44 lines
1.6 KiB
Python
44 lines
1.6 KiB
Python
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from bls.recipe_parser import parse_fddb_lists_csv, parse_fddb_produkte
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from data_layer.food_mapping import normalize_food_name
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PORRIDGE = (
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"160 g Apfel, Braeburn, 5 ml Omega-3 Vegan Algenöl, 100 g Wildheidelbeeren, "
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"30 g Haferflocken, 100% Hafer-Vollkorn, 40 g Hafer Flocken, Großblatt, 11 g Flohsamenschalen"
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)
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def test_parse_fddb_produkte_splits_on_next_quantity_not_commas():
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ings = parse_fddb_produkte(PORRIDGE)
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names = [i["source_name_raw"] for i in ings]
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assert names == [
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"Apfel, Braeburn",
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"Omega-3 Vegan Algenöl",
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"Wildheidelbeeren",
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"Haferflocken, 100% Hafer-Vollkorn",
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"Hafer Flocken, Großblatt",
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"Flohsamenschalen",
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]
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assert ings[0]["quantity_g"] == 160.0
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assert ings[1]["quantity_g"] == 5.0
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assert ings[1]["quantity_raw"] == "5 ml"
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def test_parse_fddb_lists_csv_porridge_and_portions():
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text = (
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"name;beschreibung;anzahl_portionen;zeit_vorbereitung;zeit_kochen;produkte;\n"
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'"!PorridgeBreakfast ";"";"1";"0";"0";"' + PORRIDGE + '";\n'
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'"Aloo gobi";"";"4";"0";"0";"32 ml Rapso Rapsöl, 83 g Zwiebel, frisch";\n'
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)
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recipes = parse_fddb_lists_csv(text)
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assert len(recipes) == 2
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assert recipes[0]["name_raw"] == "!PorridgeBreakfast"
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assert recipes[0]["name_normalized"] == normalize_food_name("PorridgeBreakfast")
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assert len(recipes[0]["ingredients"]) == 6
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assert recipes[1]["portions"] == 4.0
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assert recipes[1]["ingredients"][0]["source_name_raw"] == "Rapso Rapsöl"
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def test_normalize_strips_list_bang_prefix():
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assert normalize_food_name("!PorridgeBreakfast") == normalize_food_name("PorridgeBreakfast")
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