input: def findMinimumPath(grid, length):
      """
      Consider a grid with N rows and N columns where N >= 2, and a positive integer length.
      Each grid cell contains a value, and every integer from 1 to N * N appears exactly once in the grid.
  
      Your task is to determine the smallest path of a specified length within the grid. The path can begin on any cell, and with each step, you can move to any adjacent cell (i.e., cells that share an edge).
  
      Note that a path of a specified length implies visiting that number of cells (though they may not necessarily be unique). You must remain within the grid bounds.
  
      A path X (of the required length) is considered smaller than path Y (of the same length) if, after creating ordered lists of the cell values that X and Y traverse (denoted as list_X and list_Y), we determine that list_X is lexicographically less than list_Y. This occurs if there exists an index i (1 <= i <= length) such that list_X[i] < list_Y[i] and for any index j (1 <= j < i), list_X[j] = list_Y[j].
  
      It is ensured that the solution is singular and unique. Return an ordered list of values from the cells that comprise the minimum path.
  
      Examples:
  
          Input: grid = [[1,2,3], [4,5,6], [7,8,9]], length = 3
          Output: [1, 2, 1]
  
          Input: grid = [[5,9,3], [4,1,6], [7,8,2]], length = 1
          Output: [1]
      """
output:     from itertools import product
  
      def dfs(x, y, path):
          if len(path) == length:
              paths.append(path)
              return
          for dx, dy in [(-1, 0), (1, 0), (0, -1), (0, 1)]:
              nx, ny = x + dx, y + dy
              if 0 <= nx < n and 0 <= ny < n:
                  dfs(nx, ny, path + [grid[nx][ny]])
  
      n = len(grid)
      paths = []
  
      for i, j in product(range(n), repeat=2):
          dfs(i, j, [grid[i][j]])
  
      return min(paths)