https://github.com/csdms/bmi-example-c-grpc4bmi
Run the C BMI example through grpc4bmi
https://github.com/csdms/bmi-example-c-grpc4bmi
bmi c csdms docker grpc4bmi
Last synced: 4 months ago
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Run the C BMI example through grpc4bmi
- Host: GitHub
- URL: https://github.com/csdms/bmi-example-c-grpc4bmi
- Owner: csdms
- License: mit
- Created: 2024-09-05T16:40:55.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-09-25T23:46:12.000Z (8 months ago)
- Last Synced: 2025-09-26T01:25:27.109Z (8 months ago)
- Topics: bmi, c, csdms, docker, grpc4bmi
- Language: CMake
- Homepage: https://bmi.csdms.io
- Size: 23.4 KB
- Stars: 0
- Watchers: 5
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
[](https://bmi.readthedocs.io/)
[](https://doi.org/10.5281/zenodo.17204368)
[](https://github.com/csdms/bmi-example-c-grpc4bmi/actions/workflows/test.yml)
[](https://github.com/csdms/bmi-example-c-grpc4bmi/actions/workflows/release.yml)

# bmi-example-c-grpc4bmi
Set up a [grpc4bmi](https://grpc4bmi.readthedocs.io) server
to run a containerized version
of the [Basic Model Interface](https://bmi.readthedocs.io) (BMI)
[C example](https://github.com/csdms/bmi-example-c)
through Python.
## Build
There are two options for building this project:
1. from a base image, [source-base](./images/source-base/), where grpc and its dependent libraries, grpc4bmi, and the BMI C example are all built from source
1. from a base image, [conda-base](./images/conda-base/), where grpc and its dependent libraries are installed through conda-forge, the BMI C example is installed from a separate conda-based Docker image, and grpc4bmi is built from source
In each case, the grpc4bmi server is exposed through port 55555.
### source-base
Build this example locally with:
```
docker build --tag bmi-example-c-grpc4bmi images/source-base
```
The image is (temporarily) built on the [mdpiper/grpc4bmi](https://hub.docker.com/r/mdpiper/grpc4bmi) base image.
The OS is Linux/Ubuntu.
The C BMI example, grpc4bmi, and the grpc4bmi server are installed in `/usr/local`.
### conda-base
Build this example locally with:
```
docker build --tag bmi-example-c-grpc4bmi images/conda-base
```
The image is built on the [csdms/grpc4bmi](https://hub.docker.com/r/csdms/grpc4bmi) base image,
which is built on the [condaforge/miniforge3](https://hub.docker.com/r/condaforge/miniforge3) base image.
The OS is Linux/Ubuntu.
The C BMI example, grpc4bmi, and the grpc4bmi server are installed in `/opt/conda`.
## Run
Use the grpc4bmi Docker client to access the BMI methods of the containerized model.
Install with *pip*:
```
pip install grpc4bmi
```
Then, in a Python session, access the C *Heat* model in the image built above with:
```python
from grpc4bmi.bmi_client_docker import BmiClientDocker
m = BmiClientDocker(image='bmi-example-c-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., try the `csdms/bmi-example-c-grpc4bmi` image).
For more in-depth examples of running the *Heat* model through grpc4bmi,
see the [examples](./examples) directory.
## Developer notes
A versioned, multiplatform image built from the *conda-base* image in this repository is hosted on Docker Hub
at [csdms/bmi-example-c-grpc4bmi](https://hub.docker.com/r/csdms/bmi-example-c-grpc4bmi).
This image is automatically built and pushed to Docker Hub
with the [release](./.github/workflows/release.yml) CI workflow.
The workflow is only run when the repository is tagged.
To manually build and push an update, run:
```
docker buildx build --platform linux/amd64,linux/arm64 -t csdms/bmi-example-c-grpc4bmi:latest --push .
```
A user can pull this image from Docker Hub with:
```
docker pull csdms/bmi-example-c-grpc4bmi
```
optionally with the `latest` tag or with a version tag.
## Acknowledgment
This work is supported by the U.S. National Science Foundation under Award No. [2103878](https://www.nsf.gov/awardsearch/showAward?AWD_ID=2103878), *Frameworks: Collaborative Research: Integrative Cyberinfrastructure for Next-Generation Modeling Science*.