import sys
from dataclasses import dataclass
from datetime import datetime
from typing import Dict, List
from unittest.mock import Mock, patch

import pytest

from promptflow._core.connection_manager import ConnectionManager
from promptflow._utils.dataclass_serializer import assertEqual, deserialize_dataclass, deserialize_value, get_type
from promptflow.contracts.run_info import RunInfo, Status
from promptflow.storage.run_records import NodeRunRecord
from promptflow.tracing._utils import serialize
from promptflow.tracing.contracts.iterator_proxy import IteratorProxy


def get_connection_dict():
    return {
        "azure_open_ai_connection": {
            "type": "AzureOpenAIConnection",
            "value": {
                "api_key": "<azure-openai-key>",
                "api_base": "<aoai-api-endpoint>",
                "api_type": "azure",
                "api_version": "2023-07-01-preview",
            },
        },
        "custom_connection": {
            "type": "CustomConnection",
            "value": {
                "api_key": "<your-key>",
                "url": "<connection-endpoint>",
            },
            "module": "promptflow.connections",
            "secret_keys": ["api_key"],
        },
    }


@pytest.mark.unittest
@pytest.mark.parametrize(
    "type_input, expected",
    [
        (NodeRunRecord, NodeRunRecord),
        ([NodeRunRecord], List[NodeRunRecord]),
        (dict(a=NodeRunRecord), Dict[str, NodeRunRecord]),
        (int, int),
        (str, str),
    ],
)
def test_get_type(type_input, expected):
    assert get_type(type_input) == expected


@pytest.mark.unittest
def test_serialize_dataclass():
    start_time = datetime(2023, 9, 4)
    end_time = datetime(2023, 9, 4)
    node_run_info = RunInfo(
        node=None,
        run_id=None,
        flow_run_id=None,
        status=Status.Completed,
        inputs=None,
        output=None,
        metrics=None,
        error=None,
        parent_run_id=None,
        start_time=start_time,
        end_time=end_time,
        index=0,
    )
    node_record = NodeRunRecord.from_run_info(node_run_info)
    serialized_info = serialize(node_run_info)
    serialized_record = serialize(node_record)
    # test dataclass without serialize attribute
    assert serialized_info["status"] == "Completed"
    assert serialized_info["start_time"] == "2023-09-04T00:00:00Z"
    assert deserialize_value(serialized_info, RunInfo) == node_run_info
    # test dataclass with serialize attribute
    assert serialized_record == node_record.serialize()


@pytest.mark.unittest
@pytest.mark.parametrize(
    "value, value_type, expected",
    [
        (datetime(2023, 9, 4), datetime, "2023-09-04T00:00:00Z"),
        (Status.Completed, Status, "Completed"),
        ([1, 2, 3], List[int], [1, 2, 3]),
        ({"a": 1, "b": 2}, Dict[str, int], {"a": 1, "b": 2}),
        (1, int, 1),
        ("a", str, "a"),
    ],
)
def test_serialize_value(value, value_type, expected):
    assert serialize(value) == expected
    assert deserialize_value(serialize(value), value_type) == value


@pytest.mark.unittest
def test_serialize_remove_null():
    value = {"a": 1, "b": None}
    value_type = Dict[str, int]
    assert deserialize_value(serialize(value, remove_null=True), value_type) == {"a": 1, "b": None}

    @dataclass
    class DummyDataClass:
        name: str
        age: int

    assert serialize(DummyDataClass("Dummy", None), remove_null=True) == {"name": "Dummy"}


@pytest.mark.unittest
def test_serialize_connection():
    new_connection = get_connection_dict()
    connection_manager = ConnectionManager(new_connection)
    assert serialize(connection_manager.get("azure_open_ai_connection")) == "azure_open_ai_connection"


@pytest.mark.unittest
def test_serialize_generator():
    def generator():
        for i in range(3):
            yield i

    g = IteratorProxy(generator())
    next(g)
    assert serialize(g) == [0]


@pytest.mark.unittest
@patch.dict("sys.modules", {"pydantic": None})
def test_import_pydantic_error():
    # mock pydantic is not installed
    class DummyClass:
        def __init__(self, name, age):
            self.name = name
            self.age = age

    dummy = DummyClass("Test", 20)
    assert serialize(dummy) == dummy


@pytest.mark.unittest
@patch.dict("sys.modules", {"pydantic": Mock()})
def test_import_pydantic():
    # mock pydantic is installed
    class MockBaseModel:
        def dict(self):
            return {"key": "value"}

    mock_value = MockBaseModel()
    sys.modules["pydantic"].BaseModel = MockBaseModel
    assert serialize(mock_value) == mock_value.dict()
    assert serialize(123) == 123


@pytest.mark.unittest
def test_deserialize_dataclass():
    # test when cls is not dataclass
    with pytest.raises(ValueError):
        deserialize_dataclass(int, 1)
    # test when data is not a dict
    with pytest.raises(ValueError):
        deserialize_dataclass(NodeRunRecord, "NodeRunRecord")

    @dataclass
    class DummyDataClassWithDefault:
        name: str = "Default Name"
        age: int = 0

    # test deserialize dataclass with default value
    data = {"age": 25}
    obj = deserialize_dataclass(DummyDataClassWithDefault, data)
    assert obj.name == "Default Name"
    assert obj.age == 25


@pytest.mark.unittest
@pytest.mark.parametrize(
    "a, b, expected",
    [
        (1, 2, 1),
        (Status.Completed, Status, Status.Completed),
        (None, datetime, None),
        ("2022-01-01T00:00:00", datetime, datetime.fromisoformat("2022-01-01T00:00:00")),
    ],
)
def test_deserialize_value(a, b, expected):
    assert deserialize_value(a, b) == expected


@pytest.mark.unittest
@pytest.mark.parametrize(
    "a, b, path, are_equal",
    [
        # Test with identical dicts
        (
            {"key1": "value1", "key2": "value2"},
            {"key1": "value1", "key2": "value2"},
            "unittests/_utils/test_dataclass_serializer",
            True,
        ),
        # Test with non-identical dicts
        (
            {"key1": "value1", "key2": "value2"},
            {"key1": "value1", "key3": "value3"},
            "unittests/_utils/test_dataclass_serializer",
            False,
        ),
        # Test with identical lists
        (["item1", "item2"], ["item1", "item2"], "", True),
        # Test with non-identical lists
        (["item1", "item2"], ["item1", "item3"], "", False),
        # Test with other types
        (1, 1, "", True),
        (1, 2, "", False),
        ("string", "string", "", True),
        ("string1", "string2", "", False),
    ],
)
def test_assertEqual(a, b, path, are_equal):
    if are_equal:
        assertEqual(a, b, path)
    else:
        with pytest.raises(AssertionError):
            assertEqual(a, b, path)
