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86f15e6957
Tagebuchzeilen eigener Rezepte werden über den Listen-Import in Zutaten zerlegt. Zuordnen erfolgt im Namens-Popup statt per BLS-Code. Co-authored-by: Cursor <cursoragent@cursor.com>
80 lines
2.6 KiB
Python
80 lines
2.6 KiB
Python
"""Parse FDDB lists_*.csv (name;…;produkte) into recipe + ingredients."""
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from __future__ import annotations
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import csv
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import io
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import re
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from typing import Any
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from data_layer.food_mapping import normalize_food_name, parse_quantity_g
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ING_RE = re.compile(
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r"(?P<qty>\d+(?:[.,]\d+)?)\s*(?P<unit>g|kg|ml|l)\b\s*(?P<name>.+?)"
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r"(?=,\s*\d+(?:[.,]\d+)?\s*(?:g|kg|ml|l)\b|$)",
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re.IGNORECASE | re.DOTALL,
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)
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def parse_fddb_produkte(text: str) -> list[dict[str, Any]]:
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raw = (text or "").strip().strip('"')
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if not raw:
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return []
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out: list[dict[str, Any]] = []
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for i, m in enumerate(ING_RE.finditer(raw)):
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qty = float(m.group("qty").replace(",", "."))
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unit = m.group("unit").lower()
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name = re.sub(r"\s+", " ", m.group("name")).strip(" ,;")
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if not name:
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continue
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grams = qty
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if unit == "kg":
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grams = qty * 1000.0
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elif unit == "l":
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grams = qty * 1000.0
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elif unit == "ml":
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grams = qty
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out.append({
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"source_name_raw": name,
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"source_name_normalized": normalize_food_name(name),
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"quantity_raw": f"{m.group('qty').replace(',', '.')} {unit}",
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"quantity_g": round(grams, 3),
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"sort_order": i,
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})
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return out
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def parse_fddb_lists_csv(text: str) -> list[dict[str, Any]]:
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if text.startswith("\ufeff"):
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text = text[1:]
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reader = csv.DictReader(io.StringIO(text), delimiter=";")
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recipes = []
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for row in reader:
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name = (row.get("name") or "").strip().strip('"')
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if not name:
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continue
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try:
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portions = float(str(row.get("anzahl_portionen") or "1").replace(",", "."))
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except ValueError:
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portions = 1.0
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if portions <= 0:
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portions = 1.0
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ingredients = parse_fddb_produkte(row.get("produkte") or "")
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if not ingredients:
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leftover = (row.get("produkte") or "").strip().strip('"')
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if leftover:
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ingredients = [{
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"source_name_raw": leftover,
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"source_name_normalized": normalize_food_name(leftover),
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"quantity_raw": None,
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"quantity_g": parse_quantity_g(leftover),
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"sort_order": 0,
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}]
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recipes.append({
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"name_raw": name,
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"name_normalized": normalize_food_name(name),
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"portions": portions,
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"description": (row.get("beschreibung") or "").strip() or None,
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"ingredients": ingredients,
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})
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return recipes
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