Set up a grpc4bmi server to run a containerized version of the Basic Model Interface Python example.
Build this example locally with:
docker build --tag bmi-example-python-grpc4bmi .
The image is built on the mdpiper/bmi-example-python base image.
The OS is Linux/Ubuntu.
conda
and mamba
are installed in opt/conda
.
The base environment is activated,
and the Python BMI example is installed into it.
Use the grpc4bmi Docker client to access the BMI methods of the containerized model. Install grpc4bmi with pip:
pip install grpc4bmi
Then, in a Python session, access the Heat model in the image built above with:
from grpc4bmi.bmi_client_docker import BmiClientDocker
m = BmiClientDocker(image='bmi-example-python-grpc4bmi', image_port=55555, work_dir=".")
m.get_component_name()
del m # stop container cleanly
If the image isn't found locally, it's pulled from Docker Hub
(e.g., if you haven't already pulled it, try the mdpiper/bmi-example-python-grpc4bmi
image).
For a more in-depth example of running the Heat model from grpc4bmi, see the examples directory.
A versioned, multiplatform image built from this repository is hosted on Docker Hub at mdpiper/bmi-example-python-grpc4bmi. To tag, build, and push an update, run:
docker buildx build --platform linux/amd64,linux/arm64 -t mdpiper/bmi-example-python-grpc4bmi:<tagname> --push .
where <tagname>
is, e.g., 0.2
or latest
.
A user can pull this image from Docker Hub with:
docker pull mdpiper/bmi-example-python-grpc4bmi