#  ___________________________________________________________________________
#
#  Pyomo: Python Optimization Modeling Objects
#  Copyright 2017 National Technology and Engineering Solutions of Sandia, LLC
#  Under the terms of Contract DE-NA0003525 with National Technology and
#  Engineering Solutions of Sandia, LLC, the U.S. Government retains certain
#  rights in this software.
#  This software is distributed under the 3-clause BSD License.
#  ___________________________________________________________________________

import pickle
import types
try:
    import new
    new_available=True
except:
    new_available=False

import pyutilib.th as unittest
from pyomo.solvers.tests.models.base import test_models
from pyomo.solvers.tests.testcases import test_scenarios


#
# A function that returns a function that gets
# added to a test class.
#
@unittest.nottest
def create_test_method(model, solver, io,
                       test_case,
                       symbolic_labels):

    # Ignore expected failures?
    is_expected_failure = False

    def pickle_test(self):

        # Instantiate the model class
        model_class = test_case.model()

        # Create the model instance
        model_class.generate_model(test_case.testcase.import_suffixes)
        model_class.warmstart_model()

        load_solutions = (not model_class.solve_should_fail) and \
                         (test_case.status != 'expected failure')

        opt, status = model_class.solve(solver,
                                        io,
                                        test_case.testcase.io_options,
                                        test_case.testcase.options,
                                        symbolic_labels,
                                        load_solutions)
        m = pickle.loads(pickle.dumps(model_class.model))

        #
        # operate on a cloned model
        #
        instance1 = m.clone()
        model_class.model = instance1
        opt, status1 = model_class.solve(solver,
                                         io,
                                         test_case.testcase.io_options,
                                         test_case.testcase.options,
                                         symbolic_labels,
                                         load_solutions)
        inst, res = pickle.loads(pickle.dumps([instance1,status1]))

        #
        # operate on an unpickled model
        #
        # try to pickle then unpickle instance
        instance2 = pickle.loads(pickle.dumps(instance1))
        self.assertNotEqual(id(instance1),id(instance2))
        model_class.model = instance2
        opt, status2 = model_class.solve(solver,
                                         io,
                                         test_case.testcase.io_options,
                                         test_case.testcase.options,
                                         symbolic_labels,
                                         load_solutions)
        # try to pickle the instance and status,
        # then unpickle and load status
        inst, res = pickle.loads(pickle.dumps([instance2,status2]))

        #
        # operate on a clone of an unpickled model
        #
        instance3 = instance2.clone()
        self.assertNotEqual(id(instance2),id(instance3))
        model_class.model = instance3
        opt, status3 = model_class.solve(solver,
                                         io,
                                         test_case.testcase.io_options,
                                         test_case.testcase.options,
                                         symbolic_labels,
                                         load_solutions)
        # try to pickle the instance and status,
        # then unpickle and load status
        inst, res = pickle.loads(pickle.dumps([instance3,status3]))

    # Skip this test if the status is 'skip'
    if test_case.status == 'skip':
        def skipping_test(self):
            return self.skipTest(test_case.msg)
        return skipping_test

    # If this solver is in demo mode
    size = getattr(test_case.model, 'size', (None, None, None))
    for prb, sol in zip(size, test_case.demo_limits):
        if prb is None or sol is None:
            continue
        if prb > sol:
            def skipping_test(self):
                self.skipTest("Problem is too large for unlicensed %s solver" % solver)
            return skipping_test

    if is_expected_failure:
        @unittest.expectedFailure
        def failing_pickle_test(self):
            return pickle_test(self)
        # Return a test that is expected to fail
        return failing_pickle_test

    return pickle_test

cls = None

#
# Create test driver classes for each test model
#
driver = {}
for model in test_models():
    # Get the test case for the model
    case = test_models(model)

    # Create the test class
    name = "Test_%s" % model
    if new_available:
        cls = new.classobj(name, (unittest.TestCase,), {})
    else:
        cls = types.new_class(name, (unittest.TestCase,))
        cls.__module__ = __name__
    cls = unittest.category(*case.level)(cls)
    driver[model] = cls
    globals()[name] = cls
#
# Iterate through all test scenarios and add test methods
#
for key, value in test_scenarios(lambda c: c.test_pickling):
    model, solver, io = key
    cls = driver[model]
    # Symbolic labels
    test_name = "test_"+solver+"_"+io +"_symbolic_labels"
    test_method = create_test_method(model, solver, io, value, True)
    if test_method is not None:
        test_method = unittest.category('smoke','nightly',solver)(test_method)
        setattr(cls, test_name, test_method)
        test_method = None

    # Non-symbolic labels
    test_name = "test_"+solver+"_"+io +"_nonsymbolic_labels"
    test_method = create_test_method(model, solver, io, value, False)
    if test_method is not None:
        test_method = unittest.category('smoke','nightly',solver)(test_method)
        setattr(cls, test_name, test_method)
        test_method = None

# Reset the cls variable, since it contains a unittest.TestCase subclass.
# This prevents this class from being processed twice!
cls = None

if __name__ == "__main__":
    unittest.main()