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919c77fcf8
Katalog, lernendes Mapping ohne KI, optionale Items und Import-Policy. Playwright-Smoke und Issue-Audit um Ernährung/Zuordnen/API ergänzt. Co-authored-by: Cursor <cursoragent@cursor.com>
40 lines
1.1 KiB
Python
40 lines
1.1 KiB
Python
from io import BytesIO
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from openpyxl import Workbook
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from bls.parser import parse_components_xlsx, parse_foods_xlsx
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def _xlsx(rows):
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wb = Workbook()
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ws = wb.active
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for row in rows:
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ws.append(row)
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buf = BytesIO()
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wb.save(buf)
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return buf.getvalue()
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def test_parse_components_dynamic():
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data = _xlsx([
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["Code", "Name_DE", "Name_EN", "Einheit"],
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["ENERCC", "Energie", "Energy", "kcal/100g"],
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["NA", "Natrium", "Sodium", "mg/100g"],
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])
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attrs = parse_components_xlsx(data)
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keys = {a["attr_key"] for a in attrs}
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assert "ENERCC" in keys
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assert "NA" in keys
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def test_parse_foods_keeps_bls_code():
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data = _xlsx([
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["BLS Code", "Name", "Food name", "ENERCC Energie [kcal/100g]", "ENERCC Herkunft", "ENERCC Referenz"],
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["C131000", "Hafer roh", "Oats raw", 350, "Analyse", "MRI"],
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])
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parsed = parse_foods_xlsx(data)
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assert parsed["foods"][0]["bls_code"] == "C131000"
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assert parsed["foods"][0]["name_de"] == "Hafer roh"
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vals = {v["attr_key"]: v["value_num"] for v in parsed["foods"][0]["values"]}
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assert vals.get("ENERCC") == 350
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