How to run multiple Python scripts and an executable files using Docker?

Question

I want to create a container that is contained with two Python packages as well as a package consist of an executable file.

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Here\'s my main package (dockerize

Answer 1

Best practice is to launch these as three separate containers. That's doubly true since you're taking three separate applications, bundling them into a single container, and then trying to launch three separate things from them.

Create a separate Dockerfile in each of your project subdirectories. These can be simpler, especially for the one that just contains a compiled binary

# execproject/Dockerfile
FROM ubuntu:18.04
WORKDIR /app
COPY . ./
CMD ["./gowebapp"]

Then in your docker-compose.yml file have three separate stanzas to launch the containers

version: '3'
services:
  pythonic_project1:
    build: ./pythonic_project1
    ports:
      - 8008:8008
    env:
      PY2_URL: 'http://pythonic_project2:8009'
      GO_URL: 'http://execproject:8010'
  pythonic_project2:
    build: ./pythonic_project2
  execproject:
    build: ./execproject

If you really can't rearrange your Dockerfiles, you can at least launch three containers from the same image in the docker-compose.yml file:

services:
  pythonic_project1:
    build: .
    workdir: /app/pythonic_project1
    command: ./__main__.py
  pythonic_project2:
    build: .
    workdir: /app/pythonic_project1
    command: ./__main__.py

There's several good reasons to structure your project with multiple containers and images:

• If you roll your own shell script and use background processes (as other answers have), it just won't notice if one of the processes dies; here you can use Docker's restart mechanism to restart individual containers.
• If you have an update to one of the programs, you can update and restart only that single container and leave the rest intact.
• If you ever use a more complex container orchestrator (Docker Swarm, Nomad, Kubernetes) the different components can run on different hosts and require a smaller block of CPU/memory resource on a single node.
• If you ever use a more complex container orchestrator, you can individually scale up components that are using more CPU.