algo(BFS): implementation with python

Author: theikkila

src/algorithm_practice/Graph_Algorithms/BFS.py

@@ -0,0 +1,121 @@
+from collections import deque
+from random import choice, randint
+
+node_names = ["admiring",
+              "adoring",
+              "affectionate",
+              "agitated",
+              "amazing",
+              "angry",
+              "awesome",
+              "backstabbing",
+              "berserk",
+              "big",
+              "boring",
+              "clever",
+              "cocky",
+              "compassionate",
+              "condescending",
+              "cranky",
+              "desperate",
+              "determined",
+              "distracted",
+              "dreamy",
+              "drunk",
+              "eager",
+              "ecstatic",
+              "elastic",
+              "elated",
+              "elegant",
+              "evil",
+              "fervent",
+              "focused",
+              "furious",
+              "gigantic",
+              "gloomy",
+              "goofy",
+              "grave",
+              "happy",
+              "high",
+              "hopeful",
+              "hungry",
+              "infallible",
+              "jolly",
+              "jovial",
+              "kickass",
+              "lonely",
+              "loving",
+              "mad",
+              "modest",
+              "naughty",
+              "nauseous",
+              "nostalgic",
+              "peaceful",
+              "pedantic",
+              "pensive",
+              "prickly",
+              "reverent",
+              "romantic",
+              "sad",
+              "serene",
+              "sharp",
+              "sick",
+              "silly",
+              "sleepy",
+              "small",
+              "stoic",
+              "stupefied",
+              "suspicious",
+              "tender",
+              "thirsty",
+              "tiny",
+              "trusting",
+              "zen"]
+
+def node(nid):
+    name = choice(node_names) + "-" + str(randint(1000,9999))
+    return {"name": name, "id": nid, "adj": set()}
+
+
+def generate_graph(nodes):
+    graph = []
+    for n in range(0, nodes):
+        n = node(n)
+        for i in range(randint(0, 5)):
+            n['adj'].add(randint(0, nodes-1))
+        graph.append(n)
+    return graph
+
+g = generate_graph(50)
+
+
+def bfs(graph, root_n):
+    k = []
+    for i in range(0, len(graph)):
+        k.append({"distance": None, "parent": None})
+
+    root = graph[root_n]
+    Q = deque()
+    k[root_n]['distance'] = 0
+    Q.append(root)
+
+    while len(Q) > 0:
+        current = Q.pop()
+        for adjecent_node_n in current['adj']:
+            if not k[adjecent_node_n]['distance']:
+                k[adjecent_node_n]['distance'] = k[current['id']]['distance'] + 1
+                k[adjecent_node_n]['parent'] = current['id']
+                Q.append(graph[adjecent_node_n])
+    return k
+
+
+def print_distances(graph, tree):
+    for n, i in enumerate(tree):
+        name = graph[n]['name']
+        print(n, name, "with distance of", i['distance'], "from root, its parent is", i['parent'])
+
+
+if __name__=="__main__":
+    # start
+    print_distances(g, bfs(g, 0))
+    pass