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In this approach, we use a closure to maintain the state across multiple calls to the counter function. The closure lets us keep track of the last counted value between function calls.
Time Complexity: O(1) per call.
Space Complexity: O(1) for maintaining the state.
1def create_counterThis Python solution utilizes closures, where the counter function maintains its state using the nonlocal keyword to access and modify the variable n, which isn't local to the function itself. The inner counter function increments this value each time it is called and returns the current count.
This approach uses object-oriented programming to keep track of the counter's state across multiple invocations by encapsulating the state within a class instance.
Time Complexity: O(1) per call.
Space Complexity: O(1) for the instance state.
1class Counter:
2 def __init__(self, n):
3 self.count = n
4
5 def __call__(self):
6 current = self.count
7 self.count += 1
8 return currentThis Python solution utilizes a class where the count is maintained as an instance variable. Calling the instance returns the current count, increments it, and stores the new state.