I published a free sample of 5,000 food records for anyone working on nutrition search, calorie tracking, barcode matching, data cleaning, or food-related ML experiments.

Dataset:

https://www.kaggle.com/datasets/dietly/dietly-food-sample-5000-foods-calories-and-macros

Each row can include:

• – food name and brand
• – barcode
• – category
• – serving size
• – calories
• – protein, fat and carbohydrates
• – fiber and sugar
• – sodium, saturated fat and cholesterol
• – potassium
• – source and confidence metadata

The data is primarily derived from Open Food Facts and is provided with its ODbL provenance and attribution requirements.

Important limitations:

• – nutrition fields can be missing
• – community-contributed labels can be incorrect or outdated
• – coverage varies by product and country
• – this is a 5,000-row sample, not the complete catalog
• – it should not be treated as medical or laboratory-verified data

Disclosure: I created this sample while building DietlyAPI, a hosted search and barcode API over a much larger indexed catalog. The downloadable sample itself is available without an API signup.

I’d especially appreciate feedback about the schema: which additional fields or export format would make the dataset more useful?