import threading
import unittest

import ray
from ray.tune import CheckpointConfig, register_trainable
from ray.tune.error import TuneError
from ray.tune.experiment import Experiment, _convert_to_experiment_list
from ray.tune.utils import diagnose_serialization


class ExperimentTest(unittest.TestCase):
    def tearDown(self):
        ray.shutdown()

    def setUp(self):
        def train_fn(config):
            for i in range(100):
                ray.tune.report(dict(timesteps_total=i))

        register_trainable("f1", train_fn)

    def testConvertExperimentFromExperiment(self):
        exp1 = Experiment(
            **{"name": "foo", "run": "f1", "config": {"script_min_iter_time_s": 0}}
        )
        result = _convert_to_experiment_list(exp1)
        self.assertEqual(len(result), 1)
        self.assertEqual(type(result), list)

    def testConvertExperimentNone(self):
        result = _convert_to_experiment_list(None)
        self.assertEqual(len(result), 0)
        self.assertEqual(type(result), list)

    def testConvertExperimentList(self):
        exp1 = Experiment(
            **{"name": "foo", "run": "f1", "config": {"script_min_iter_time_s": 0}}
        )
        result = _convert_to_experiment_list([exp1, exp1])
        self.assertEqual(len(result), 2)
        self.assertEqual(type(result), list)

    def testConvertExperimentJSON(self):
        experiment = {
            "name": {"run": "f1", "config": {"script_min_iter_time_s": 0}},
            "named": {"run": "f1", "config": {"script_min_iter_time_s": 0}},
        }
        result = _convert_to_experiment_list(experiment)
        self.assertEqual(len(result), 2)
        self.assertEqual(type(result), list)

    def testConvertExperimentIncorrect(self):
        self.assertRaises(TuneError, lambda: _convert_to_experiment_list("hi"))

    def testFuncTrainableCheckpointConfigValidation(self):
        """Raise an error when trying to specify checkpoint_at_end/checkpoint_frequency
        with a function trainable."""
        with self.assertRaises(ValueError):
            Experiment(
                name="foo",
                run="f1",  # Will point to a wrapped function trainable
                checkpoint_config=CheckpointConfig(checkpoint_at_end=True),
            )
        with self.assertRaises(ValueError):
            Experiment(
                name="foo",
                run="f1",
                checkpoint_config=CheckpointConfig(checkpoint_frequency=1),
            )
        with self.assertRaises(ValueError):
            Experiment(
                name="foo",
                run=lambda config: 1,
                checkpoint_config=CheckpointConfig(checkpoint_at_end=True),
            )

    def testInvalidExperimentConfig(self):
        with self.assertRaises(ValueError):
            Experiment(name="foo", run="f1", config="invalid")

        class InvalidClass:
            def to_dict(self):
                return {"valid": 1}

        with self.assertRaises(ValueError):
            Experiment(name="foo", run="f1", config=InvalidClass())

        Experiment(name="foo", run="f1", config=InvalidClass().to_dict())


class ValidateUtilTest(unittest.TestCase):
    def testDiagnoseSerialization(self):
        # this is not serializable
        e = threading.Event()

        def test(config):
            print(e)

        assert diagnose_serialization(test) is not True

        # should help identify that 'e' should be moved into
        # the `test` scope.

        # correct implementation
        def test(config):
            e = threading.Event()
            print(e)

        assert diagnose_serialization(test) is True


if __name__ == "__main__":
    import sys

    import pytest

    sys.exit(pytest.main(["-v", __file__]))