input: 
  def solve_linear_programming_problem(objective_function: List[float], constraints: List[List[float]], rhs: List[float], maximization: bool) -> List[float]:
      """Solves a linear programming problem using the Simplex method in Python. The problem is defined by its objective function coefficients, constraints coefficients, right-hand side (RHS) values of constraints, and whether it is a maximization or minimization problem.
      >>> solve_linear_programming_problem([3.0, 2.0], [[1.0, 0.0], [0.0, 1.0], [1.0, 1.0]], [4.0, 5.0, 9.0], True)
      [4.0, 5.0]
      >>> solve_linear_programming_problem([-1.0, -2.0], [[1.0, 1.0], [2.0, 1.0]], [2.0, 5.0], False)
      [3.0, -1.0]
      """
  
output:     from scipy.optimize import linprog
  
      if maximization:
          objective_function = [-x for x in objective_function]
  
      result = linprog(objective_function, A_ub=constraints, b_ub=rhs, method='simplex')
  
      if result.success:
          return result.x
      else:
          raise ValueError("The linear programming problem could not be solved.")