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This approach leverages an array to manage the count of available parking slots for each type of car. The array indices correspond to the car types: index 0 for big cars, index 1 for medium, and index 2 for small. The addCar function decrements the corresponding index if space is available.
Time Complexity: O(1) for each addCar operation as we are directly accessing an array element.
Space Complexity: O(1) as only a fixed-size array is used.
1class ParkingSystem:
2 def __init__(self, big: int, medium: int, small: int):
3 self.slots = [big, medium, small]
4
5 def addCar(self, carType: int) -> bool:
6 if self.slots[carType - 1] > 0:
7 self.slots[carType - 1] -= 1
8 return True
9 return FalseThe Python implementation uses a list to track the available parking slots for each car type. The addCar method updates the count for the corresponding slot, using list indexing to access the correct slot.
This method uses distinct variables to handle each type of car's parking slots. This approach makes the code very clear for small data sets. While this isn't necessarily more efficient than the array method for this particular problem, it offers an alternative for simple systems where explicit clarity is beneficial.
Time Complexity: O(1) for checking and updating.
Space Complexity: O(1) as three variables track the state.
1
This Python variant uses distinct attributes for managing parking spaces. Using conditional statements, addCar checks and updates respective attribute values.