Here’s a clean version you can use:

Short Question:
How do you design a data structure to efficiently track and retrieve the first non-repeating character in a stream?

Description:
In many data stream problems, characters arrive one by one, and we need to continuously determine the first non-repeating character at any given point.

The challenge is to design a data structure that:

• Supports real-time updates as new characters arrive

• Efficiently tracks frequencies of characters

• Quickly returns the first character that has appeared only once so far

A brute-force approach would re-scan the entire stream after each insertion, which is inefficient. Instead, we need an optimized approach using a combination of data structures to maintain order and frequency.

Approach:
Use:

• A hash map to store frequency of each character

• A queue to maintain insertion order

Python Code:

from collections import deque

class FirstNonRepeating:
    def __init__(self):
        self.freq = {}
        self.queue = deque()

    def add(self, char):
        # Update frequency
        self.freq[char] = self.freq.get(char, 0) + 1
        
        # Add to queue
        self.queue.append(char)
        
        # Remove repeating characters from front
        while self.queue and self.freq[self.queue[0]] > 1:
            self.queue.popleft()

    def get_first_non_repeating(self):
        return self.queue[0] if self.queue else None


# Example usage
stream = FirstNonRepeating()

for ch in "aabcbd":
    stream.add(ch)
    print(stream.get_first_non_repeating())