from tempfile import NamedTemporaryFile
import pytest
from typing import Any, Dict
from io import BytesIO
from openpyxl import Workbook
from datetime import datetime

from backend.condition.lookups.uprn_lookup_csv import UprnLookupLocal
from backend.condition.parsing.peabody_parser import PeabodyParser
from backend.condition.parsing.records.peabody.peabody_asset_condition import (
    PeabodyAssetCondition,
)
from backend.condition.parsing.records.peabody.peabody_property import PeabodyProperty


@pytest.fixture
def peabody_assets_xlsx_bytes() -> BytesIO:
    wb = Workbook()
    survey_records_d_and_lower = wb.active
    survey_records_d_and_lower.title = "Survey Records - D & Lower"
    survey_records_d_and_lower.append(
        [
            "Lo_Reference",
            "full_address",
            "location_type_code",
            "Parent_Lo_Reference",
            "Element_Code",
            "Element",
            "Sub_Element_Code",
            "Sub_Element",
            "Material_Code",
            "material_or_answer",
            "Renewal_Quantity",
            "Renewal_Year",
            "Renewal_Cost",
            "cloned",
            "lo_type_code",
            "condition_survey_date",
        ]
    )
    survey_records_d_and_lower.append(
        [
            "B000RAND",
            "1 RANDOM HOUSE LONDON",
            3,
            "RAND2EST",
            110,
            "ROOFS",
            1,
            "Primary Roof",
            9,
            "Other",
            3,
            2054,
            330,
            "N",
            3,
            datetime(2025, 12, 4, 9, 17, 0),
        ]
    )
    survey_records_d_and_lower.append(
        [
            "B000BLOCK",
            "1100 BLOCK",
            3,
            "RAND2EST",
            110,
            "ROOFS",
            1,
            "Primary Roof",
            9,
            "Other",
            3,
            2054,
            330,
            "N",
            3,
            datetime(2025, 12, 4, 9, 17, 0),
        ]
    )
    survey_records_d_and_lower.append(
        [
            "B000FAKE",
            "3 FAKE CLOSE LONDON",
            3,
            "FAKEEST",
            100,
            "GENERAL",
            15,
            "External Decoration",
            2,
            "Normal",
            1,
            2035,
            1500.7,
            "N",
            3,
            datetime(2025, 7, 5, 0, 0, 0),
        ]
    )
    survey_records_d_and_lower.append(
        [
            "B000MIS",
            "99 MISC ROAD LONDON",
            3,
            "300828",
            54,
            "HHSRS",
            29,
            "HHSRS Structural Collapse & Falling Elements",
            4,
            "HHSRS Moderate",
            2,
            2027,
            None,
            "N",
            3,
            None,
        ]
    )
    survey_records_d_and_lower.append(
        [
            "B000MIS",
            "99 MISC ROAD LONDON",
            3,
            "300828",
            53,
            "External",
            2,
            "Chimney",
            2,
            "Present",
            33,
            2053,
            3531,
            "N",
            3,
            None,
        ]
    )

    stream = BytesIO()
    wb.save(stream)
    stream.seek(0)

    return stream


@pytest.fixture
def prop_ref_uprn_csv_file() -> str:
    csv_content = """reference,out_uprn
    B000RAND,1
    B000BLOCK,2
    B000FAKE,3
    B000MIS,4
    """
    with NamedTemporaryFile(mode="w+", delete=False, suffix=".csv") as tmp:
        tmp.write(csv_content)
        tmp.flush()
        return tmp.name


def test_peabody_parser_parses_conditions(
    peabody_assets_xlsx_bytes, prop_ref_uprn_csv_file
):
    # arrange
    uprn_lookup = UprnLookupLocal(csv_path=prop_ref_uprn_csv_file)
    parser = PeabodyParser(uprn_lookup=uprn_lookup)

    # act
    result: Any = parser.parse(peabody_assets_xlsx_bytes)

    # assert
    assert len(result) == 3

    assert all(isinstance(item, PeabodyProperty) for item in result)


@pytest.fixture
def asset_condition_factory():
    def _factory(full_address: str) -> PeabodyAssetCondition:
        return PeabodyAssetCondition(
            lo_reference="",
            full_address=full_address,
            location_type_code=0,
            parent_lo_reference="",
            element_code=0,
            element="",
            sub_element_code=0,
            sub_element="",
            material_code=0,
            material_or_answer="",
            renewal_quantity=0,
            renewal_year=2026,
            cloned="",
            lo_type_code=0,
            renewal_cost=None,
            condition_survey_date=None,
        )

    return _factory


@pytest.mark.parametrize(
    "full_address, expected_block_level",
    [
        ("1-80  PRINCESS ALICE HOUSE  LONDON", True),
        ("FLATS A-D  7  ST CHARLES SQUARE  LONDON", True),
        ("9A-9H  HEDGEGATE COURT  LONDON", True),
        ("BLOCK  MILNE HOUSE  LONDON", True),
        ("81A-B  GORE ROAD    LONDON", True),
        ("73 & 74 HARVEST COURT  ST. ALBANS", True),
        ("25  HAVERSHAM COURT  GREENFORD", False),
        ("FLAT 10  SPARROW COURT  SOUTHMERE DRIVE  LONDON  SE2 9ES", False),
    ],
)
def test_peabody_asset_is_block_level(
    asset_condition_factory,
    full_address,
    expected_block_level,
):
    # arrange
    asset_condition = asset_condition_factory(full_address)

    # act + assert
    assert asset_condition.is_block_level == expected_block_level