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reconstruct-itinerary.py
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reconstruct-itinerary.py
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# Time: O(t! / (n1! * n2! * ... nk!)), t is the total number of tickets,
# ni is the number of the ticket which from is city i,
# k is the total number of cities.
# Space: O(t)
# Given a list of airline tickets represented by pairs of departure
# and arrival airports [from, to], reconstruct the itinerary in order.
# All of the tickets belong to a man who departs from JFK.
# Thus, the itinerary must begin with JFK.
#
# Note:
# If there are multiple valid itineraries, you should return the itinerary
# that has the smallest lexical order when read as a single string.
# For example, the itinerary ["JFK", "LGA"] has a smaller lexical
# order than ["JFK", "LGB"].
# All airports are represented by three capital letters (IATA code).
# You may assume all tickets may form at least one valid itinerary.
# Example 1:
# tickets = [["MUC", "LHR"], ["JFK", "MUC"], ["SFO", "SJC"], ["LHR", "SFO"]]
# Return ["JFK", "MUC", "LHR", "SFO", "SJC"].
# Example 2:
# tickets = [["JFK","SFO"],["JFK","ATL"],["SFO","ATL"],["ATL","JFK"],["ATL","SFO"]]
# Return ["JFK","ATL","JFK","SFO","ATL","SFO"].
# Another possible reconstruction is ["JFK","SFO","ATL","JFK","ATL","SFO"].
# But it is larger in lexical order.
import collections
class Solution(object):
def findItinerary(self, tickets):
"""
:type tickets: List[List[str]]
:rtype: List[str]
"""
def route_helper(origin, ticket_cnt, graph, ans):
if ticket_cnt == 0:
return True
for i, (dest, valid) in enumerate(graph[origin]):
if valid:
graph[origin][i][1] = False
ans.append(dest)
if route_helper(dest, ticket_cnt - 1, graph, ans):
return ans
ans.pop()
graph[origin][i][1] = True
return False
graph = collections.defaultdict(list)
for ticket in tickets:
graph[ticket[0]].append([ticket[1], True])
for k in graph.keys():
graph[k].sort()
origin = "JFK"
ans = [origin]
route_helper(origin, len(tickets), graph, ans)
return ans