[Python] How to forcefully trigger updates for dynamic plots in Google Colab without user...

I'm trying to create responsive dynamic plots in Google Colab, but I'm running into performance issues with the updates.

For a minimal example, I made a simple scatter plot of random values with a changing title. Initially, the plot updates smoothly for the first few frames, but it quickly starts to slow down or even freeze completely. A strange workaround I've discovered is that spam-clicking the figure keeps the updates running more consistently, roughly every second.

I'm wondering if there's a way to "simulate" this spam-clicking behavior or send some kind of event to force Colab to update the figure more reliably, without requiring direct user interaction. So far, I haven't found anything that works well.

I'm open to any suggestions, even hacky workarounds, as long as they help keep the plot updates responsive and prevent Colab from "putting the plot to sleep."

https://colab.research.google.com/drive/1n8xjt3ZtmeRmW5Usl_gcCoSHy1SGEWBy?usp=sharing

%pip install ipympl

from google.colab import output
output.enable_custom_widget_manager()
%matplotlib ipympl

import matplotlib.pyplot as plt
import numpy as np
import threading
import time
figure, ax = plt.subplots()
line = ax.plot([],[], 'o')
ax.set_xlim(0,100)
ax.set_ylim(0,1)

figure._canvas_callbacks._signals += ["fake_event"]
def wtf_event(*args,**kwargs):
print(flush=True, end="")
# print(args,kwargs)
figure.canvas.mpl_connect('fake_event', wtf_event)

def work1(figure,ax,line):
total = 100
for i in range(total):
X,Y = np.arange(100), np.random.rand(100) # data
figure.suptitle(i) # update title
line[0].set_data(X, Y) # update plot

figure.canvas.flush_events()
# figure.canvas.draw() # causes issues, if the delay is too long doesn't draw at all
figure.canvas.draw_idle()

# plt.pause(0.2) # throws errors
time.sleep(0.2) # actual display can take from instantly to 30 seconds (or more) in colab,
# colab also required cell to be "actively in focus" to update, repeatedly clicking on the plot "helps" it update (about 1 second)

figure.canvas.callbacks.process("fake_event")

thread = threading.Thread(target=work1, args=(figure,ax,line))
thread.start()

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