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Automatically started kernels in jupyterlab break matplotlib

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评估

难度
4/5
预计耗时
3-5 天
新手友好度
30/100
Issue 类型
缺陷
描述清晰度
基本清楚
活跃度
停滞
技术栈
jupyter-notebook, matplotlib, numpy
领域
backend, frontend

调研方向

首先,使用列出的 conda 环境、jupyter lab%matplotlib widget 示例重现该问题。比较重新打开 notebook 后的 kernel 状态与使用 Kernel > Shut Down Kernel 和 Kernel > Restart Kernel 后的状态;当重新打开的 notebook 能够渲染图表,且没有黑色输出或 No such comm 警告时,即表示完成。

由索引模型根据 Issue 内容生成。

描述

When a jupyterlab server is shut down, it remembers which files were open the next time it starts. When the jupyterlab server is restarted, it opens those files and starts a kernel for each one. These kernels are cursed. If %matplotlib widget is used in any of these open files, matplotlib will show a black image instead of the expected plot. Errors like [IPKernelApp] WARNING | No such comm: fcef8c0be3a345e493e771adbbb0df16 appear in the server's standard out. Restarting the kernel does not help. The kernel must be shut down and then restarted. Only then will the notebook display plots correctly.

How to reproduce

  1. Create a new conda environment with jupyterlab and matplotlib installed and start the server.
conda create -n temp -c conda-forge jupyterlab==1.0.9 matplotlib==3.1.1 ipympl==0.3.3
conda activate temp
jupyter labextension install @jupyter-widgets/jupyterlab-manager
jupyter lab
  1. Create a new notebook in JupyterLab and leave it open.

  2. Shutdown the server and restart it. Note that the new file has a running kernel.

  3. Put some plotting code using %matplotlib widget in the notebook and run it. A black box will appear instead of a plot. Error messages will stream in the console.

%matplotlib widget
import numpy as np
import matplotlib.pyplot as plt

x = np.linspace(0, 1, 500)
y = np.sin(4 * np.pi * x) * np.exp(-5 * x)

fig, ax = plt.subplots()

ax.fill(x, y, zorder=10)
ax.grid(True, zorder=5)
plt.show()
  1. Navigate to Kernel > Shut Down Kernel and then Kernel > Restart Kernel. Run the notebook again and the plots will appear.
主要语言
Jupyter Notebook
星标
1.7k
派生
234
PR 合并指标
30 天内没有已合并 PR

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  2. 在 Issue 下留言说明你要接手 —— 这能避免两个人做同样的事。
  3. Fork 仓库,在一个分支上完成修改。
  4. 提交 Pull Request,并在描述里引用这个 Issue 编号。

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