import json
from pathlib import Path

import numpy.testing as npt
import pytest

from akkudoktoreos.core.coreabc import get_ems
from akkudoktoreos.prediction.weatherimport import WeatherImport
from akkudoktoreos.utils.datetimeutil import compare_datetimes, to_datetime, to_duration

DIR_TESTDATA = Path(__file__).absolute().parent.joinpath("testdata")

FILE_TESTDATA_WEATHERIMPORT_1_JSON = DIR_TESTDATA.joinpath("import_input_1.json")


@pytest.fixture
def provider(sample_import_1_json, config_eos):
    """Fixture to create a WeatherProvider instance."""
    settings = {
        "weather": {
            "provider": "WeatherImport",
            "weatherimport": {
                "import_file_path": str(FILE_TESTDATA_WEATHERIMPORT_1_JSON),
                "import_json": json.dumps(sample_import_1_json),
            },
        }
    }
    config_eos.merge_settings_from_dict(settings)
    provider = WeatherImport()
    provider._db_reset_state()
    assert provider.enabled() == True
    return provider


@pytest.fixture
def sample_import_1_json():
    """Fixture that returns sample forecast data report."""
    with FILE_TESTDATA_WEATHERIMPORT_1_JSON.open("r", encoding="utf-8", newline=None) as f_res:
        input_data = json.load(f_res)
    return input_data


# ------------------------------------------------
# General forecast
# ------------------------------------------------


def test_singleton_instance(provider):
    """Test that WeatherForecast behaves as a singleton."""
    another_instance = WeatherImport()
    assert provider is another_instance


def test_invalid_provider(provider, config_eos, monkeypatch):
    """Test requesting an unsupported provider."""
    settings = {
        "weather": {
            "provider": "<invalid>",
            "weatherimport": {
                "import_file_path": str(FILE_TESTDATA_WEATHERIMPORT_1_JSON),
            },
        }
    }
    with pytest.raises(ValueError, match="not a valid weather provider"):
        config_eos.merge_settings_from_dict(settings)


# ------------------------------------------------
# Import
# ------------------------------------------------


@pytest.mark.asyncio
@pytest.mark.parametrize(
    "start_datetime, from_file",
    [
        ("2024-11-10 00:00:00", True),  # No DST in Germany
        ("2024-08-10 00:00:00", True),  # DST in Germany
        ("2024-03-31 00:00:00", True),  # DST change in Germany (23 hours/ day)
        ("2024-10-27 00:00:00", True),  # DST change in Germany (25 hours/ day)
        ("2024-11-10 00:00:00", False),  # No DST in Germany
        ("2024-08-10 00:00:00", False),  # DST in Germany
        ("2024-03-31 00:00:00", False),  # DST change in Germany (23 hours/ day)
        ("2024-10-27 00:00:00", False),  # DST change in Germany (25 hours/ day)
    ],
)
async def test_import(provider, sample_import_1_json, start_datetime, from_file, config_eos):
    """Test fetching forecast from Import."""
    key = "weather_temp_air"
    ems_eos = get_ems()
    ems_eos.set_start_datetime(to_datetime(start_datetime, in_timezone="Europe/Berlin"))
    if from_file:
        config_eos.weather.weatherimport.import_json = None
        assert config_eos.weather.weatherimport.import_json is None
    else:
        config_eos.weather.weatherimport.import_file_path = None
        assert config_eos.weather.weatherimport.import_file_path is None
    await provider.delete_by_datetime(start_datetime=None, end_datetime=None)

    # Call the method
    await provider.update_data()

    # Assert: Verify the result is as expected
    assert provider.ems_start_datetime is not None
    assert provider.total_hours is not None
    assert compare_datetimes(provider.ems_start_datetime, ems_eos.start_datetime).equal

    expected_values = sample_import_1_json[key]
    result_values = await provider.key_to_array(
        key=key,
        start_datetime=provider.ems_start_datetime,
        end_datetime=provider.ems_start_datetime + to_duration(f"{len(expected_values)} hours"),
        interval=to_duration("1 hour"),
    )
    # Allow for some difference due to value calculation on DST change
    npt.assert_allclose(result_values, expected_values, rtol=0.001)
