Shiny-Server on Docker for ARM with Python Support

This Docker image builds on shiny-server-arm-docker and adds the following features:

• python3.11: using python3.11.6
• Common data handling and visualization packages:
  • python:
    • shiny : for running python shiny apps
    • plotnine : ggplot for python
    • seaborn : plotting
    • plotly : interactive visualization
    • scikit-learn : statistical analysis
    • pyarrow : for reading data stored in parquet files (better alternative to csv)
  • R:
    • tidyverse : data science
    • gt : great looking tables
    • gtExtras : additional features for gt
    • ggimage : add images to ggplot
    • ggtext : modifying text in ggplot
    • scales : axis scales for ggplot

Installation

Clone this repo and enter the directory:

git clone https://github.com/sravanpannala/shiny-server-arm-python ./shiny-server
cd shiny-server

Run docker compose

docker-compose up -d

The server will be available at:

http://localhost:3838/

You can change the port in docker-compose.yml

ports:
      - {your_port_number}:3838

Usage

Installing libraries

Libraries can be installed by modifying the init.sh file under shiny-server/conf. It contains and will execute these commands:

py3.11 install package1 package2 .........
R -e "install.packages(c('lib1','lib2',...))

command the first time the container is started. Simply add the libraries you wish installed there. In order to avoid installing the same libraries on each restart, the script generates an init_done file and will not run if the file is present on the system. To add additional libraries in subsequent runs, delete the init_done file and add the new libraries to init.sh as before. Please note that installed libraries will persist between restarts as long as the container image is not removed or recreated.

Adding and configuring apps

Apps can be added to the ~/shiny-server/apps folder and will be loaded into shiny-server. There are four example apps included, 3 in python and 1 in R. If you followed the steps so far, the apps should be accessible at these urls:

• Py-basic-app: Running at http://localhost:3838/Py-basic-app
• Py-dashboard: Running at http://localhost:3838/Py-dashboard
• Py-multi-page: Running at http://localhost:3838/Py-multi-page
• R-ggplot: Running at http://localhost:3838/R-ggplot

You can add your own app by copying it over to the folder shiny-server/apps, where it will be available under http://localhost:3838/yourappfolder. You can add a configuration file for each app under shiny-server/apps/yourappfolder/.shiny_app.conf.

Troubleshooting

If you run into any trouble along the way, it might be due to permission problems. First, try making the init.sh script executable:

chmod +x ~/shiny-server/conf/init.sh

If the issue is not solved, you can also try running the following command:

chmod -R 777 ~/shiny-server/

Configuring shiny-server

Shiny servers' configuration file can be found under shiny-server/conf/shiny-server.conf. The default settings should be sufficient, however you can also modify it according to your needs. The documentation of shiny-server is always a good place to start, when you want to tune your installation.

Slimmer Options:

There are three versions of the image, tagged and snapshotted at various stages in the build process. The images can be found at dockerhub. Here are the images in the increasing order of size:

• shiny-server-arm-python:python: This image comes only with python support along with R and no packages.
• shiny-server-arm-python:pypackages: This image comes with only python packages instaled and no R packages.
• shiny-server-arm-python:latest: Normal image with all features. Installed by default.

If you want to change the image you want to install, you can do it in the docker-compose.yml, by changing the tag name:

image: sradjoker/shiny-server-arm-python:{tag}

Build Instructions

This image can be build on an ARM machine by running the following code in this directory:

docker build -t shiny-server .

docker build command uses the provided Dockerfile to build the image. You can also customize your image by editing the dockerfile before building it.

Acknowledgements

Further instructions and resources are available shiny-server-arm-docker repo. I suggest that you read the readme file in that repo carefully. This image is just a custom fork of that docker image suited to my purposes. All the credit goes to hvalev who is the maintainer of shiny-server-arm-docker].

Resources

• shiny-server-arm-docker: orginal source of this docker image
• Python Configuration section of Shiny documentation
• Shiny Python documentation
• Shiny Server documentation