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Proof of concept implementation of a CPLEX service implement in flask running in a docker container.
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IBMDecisionOptimization/docker_flask_service
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Simple CPLEX service and client implementation for Docker. The service is based on Python. It receives a model file and optionally a parameter file and then solves the model. The main purpose of this is to illustrate how one could build a simple service that solves optimization problems with CPLEX. To build the container run the following command from this directory (assuming $COSDIR points to a valid CPLEX installation): tar cvzf - --transform='s,^.*cplex/python/3.6/x86-64_linux/,,' \ $COSDIR/cplex/python/3.6/x86-64_linux/cplex \ ./service.py \ ./Dockerfile \ | \ docker build \ --tag=cplex/flask_service:12.9 \ --tag=cplex/flask_service:latest \ -f Dockerfile \ - Adapt the '12.9' and 'latest' tags depending on your needs and on the version of CPLEX you build with. After building the container you can start it with docker --rm -p 50010:5000 cplex/flask_service:12.9 The container listens on port 5000 and the above command line connects this to port 5000 on the local host. This is the default configuration used in client.py. To test the service in docker you can use the client.py script from this directory: python ./client.py model.lp The client reads the model, submits it to the service, solves it for 10 seconds (displaying some progress messages) and stops the solve.
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Proof of concept implementation of a CPLEX service implement in flask running in a docker container.
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