1. PyCuisine:
python
from pycuisine import Recipe, Ingredient
tomato = Ingredient('Tomato', '2', 'pcs')
chop_tomatoes = Step('Chop the tomatoes', 'Chop the tomatoes into small pieces')
recipe = Recipe('Tomato Salad')
recipe.add_ingredient(tomato)
recipe.add_step(chop_tomatoes)
print(recipe.get_recipe())
2. Recipe-Scrapers:
python
from recipe_scrapers import scrape_me
scraper = scrape_me('https://www.allrecipes.com/recipe/278773/simple-salisbury-steak/')
recipe_title = scraper.title()
ingredients = scraper.ingredients()
instructions = scraper.instructions()
print('Recipe Title:', recipe_title)
print('Ingredients:', ingredients)
print('Instructions:', instructions)
3. Recommender Systems:
python
from surprise import SVD
from surprise import Dataset
from surprise.model_selection import train_test_split
data = Dataset.load_builtin('ml-100k')
trainset, testset = train_test_split(data, test_size=0.2)
algo = SVD()
algo.fit(trainset)
predictions = algo.test(testset)
for pred in predictions:
print(pred)
