I’m asking this question because I can’t solve one problem in Python/Django (actually in pure Python it’s ok) which leads to RuntimeError: tcl_asyncdelete async handler deleted by the wrong thread. This is somehow related to the way how I render matplotlib plots in Django. The way I do it is:

...
import matplotlib.pyplot as plt
...
fig = plt.figure()
...
plt.close()

I extremely minimized my code. But the catch is – even if I have just one line of code:

fig = plt.figure()

I see this RuntimeError happening. I hope I could solve the problem, If I knew the correct way of closing/cleaning/destroying plots in Python/Django.

By default matplotlib uses TK gui toolkit, when you’re rendering an image without using the toolkit (i.e. into a file or a string), matplotlib still instantiates a window that doesn’t get displayed, causing all kinds of problems. In order to avoid that, you should use an Agg backend. It can be activated like so —

import matplotlib
matplotlib.use('Agg')
from matplotlib import pyplot

For more information please refer to matplotlib documentation — http://matplotlib.org/faq/howto_faq.html#matplotlib-in-a-web-application-server

The above (accepted) answer is a solution in a terminal environment. If you debug in an IDE, you still might wanna use ‘TkAgg‘ for displaying data. In order to prevent this issue, apply these two simple rules:

  1. everytime you display your data, initiate a new fig = plt.figure()
  2. don’t close old figures manually (e.g. when using a debug mode)

Example code:

import matplotlib
matplotlib.use('TkAgg')
from matplotlib import pyplot as plt

fig = plt.figure()
plt.plot(data[:,:,:3])
plt.show()

This proves to be the a good intermediate solution under MacOS and PyCharm IDE.

If you don’t need to show plots while debugging, the following works:

import matplotlib
matplotlib.use('Agg')
from matplotlib import pyplot as plt

However, if you would like to plot while debugging, you need to do 3 steps:

1.Keep backend to ‘TKAgg’ as follows:

import matplotlib
matplotlib.use('TKAgg')
from matplot.lib import pyplot as plt

or simply

import matplotlib.pyplot as plt

2.As Fábio also mentioned, you need to add fig(no. #i)=plt.figure(no.#i) for each figure #i. As the following example for plot no.#1, add:

fig1 = plt.figure(1)
plt.plot(yourX,yourY)
plt.show()

3.Add breakpoints. You need to add two breakpoints at least, one somewhere at the beginning of your codes (before the first plot), and the other breakpoint at a point where you would like all plots (before to the second breakpoint) are plotted. All figures are plotted and you even don’t need to close any figure manually.

For me, this happened due to parallel access to data by both Matplotlib and by Tensorboard, after Tensorboard’s server was running for a week straight.

Rebotting tensorboard tensorboard --logdir . --samples_per_plugin images=100 solved this for me.

I encountered this problem when plotting graphs live with matplotlib in my tkinter application.

The easiest solution I found, was to always delete subplots. I found you didn’t need to instantiate a new figure, you only needed to delete the old subplot (using del subplot), then remake it.

Before plotting a new graph, make sure to delete the old subplot.
Example:

f = Figure(figsize=(5,5), dpi=100)
a = f.add_subplot(111)
(For Loop code that updates graph every 5 seconds):
    del a #delete subplot
    a = f.add_subplot(111) #redefine subplot

Finding this simple solution to fix this “async handler bug” was excruciatingly painful, I hope this helps someone else 🙂