1 if no path exists.`
`79`	`81`	`Example:`
`80`	`82`	`>>> bfs_shortest_path_distance(demo_graph, "G", "D")`
`@@ -88,12 +90,12 @@ def bfs_shortest_path_distance(graph: dict, start, target) -> int:`
`88`	`90`	`return -1`
`89`	`91`	`if start == target:`
`90`	`92`	`return 0`
`91`		`- queue = [start]`
	`93`	`+ queue = deque([start])`
`92`	`94`	`visited = set(start)`
`93`	`95`	# Keep tab on distances from `start` node.
`94`	`96`	`dist = {start: 0, target: -1}`
`95`	`97`	`while queue:`
`96`		`- node = queue.pop(0)`
	`98`	`+ node = queue.popleft()`
`97`	`99`	`if node == target:`
`98`	`100`	`dist[target] = (`
`99`	`101`	`dist[node] if dist[target] == -1 else min(dist[target], dist[node])`

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`‎graphs/breadth_first_search_shortest_path_2.py`

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