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, will soon be 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¶
A Docker image of 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, and run:
docker build . -t ml-peg-app
Once built, you can mount your current directory and start the app by running:
docker run --volume .:/app --publish 8050:8050 ml-peg-app
Tip
Ensure ml_peg/app/data
is populated with results before running the container.
Alternatively, you can use the compose.yml file provided, via Docker Compose:
docker compose up -d
The app should now be accessible at http://localhost:8050.