This repository contains the code to demonstrate how to interact with the Station application of Railway. It contains a simple Master and Station example.

The following folders are used by Station to write to and read from the docker application. The format of the input and output text can be any format and is free to be implemented by the Train creator The tasks information is a fixed JSON format.

• INPUT_PATH = '/opt/input.txt'
• OUTPUT_PATH = '/opt/output.txt'
• COMPLETED_TASK_PATH = '/opt/completed-client-tasks.json'
• NEW_TASK_PATH = '/opt/new-client-tasks.json'

The master algorithm must be triggered to combine information from the different station algorithms. The completed tasks JSON is always provided (even on the first run) and will contain the in and output of every Station task

The station algorithm contains the code that will be run to process the local data. The result can never be any identifiable data as it is returned to the server/master algorithm.

• copy this repository to your own.
• use the StationInterface to read and write output.
• use the simulateMasterAndStation as an example how to debug your algorithm.

use these steps to manage a new train container locally

• using your preferred terminal to go to the root of the repository and use the following commands

• run "docker build --no-cache -t test_train ."

• run "docker run -d -it --name=test_train test_train"

• docker exec -it test_train /bin/bash

• docker cp ./src/. test_train:/app

• docker stop test_train

• docker rm test_train

• install anaconda for your OS (https://www.anaconda.com/distribution/)
• run "conda install -c conda-forge jupyterlab" in the anaconda terminal