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Find Shortest Word Edit Path in python


Shortest path via two intermediate pointsGoogle FooBar Level 3 - Shortest path to 14 sum challenge (part 2)Shortest path around a set of pointsShortest path challengeShortest path to transform one word into anotherDijkstra finding shortest path satisfying given constraintsFind The Duplicates using binarySearch pythonFind the shortest path between two points in a 2D matrix with obstaclesPython A Star with fewest turns and shortest path variations













0












$begingroup$


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)








share









$endgroup$
















    0












    $begingroup$


    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)








    share









    $endgroup$














      0












      0








      0





      $begingroup$


      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)








      share









      $endgroup$




      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)






      python interview-questions





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