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Destination City

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Statistics

Time Spent Coding
2 minutes

Time Complexity
O(n) - In the worst case, every element in the input list will be visited twice, but constant multiples of n do not increase the growth rate, resulting in the O(n) time complexity.

Space Complexity
O(n) - In the worst case, every element in the input list will be stored twice, but constant multiples of n do not increase the growth rate, resulting in the O(n) space complexity.

Runtime Beats
99.93% of other submissions

Memory Beats
89.62% of other sumbissions

Explanation

The comments explain the program

Data Structures Used

Hash Table (Set) - An unordered container of non-repeating values.

Visual Examples
An array being transformed into a set, click to view

Solution

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class Solution:
    def destCity(self, paths: List[List[str]]) -> str:
        # Initialize sets to store all starting and ending cities
        startings = set()
        endings = set()
        
        # Fill sets with corresponding elements from the input list
        for s, e in paths:
            startings.add(s)
            endings.add(e)

        # Iterate through all ending cities until one is not found within the starting cities set
        for e in endings:
            if e not in startings:
                return e
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Unique Number of Occurrences

Relative Sort Array