47 lines
1.2 KiB
Python
47 lines
1.2 KiB
Python
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import re
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import json
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from os import walk
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import spacy
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from tqdm import tqdm
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import csv
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path_to_file_input = "./recipe"
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recipe_files = []
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for (dirpath, dirnames, filenames) in walk(path_to_file_input):
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recipe_files.extend(filenames)
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break
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recipes_names=[]
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recipes_ingredients=dict()
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for recipe in recipe_files:
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with open(path_to_file_input+"/"+recipe) as f:
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data=json.load(f)
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recipe_ingredients=[]
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for row in data["content"]:
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if row['type']=='ingredient':
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recipe_ingredients.append(" ".join(re.findall("[a-zA-z]+",row['text'])))
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recipes_ingredients[int(recipe[:3])]=[re.sub('json|(I+)',' ', ' '.join(re.findall("[a-zA-Z]+",recipe)))]+recipe_ingredients
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text_list = []
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for k,v in recipes_ingredients.items():
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text_list.append(str(k)+' '+' '.join(v))
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tok_text=[]
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nlp=spacy.load("en_core_web_sm")
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stopwords=['can','cans','inch','cup','cups','and','or','what','teaspoon','teaspoons','chopped','cut']
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for doc in tqdm(nlp.pipe(text_list, disable=['tagger', 'parser', 'ner'])):
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tok=[t.text for t in doc if not t.text in stopwords]
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tok_text.append(tok)
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print(tok_text)
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with open('ingredients_recipes_merged.csv', 'w') as f:
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wr=csv.writer(f)
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wr.writerows(tok_text)
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