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Visual Editor Installation

This document outlines an installation guide for using the workbench with its visual editor. See the codebase installation for how to install the codebase to be use-able in Python scripts.

Step 0: Install Docker

If you are unsure which variant of docker install, we recommend Docker Desktop to you.

  • On windows, you might have to toggle docker to use linux containers

    1. right-click the Docker Desktop icon in your status bar
    2. click the Switch to linux containers button
    • Windows: Switch to linux containers

Step 1: Download the docker-compose.yml

Download the docker-compose.yml file to your machine to a location of your choice.

This file tells docker how to orchestrate the containers required to run the workbench editor.

(In case you have already checked out the repository: You can use the docker-compose.yml directory in your git project instead)

Step 2: Start the workbench editor

Switch to a CLI (e.g. cmd) and change into the directory of the downloaded file. (If you are unsure where your file is: Under windows: Shift-right-click the folder containing the file and select Open in Terminal.)

Run the docker compose up command in the CLI.

In case you receive an error during connect error: Ensure Docker (Desktop) is running.

Step 3: Done

Open http://localhost:8080 in your browser. You might have to wait for the console to pause its output/the backend to be ready.

How to use your own data with the graphical interface:

By default, the docker setup mounts a own_data directory, which allows you to use your own input files. (Internally, they are mounted to examples/own_data.)

How to update the graphical interface:

Run docker compose pull, but Step 2 should update the images automatically.
Certain updates might require you to also update the docker-compose.yml file, in which case you will have to perform Steps 1 and 2 again.

How to reset the graphical interface:

In case the application fails to start after an update, etc.: Run docker compose down to reset the interface. Then continue with Step 2 to start the interface again

How to use a local codebase

In your docker-compose.yml file: Go to the services.py_runner.volumes key and uncomment/add the following lines:

services:
   py_runner:
      # ...
      volumes:
         - "./path/to/my/codebase/:/usr/src/app/codebase/"

Change the ./path/to/my/codebase/ path to point to codebase directory.

(Special case: If you are using the docker-compose.yml from the codebase's directory, uncomment the # option 1 lines instead.)

Now the container will start with your local codebase. After making changes to your local codebase, restart the py_runner container with docker compose restart py_runner to apply them.

In case you have modified the component signatures, you have to reset the stored components in the database: use the Reset page and then restart the py_runner container. The Runners page might help with dead runners.