60 lines
1.9 KiB
Python
60 lines
1.9 KiB
Python
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from product import Product
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from recipe.db import Recipe, Ingredient
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from recipe.scraping import scrape_recipe
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from ingredient_parser import parse_multiple_ingredients
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from typing import List
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from product import find_product_by_tag
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import json
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async def find_existing_product(conn, ingredient: str) -> Product:
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async for item in find_product_by_tag(conn, ingredient):
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return item
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return None
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def parse_ingredient_from_nlp(ingredients: List[str]) -> Ingredient:
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results = []
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for ingredient in parse_multiple_ingredients(ingredients):
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name = ingredient.name.text if ingredient.name else ''
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quantity, unit = None, None
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if ingredient.amount:
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amount = ingredient.amount[0]
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quantity, unit = amount.quantity, amount.unit
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results.append(Ingredient(id=0,
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line=ingredient.sentence,
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name=name,
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quantity=quantity,
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unit=unit,
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preparation=ingredient.preparation.text if ingredient.preparation else '',
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product_id=0
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))
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return results
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async def match_existing_products(conn, ingredients: List[Ingredient]) -> List[Ingredient]:
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for ingredient in ingredients:
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if not ingredient.product:
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existing = await find_existing_product(conn, ingredient.name)
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if existing:
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ingredient.product = existing
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return ingredients
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async def _get_recipe_from_ldata(conn, url: str, ldata: dict) -> dict:
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ingredients = parse_ingredient_from_nlp(ldata['recipeIngredient'])
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ingredients = await match_existing_products(conn, ingredients)
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return Recipe(
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id=0,
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name=ldata['name'],
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link=url,
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raw_data=json.dumps(ldata),
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ingredients=ingredients
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)
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async def parse_recipe(conn, url: str) -> dict:
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ldata = await scrape_recipe(conn, url)
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if ldata:
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return await _get_recipe_from_ldata(conn, url, ldata)
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return None
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