# MIP Solve Example

The following example showcases how to build a mathematical optimization problem
using MathOpt and make a remote solve using the OR API. To obtain an API Key,
follow the [setup guide](https://developers.google.com/optimization/service/setup) first. MathOpt is available as part of [OR-Tools
since release 9.9](https://github.com/google/or-tools/releases/tag/v9.9). Visit the [install guide](https://developers.google.com/optimization/install) for more information.


    # solve_math_opt_model_via_http.py

    """Example of solving a MathOpt model through the OR API.

    The model is built using the Python API, and the corresponding proto is
    serialized to JSON to make the HTTP request.
    """

    from collections.abc import Sequence

    from absl import app
    from absl import flags

    from ortools.math_opt.python import mathopt
    from ortools.math_opt.python.ipc import remote_http_solve

    _API_KEY = flags.DEFINE_string("api_key", None, "API key for the OR API")

    def request_example() -> None:
      """Run example using MathOpt `remote_http_solve` function."""
      # Set up the API key.
      api_key = _API_KEY.value
      if not api_key:
        print(
            "API key is required. See"
            " https://developers.google.com/optimization/service/setup for"
            " instructions."
        )
        return

      # Build a MathOpt model
      model = mathopt.Model(name="my_model")
      x = model.add_binary_variable(name="x")
      y = model.add_variable(lb=0.0, ub=2.5, name="y")
      model.add_linear_constraint(x + y <= 1.5, name="c")
      model.maximize(2 * x + y)
      try:
        result, logs = remote_http_solve.remote_http_solve(
            model,
            mathopt.SolverType.GSCIP,
            mathopt.SolveParameters(enable_output=True),
            api_key=api_key,
        )
        print("Objective value: ", result.objective_value())
        print("x: ", result.variable_values(x))
        print("y: ", result.variable_values(y))
        print("\n".join(logs))
      except remote_http_solve.OptimizationServiceError as err:
        print(err)

    def main(argv: Sequence[str]) -> None:
      del argv  # Unused.
      request_example()

    if __name__ == "__main__":
      app.run(main)