Getting started

Dependencies

All required and optional dependencies can be found in pyproject.toml.

Installation

The latest stable release of ML-PEG, including its dependencies, is installable from PyPI by running:

python3 -m pip install ml-peg

To get all the latest changes, ML-PEG can also be installed from GitHub:

python3 -m pip install git+https://github.com/ddmms/ml-peg.git

Running the application

You can use Docker or Podman to build and/or run the ML-PEG app yourself.

Tip

The commands below will assume you are using Docker. To use Podman, replace docker with podman, e.g. podman pull, podman build, and podman run.

A Docker image with the latest changes can be pulled from the GitHub container registry, following the command that can be found under this repository’s packages.

Note

Currently, this repository only contains images for the linux/amd64 platform. On MacOS with ARM silicon, this can often still be run by setting --platform linux/amd64 when using docker run.

Alternatively, to build the container yourself, you can use the Dockerfile provided. From the ml-peg directory, run:

docker build -t ml-peg-app -f containers/Dockerfile .

Once built, you can mount your current application data and start the app by running:

docker run --volume ./ml_peg/app/data:/app/ml_peg/app/data  --publish 8050:8050 ml-peg-app

Tip

Ensure ml_peg/app/data is populated with results before running the container.

A compressed zip file containing the current live data can be found at http://s3.echo.stfc.ac.uk/ml-peg-data/app/data/data.tar.gz.

This may also be downloaded through the command line using:

ml_peg download --key app/data/data.tar.gz  --filename data.tar.gz

Alternatively, you can use the compose.yml file provided, via Docker Compose:

docker compose -f containers/compose.yml up -d

The app should now be accessible at http://localhost:8050.

Reporting a website bug

Use Report a bug in the app header to prepare a GitHub issue with page and settings details. Optionally capture the page and mark the problem area.

Select Open GitHub issue to open a prefilled Website bug issue form, labelled automatically, then review and submit using your GitHub account. Large page details are shortened automatically, with counts of omitted entries. Captured screenshots download separately. Drag the file into the Screenshots field to attach it, or attach your own screenshot directly on GitHub.