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This a collaborative database of food products from around the world, containing information on ingredients, nutritional values, labels and food additives.
Open Food Facts provides a complete database dump as CSV (downloadable from the website) and a REST API. Engineers load the CSV with `pandas.read_csv()` and handle the 180+ column schema with column selection. The `openfoodfacts` Python library provides API access for individual product lookups.
Open Food Facts data trains AI nutrition analysis models that scan product barcodes and explain ingredient risks. RAG systems built on this dataset answer 'Does this product contain palm oil or high-fructose corn syrup?' A fine-tuned model on Nutri-Score ratings classifies food healthiness.
# pip install openfoodfacts pandas
import openfoodfacts, pandas as pd
# Search products by category
results = openfoodfacts.products.get_by_category("cereals")
products = results["products"]
df = pd.DataFrame(products)[["product_name", "nutriscore_grade", "energy_100g"]]
print(df.dropna(subset=["nutriscore_grade"]).head(10))Official dataset source
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