Compute Server Env constructor. Creates a client environment on a compute server. If all compute servers are at capacity, this command will cause a job to be placed in the compute server queue, and the command will return an environment once capacity is available.
Client environments have limited uses in the Python environment. You can use a client environment as an argument to the Model constructor, to indicate that a model should be constructed on a Compute Server, or as an argument to the global read function, to indicate that the result of reading the file should be place on a Compute Server.
logfilename: Name of the log file for this environment. Pass an an empty string if you don't want a log file.
computeServers: Comma-separated list of compute servers. Servers can be identified by name or by IP address.
port: Port number on compute server. Use the default value unless your server administrator has informed you that a different value should be used.
password: User password on compute server. Obtain this from your Compute Server administrator.
priority: Job priority on the compute server. Higher priority jobs are pulled from the job queue before lower priority jobs. A special value of 100 indicates that the job should run immediately.
timeout: Job queue timeout. After the specified timeout (in seconds) has elapsed, this command will give up and return a Gurobi exception. Use a negative value to indicate that the call should never timeout.
New environment object.
env = Env.ClientEnv("client.log", "server1.mycompany.com,server2.mycompany.com") m = read("misc07.mps", env) m.optimize()