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| 1 | +# --------------------------------------------------------------- |
| 2 | +# Title: Stock Buy and Sell - Max One Transaction Allowed |
| 3 | +# |
| 4 | +# Problem: |
| 5 | +# Given an array prices[] representing the price of a stock on each day, |
| 6 | +# find the maximum profit achievable by performing at most one transaction. |
| 7 | +# (You must buy before you sell.) |
| 8 | +# |
| 9 | +# Example: |
| 10 | +# Input: prices = [7, 10, 1, 3, 6, 9, 2] |
| 11 | +# Output: 8 (Buy at 1, Sell at 9) |
| 12 | +# |
| 13 | +# Approach: |
| 14 | +# We traverse the list once, keeping track of: |
| 15 | +# - min_price_so_far: The lowest price encountered so far. |
| 16 | +# - max_profit: The maximum profit seen so far. |
| 17 | +# |
| 18 | +# For each price: |
| 19 | +# - Compute potential profit = current_price - min_price_so_far. |
| 20 | +# - Update max_profit if this profit is greater than the previous. |
| 21 | +# - Update min_price_so_far if a smaller price is found. |
| 22 | +# |
| 23 | +# Time Complexity: O(n) |
| 24 | +# Space Complexity: O(1) |
| 25 | +# --------------------------------------------------------------- |
| 26 | + |
| 27 | +def max_profit(prices): |
| 28 | + """ |
| 29 | + Calculate maximum profit from at most one buy-sell transaction. |
| 30 | +
|
| 31 | + Parameters: |
| 32 | + prices (list[int]): List of stock prices per day. |
| 33 | +
|
| 34 | + Returns: |
| 35 | + int: Maximum profit possible. Returns 0 if no profit is possible. |
| 36 | + """ |
| 37 | + |
| 38 | + # Edge case: no transaction possible if list is too short |
| 39 | + if not prices or len(prices) < 2: |
| 40 | + return 0 |
| 41 | + |
| 42 | + # Initialize minimum price as the first day's price |
| 43 | + min_price_so_far = prices[0] |
| 44 | + |
| 45 | + # Initialize maximum profit |
| 46 | + max_profit = 0 |
| 47 | + |
| 48 | + # Traverse price list starting from the second day |
| 49 | + for price in prices[1:]: |
| 50 | + # Update the minimum price seen so far |
| 51 | + min_price_so_far = min(min_price_so_far, price) |
| 52 | + |
| 53 | + # Calculate today's potential profit |
| 54 | + profit_today = price - min_price_so_far |
| 55 | + |
| 56 | + # Update max profit if today's profit is higher |
| 57 | + max_profit = max(max_profit, profit_today) |
| 58 | + |
| 59 | + return max_profit |
| 60 | + |
| 61 | + |
| 62 | +# --------------------------------------------------------------- |
| 63 | +# Example Usage (For quick testing) |
| 64 | +# --------------------------------------------------------------- |
| 65 | +if __name__ == "__main__": |
| 66 | + prices = [7, 10, 1, 3, 6, 9, 2] |
| 67 | + print("Stock Prices:", prices) |
| 68 | + print("Maximum Profit:", max_profit(prices)) # Expected Output: 8 |
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