from csv_parser.executor import guess_nutrition_item_fields
from data_layer.food_mapping import merge_unmapped_rows, normalize_food_name, parse_quantity, parse_quantity_g
from data_layer.nutrition_items import macros_differ


def test_normalize_strips_leading_quantity():
    assert normalize_food_name("50 g Hähnchen") == "hähnchen"
    assert normalize_food_name("  Vollmilch  3,5% ") == "vollmilch 3.5%"
    assert normalize_food_name("1 ml Olivenöl") == normalize_food_name("2 ml Olivenöl") == "olivenöl"


def test_merge_unmapped_collapses_quantity_variants():
    rows = merge_unmapped_rows([
        {"source_name_raw": "1 ml Olivenöl", "source_name_normalized": "1 ml olivenöl", "count": 3, "kind": "diary"},
        {"source_name_raw": "2 ml Olivenöl", "source_name_normalized": "2 ml olivenöl", "count": 1, "kind": "diary"},
    ])
    assert len(rows) == 1
    assert rows[0]["source_name_normalized"] == "olivenöl"
    assert rows[0]["count"] == 4
    assert rows[0]["source_name_raw"].lower() == "olivenöl"


def test_parse_quantity_g():
    assert parse_quantity_g("150 g") == 150.0
    assert parse_quantity_g("150") == 150.0
    assert parse_quantity_g("1 kg") == 1000.0
    assert parse_quantity_g("5 ml") == 5.0
    assert parse_quantity_g("1 Stück") is None
    assert parse_quantity_g("1 Stück", 60) == 60.0
    assert parse_quantity_g("2 EL") == 30.0
    assert parse_quantity("1 Scheibe")["needs_unit_map"] is True
    assert parse_quantity("2 EL")["unit"] == "el"


def test_guess_fddb_bezeichnung_without_template_mapping():
    name, qty = guess_nutrition_item_fields({
        "bezeichnung": "50 g Hähnchen",
        "menge": "50 g",
        "kj": "800",
    })
    assert name == "50 g Hähnchen"
    assert qty == "50 g"


def test_macros_differ_rounds():
    assert not macros_differ({"kcal": 1.04, "protein_g": 0, "fat_g": 0, "carbs_g": 0}, {"kcal": 1.0, "protein_g": 0, "fat_g": 0, "carbs_g": 0})
    assert macros_differ({"kcal": 10, "protein_g": 0, "fat_g": 0, "carbs_g": 0}, {"kcal": 11, "protein_g": 0, "fat_g": 0, "carbs_g": 0})