通知代码会自动消失

Question

当我收到通知时，我希望它自动消失并且必须手动上传我，提前谢谢。

这里我附上代码，我在其中创建通知。我想要发生的是，当我收到通知时，我下车，我可以在屏幕上看到它，几秒钟后我就独自上去，而不必与之互动。

# -*- coding: utf-8 -*-
"""
Paraboloid tutorial from OpenMDAO documentation:
https://openmdao.readthedocs.io/en/latest/usr-guide/tutorials/paraboloid-tutorial.html

"""

# import print function from Python 3 if we are using Python 2
from __future__ import print_function

# import all the components we need from openmdao module
from openmdao.api import IndepVarComp, Component, Problem, Group, ScipyOptimizer

class Paraboloid(Component):
    """ Evaluates the equation f(x,y) = (x-3)^2 + xy + (y+4)^2 - 3 """

    def __init__(self):
        super(Paraboloid, self).__init__()

        self.add_param('x', val=0.0)
        self.add_param('y', val=0.0)

        self.add_output('f_xy', shape=1)

    def solve_nonlinear(self, params, unknowns, resids):
        """f(x,y) = (x-3)^2 + xy + (y+4)^2 - 3
        """

        x = params['x']
        y = params['y']

        unknowns['f_xy'] = (x-3.0)**2 + x*y + (y+4.0)**2 - 3.0

    def linearize(self, params, unknowns, resids):
        """ Jacobian for our paraboloid."""

        x = params['x']
        y = params['y']
        J = {}

        J['f_xy', 'x'] = 2.0*x - 6.0 + y
        J['f_xy', 'y'] = 2.0*y + 8.0 + x
        return J

# This if statement executes only if the script is run as a script, not if the
#   script is imported as a module. It's not necessary for this demo, but it
#   is good coding practice.
if __name__ == "__main__":

    # initiallize the overall problem
    top = Problem()

    # each problem has a root "group" that contains the component evaluating
    #   the objective function
    root = top.root = Group()

    # define components with the independent variables and their initial guesses
    root.add('p1', IndepVarComp('x', 3.0))
    root.add('p2', IndepVarComp('y', -4.0))
    
    # add the component that defines our objective function
    root.add('p', Paraboloid())

    # connect the components together
    root.connect('p1.x', 'p.x')
    root.connect('p2.y', 'p.y')
    
    # specify our driver for the problem (optional)
    top.driver = ScipyOptimizer()
    top.driver.options['optimizer'] = 'SLSQP'
    top.driver.options['disp'] = True  # don't display optimizer output

    # set up the problem
    top.setup()
    
    # run the optimization
    top.run()

    print(top['p.f_xy'])