Plot windows with qt4 or qt5 as backend for the IPython console run very slowly.

Issue Report Checklist

• [ x] Searched the issues page for similar reports
• [x ] Read the relevant sections of the Spyder Troubleshooting Guide and followed its advice
• [x ] Reproduced the issue after updating with conda update spyder (or pip, if not using Anaconda)
• [x ] Could not reproduce inside jupyter qtconsole (if console-related)
• [x ] Tried basic troubleshooting (if a bug/error)
  • [x ] Restarted Spyder
  • [ x] Reset preferences with spyder --reset
  • [ x] Reinstalled the latest version of Anaconda
  • [x ] Tried the other applicable steps from the Troubleshooting Guide
• [x ] Completed the Problem Description, Steps to Reproduce and Version sections below

Problem Description

When I use either qt4 or qt5 as the backend for the IPython console, the plot that opens up in a new window runs extremely slowly. This is different than other bug reports I have seen because the kernel itself works fine for me.

I think this has to do with version 5 of ipykernel, because I downgraded to ipykernel 4.10.0 (and downgraded to Spyder 3) and the plot window worked fine. Then I upgraded to ipykernel 5 (while still using Spyder 3) and the plot windows became slow again.

What steps reproduce the problem?

1. Set qt4 or qt5 as the backend.
2. Try to plot anything. For this I just plotted a sin curve:

import matplotlib.pyplot as plt
import numpy as np
x = np.linspace(0, 4*np.pi, num=1000)
y = np.sin(x)
plt.plot(x, y)

What is the expected output? What do you see instead?

I expect a window which will respond to the cursor position in real time – instead it freezes up and takes several seconds to respond, even when exiting out.

Versions

• Spyder version: 4.1.4
• Python version: 3.7.7 64-bit
• Qt version: 5.9.6
• PyQt version: 5.9.2
• Operating System name/version: Windows 10 64-bit

Dependencies

# Mandatory:
atomicwrites >=1.2.0           :  1.4.0 (OK)
chardet >=2.0.0                :  3.0.4 (OK)
cloudpickle >=0.5.0            :  1.5.0 (OK)
diff_match_patch >=20181111    :  20200713 (OK)
intervaltree                   :  None (OK)
IPython >=4.0                  :  7.16.1 (OK)
jedi =0.17.1                   :  0.17.1 (OK)
nbconvert >=4.0                :  5.6.1 (OK)
numpydoc >=0.6.0               :  1.1.0 (OK)
paramiko >=2.4.0               :  2.7.1 (OK)
parso =0.7.0                   :  0.7.0 (OK)
pexpect >=4.4.0                :  4.8.0 (OK)
pickleshare >=0.4              :  0.7.5 (OK)
psutil >=5.3                   :  5.7.0 (OK)
pygments >=2.0                 :  2.6.1 (OK)
pylint >=1.0                   :  2.5.3 (OK)
pyls >=0.34.0;<1.0.0           :  0.34.1 (OK)
qdarkstyle >=2.8               :  2.8.1 (OK)
qtawesome >=0.5.7              :  0.7.2 (OK)
qtconsole >=4.6.0              :  4.7.5 (OK)
qtpy >=1.5.0                   :  1.9.0 (OK)
rtree >=0.8.3                  :  0.9.4 (OK)
sphinx >=0.6.6                 :  3.1.2 (OK)
spyder_kernels >=1.9.2;<1.10.0 :  1.9.2 (OK)
watchdog                       :  None (OK)
zmq >=17                       :  19.0.1 (OK)

# Optional:
cython >=0.21                  :  None (OK)
matplotlib >=2.0.0             :  3.2.2 (OK)
numpy >=1.7                    :  1.18.5 (OK)
pandas >=0.13.1                :  1.0.5 (OK)
scipy >=0.17.0                 :  1.5.0 (OK)
sympy >=0.7.3                  :  1.6.1 (OK)

[jjhelmus]

@anaconda-pkg-build, could you package ipykernel 5.3.4? We have received bug reports about this problem in the last weeks, which was solved in that version. Thanks!

ipykernel 5.3.4 packages are now available in defaults

[dalthviz]

Totally right @lucasmyers97 I think ipykernel 5.3.4 is not yet available in the default conda channel. For now, I suggest to work with the version 5.3.2 (the work around found) and try again to update ipykernel when the package is uploaded (probably in a couple of days). Sorry for the inconvenience 😕