Bipartition- Jenny L C17 Otters

graphs/possible_bipartition.py

@@ -1,12 +1,49 @@
-# Can be used for BFS
-from collections import deque 
+# The graph is stored in an adjacency dictionary where each key
+# represents an item in the graph and each value in the dictionary
+# corresponds to a list of edges from the key
 
+# Can be used for BFS: from collections import deque
 def possible_bipartition(dislikes):
     """ Will return True or False if the given graph
         can be bipartitioned without neighboring nodes put
         into the same partition.
         Time Complexity: ?
         Space Complexity: ?
     """
-    pass
+    if dislikes == {}:
+        return True
+    grouped_dogs = {dog: 'TBD' for dog in dislikes} 
+
+    # BFS:
+    dogs_visited = set()
+    dog_list = [dog for dog in dislikes]
+    start_dog = dog_list[-1]
+
+    grouped_dogs[start_dog] = 'group A'
+    queue = [start_dog]  # FIFO
+
+    while len(dogs_visited) != len(dislikes): # this is for when run into dog with no neighbors/edges
+        while queue:
+            current_dog = queue.pop(-1) 
+            dogs_visited.add(current_dog)
+            if current_dog in dog_list:
+                dog_list.remove(current_dog)
+            for foe_dog in dislikes[current_dog]: 
+                if grouped_dogs[foe_dog] == 'TBD':
+                    if grouped_dogs[current_dog] == 'group A':
+                        grouped_dogs[foe_dog] = 'group B'
+                    else:
+                        grouped_dogs[foe_dog] = 'group A'
+                if grouped_dogs[foe_dog] == grouped_dogs[current_dog]:
+                    return False
+
+                if foe_dog not in dogs_visited:
+                    queue.append(foe_dog)
+
+            if not queue and len(dog_list) != 0:
+                next_dog = dog_list.pop()
+                queue.append(next_dog)
+    return True
+
+