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4b1be3019d
Bezeichnung/Menge auch ohne Vorlagen-Mapping, Zuordnen-Hinweis, Tagesliste mit Lebensmitteln. Co-authored-by: Cursor <cursoragent@cursor.com>
30 lines
1.1 KiB
Python
30 lines
1.1 KiB
Python
from csv_parser.executor import guess_nutrition_item_fields
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from data_layer.food_mapping import normalize_food_name, parse_quantity_g
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from data_layer.nutrition_items import macros_differ
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def test_normalize_strips_leading_quantity():
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assert normalize_food_name("50 g Hähnchen") == "hähnchen"
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assert normalize_food_name(" Vollmilch 3,5% ") == "vollmilch 3.5%"
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def test_parse_quantity_g():
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assert parse_quantity_g("150 g") == 150.0
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assert parse_quantity_g("150") == 150.0
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assert parse_quantity_g("1 Stück") is None
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def test_guess_fddb_bezeichnung_without_template_mapping():
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name, qty = guess_nutrition_item_fields({
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"bezeichnung": "50 g Hähnchen",
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"menge": "50 g",
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"kj": "800",
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})
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assert name == "50 g Hähnchen"
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assert qty == "50 g"
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def test_macros_differ_rounds():
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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})
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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})
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