Vwwxrf

Find the Shortest Word Edit Path

I was given this problem from an interview. 
#Given two words source and target, and a list of words words,
#find the length of the shortest series of edits that transforms source to target. 
#Each edit must change exactly one letter at a time, and each 
#intermediate word (and the final target word) must exist in words.

If the task is impossible, return -1.

Examples:

source = "bit", target = "dog" words = ["but", "put", "big", "pot",
"pog", "dog", "lot"]

output: 5 explanation: bit -> but -> put -> pot -> pog -> dog has 5
transitions. source = "no", target = "go" words = ["to"]

output: -1

def one_letter_difference(current_word, next_word):
 count = 0
 for i in range(len(current_word) -1):

 if current_word[i] != next_word[i]:
 count += 1;
 if count == 1:
 return True
 else:
 return False

def shortestWordEditPath(source, target, words):
 """
 @param source: str
 @param target: str
 @param words: str[]
 @return: int

 Input: source = "bit", target = "dog"
 words = ["but", "put", "big", "pot", "pog", "dog", "lot"]

 Output: 5
 explanation: 
 1 -> 1 -> 1 -> 1 -> 1
 (source) bit -> but -> put -> pot -> pog -> dog (target) 
 has minimum of 5 transitions 
 """
 graph = 

 for i in range(-1, len(words)):
 if i == -1:
 current_word = source
 else:
 current_word = words[i]
 graph[current_word] = []
 for word in range(len(words)):
 next_word = words[word]
 if one_letter_difference(current_word, next_word):
 graph[current_word].append(next_word)

 #perform BFS
 queue = collections.deque()
 seen = set() # visited words
 queue.append([source, 1])
 seen.add(source)

 while len(queue) > 0:
 current, distance = queue.popleft()
 if current == target: return distance
 for neighbor in graph[current]:
 if neighbor not in seen:
 queue.append([neighbor, distance +1])
 seen.add(neighbor)
 return -1

source = "bit"
target = "dog"
words = ["but", "put", "big", "pot", "pog", "dog", "lot"]
test = shortestWordEditPath(source, target,words)
print(test)