[PYTHON] Run matplotlib on a Windows Docker container
Introduction
Describes how to run matplotlib on a Windows Docker container. I tried Windows on Windows 10 Pro 64Bit version 2004. I also tried older versions. Docker Desktop can be WSL2 compliant or remains the same. Since it is in the Docker container, graphs such as matplotlib will not be displayed on the host side as it is. In order to display on the display on the host side (Windows side), I think that the container OS is linux, so it is necessary to start XServer on the Windows side and flow the display to that XServer.
Install VcXsrv
First, install * VcXsrv *. After installation, click * XL launch * under * VcXsrv * from the Windows menu. You can keep the default settings.
You should not need to configure * Firewall *. Also, if you run it on the same PC, it should not be necessary, but if you get an error due to authentication etc., please try the following.
- C: \ Program Files \ VcXsrv * etc. Open the file * X0.hosts * and add the IP address or host name of the host. This file cannot be edited without permission, so add permission in the properties etc. (By the way, you can edit it by opening it with VS Code)
Once started, you should see the VcXsrv X Server icon at the bottom right of the screen.
Right-click on the icon and select Applications xclock from the menu that appears, and xclock should start as shown below!
docker-compose.yml
Add the following to * docker-compose.yml * as a display setting.
docker-compose.yml
environment:
DISPLAY: host.docker.internal:0.0
Japanese display
If you need Japanese display, please add the following to * Dockerfile *.
- fonts-ipafont * is used, but of course another font can be used.
RUN apt-get update && apt-get install -y fonts-ipafont
Program that was run
It looks like this as a running program.
test.py
import numpy as np
import matplotlib.pyplot as plt
x = np.arange(-3, 3, 0.1)
y = np.sin(x)
fig = plt.plot(x, y)
plt.show()
matplotlib
When you execute the above program in Docker, the following graph will be displayed.
in conclusion
Did the graph display successfully? ?? That's all, we hope that you can contribute to improving the development efficiency of everyone.
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