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def findBestPath(n, m, startRow, startColumn, endRow, endColumn, monsterRow, monsterColumn):
    def distance(x1, y1, x2, y2):
        return abs(x1 - x2) + abs(y1 - y2)
    
    def bfs(x, y):
        visited = [[False] * m for _ in range(n)]
        queue = [(x, y, 0)]
        visited[x][y] = True
        
        while queue:
            curr_x, curr_y, dist = queue.pop(0)
            
            for dx, dy in [(0, 1), (1, 0), (0, -1), (-1, 0)]:
                new_x, new_y = curr_x + dx, curr_y + dy
                
                if 0 <= new_x < n and 0 <= new_y < m and not visited[new_x][new_y]:
                    visited[new_x][new_y] = True
                    queue.append((new_x, new_y, dist + 1))
                    min_dist[new_x][new_y] = dist + 1
    
    min_dist = [[float('inf')] * m for _ in range(n)]
    min_dist[startRow][startColumn] = 0
    
    for i in range(len(monsterRow)):
        bfs(monsterRow[i], monsterColumn[i])

 left, right = 0, distance(startRow, startColumn, endRow, endColumn)
    result = 0
    
    while left <= right:
        mid = (left + right) // 2
        dp = [[False] * m for _ in range(n)]
        dp[startRow][startColumn] = True
        queue = [(startRow, startColumn)]
        
        while queue:
            curr_x, curr_y = queue.pop(0)
            
            for dx, dy in [(0, 1), (1, 0), (0, -1), (-1, 0)]:
                new_x, new_y = curr_x + dx, curr_y + dy
                
                if 0 <= new_x < n and 0 <= new_y < m and not dp[new_x][new_y] and min_dist[new_x][new_y] >= mid:
                    dp[new_x][new_y] = True
                    queue.append((new_x, new_y))
        
        if dp[endRow][endColumn]:
            result = mid
            left = mid + 1
        else:
            right = mid - 1
    
    return result