Skip to content
gRPC wrapper for model with a Basic modeling interface
Python C++ CMake Other
Branch: master
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Type Name Latest commit message Commit time
Failed to load latest commit information.
bmi @ 5647424 Swapped cpp submodule for csdms bmi submodule Jul 11, 2019
cpp fix install of c++ headers Dec 17, 2019
docs Update compile instructions for grpc4bmi in c++ Jul 18, 2019
proto/grpc4bmi Update proto, var location retrun should be singular Jul 11, 2019
.gitignore Added makefile + run protoc with grpc v1.14.1 instead of master Aug 27, 2018
CITATION.cff Update CITATION.cff Nov 19, 2019
Dockerfile Added docker file for C bindings. Fixed typos. Mar 28, 2019
LICENSE Added sonarcloud for Python Jul 18, 2019
requirements.txt Make long description markdown Nov 19, 2019

DOI Build Status Documentation Status Quality Gate Status Coverage



This software allows you to wrap your BMI implementation ( in a server process and communicate with it via the included python client. The communication is serialized to protocol buffers by GRPC ( and occurs over network ports.


Optionally, create your virtual environment and activate it, Then, run

pip install grpc4bmi

on the client (python) side. If your server model is implemented in Python, do the same in the server environment (e.g. docker container). If the model is implemented in R, run instead

pip install grpc4bmi[R]

in the server environment. For bleeding edge version from GitHub use

pip install git+

Finally if the model is implemented in C or C++, clone this git repo and run

make ; make install

in the cpp folder.


Model written in Python

For inspiration look at the example in the test directory. To start a server process that allows calls to your BMI implementation, type

run-bmi-server --name <PACKAGE>.<MODULE>.<CLASS> --port <PORT> --path <PATH>

where <PACKAGE>, <MODULE> are the python package and module containing your implementation, <CLASS> is your bmi model class name, <PORT> is any available port on the host system, and optionally <PATH> denotes an additional path that should be added to the system path to make your implementation work. The name option above is optional, and if not provided the script will look at the environment variables BMI_PACKAGE, BMI_MODULE and BMI_CLASS. Similarly, the port can be defined by the environment variable BMI_PORT. This software assumes that your implementation constructor has no parameters.

Model written in C/C++ (beta)

Create an executable along the lines of cpp/ You can copy the file and replace the function

Bmi* create_model_instance()
    /* Return your new BMI instance pointer here... */

with the instantiation of your model BMI. The model needs to implement the csdms BMI for C, but you may also implement our more object-oriented C++ interface BmiCppExtension.

Model written in R

The grpc4bmi Python package can also run BMI models written in R if the model is a subclass of AbstractBmi See for instruction on R and Docker.

Run the R model a server with

run-bmi-server --lang R [--path <R file with BMI model>] --name [<PACKAGE>::]<CLASS> --port <PORT>

For example with WALRUS use

run-bmi-server --lang R --path ~/git/eWaterCycle/grpc4bmi-examples/walrus/walrus-bmi.r --name WalrusBmi --port 55555

The client side

The client side has only a Python implementation. The default BMI client assumes a running server process on a given port.

from grpc4bmi.bmi_grpc_client import BmiClient
import grpc
mymodel = BmiClient(grpc.insecure_channel("localhost:<PORT>"))
print mymodel.get_component_name()
...further BMI calls...

The package contains also client implementation that own the server process, either as a python subprocess or a docker image or a singularity image running the run-bmi-server script. For instance

from grpc4bmi.bmi_client_subproc import BmiClientSubProcess
mymodel = BmiClientSubProcess(<PACKAGE>.<MODULE>.<CLASS>)

will automatically launch the server in a sub-process and

from grpc4bmi.bmi_client_subproc import BmiClientDocker
mymodel = BmiClientDocker(<IMAGE>,<PORT>)

will launch a docker container, assuming that a GRPC BMI server will start and exposes the port <PORT>.

from grpc4bmi.bmi_client_singularity import BmiClientSingularity
mymodel = BmiClientSingularity(<IMAGE>,<PORT>)

will launch a singularity container, assuming that a GRPC BMI server will start and exposes the port <PORT>.

Development: generating the grpc code

When developers change the proto-file, it is necessary to install grpc tools python packages in your python environment:

pip install -r requirements.txt
pip install -e .
# For R integration also install the R extras with
pip install -e .[R]

and install the C++ runtime and protoc command as described in After this, simply executing the script should do the job.

Future work

More language bindings are underway.

You can’t perform that action at this time.