# Food Product Data Scraper: Barcode & Name Lookup (`scrapemint/food-product-data-scraper`) Actor Look up food products in bulk by barcode (EAN/UPC) or by name. For each product: name, brand, quantity, ingredients, allergens, Nutri-Score, NOVA group, nutrition per 100g and a photo URL. For grocery apps, e-commerce listings and nutrition tools. No API key needed. - **URL**: https://apify.com/scrapemint/food-product-data-scraper.md - **Developed by:** [Ken M](https://apify.com/scrapemint) (community) - **Categories:** E-commerce, Business - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Food Product Data Scraper: Barcode & Name Lookup Look up food products in bulk. Paste a list of **barcodes** (EAN-13, EAN-8 or UPC-A, straight from a scanner or an inventory export) or **product name searches**, and get one clean row per product: name, brand, quantity, ingredients, allergens, Nutri-Score, NOVA group, nutrition per 100g and a photo URL. Built for **grocery e-commerce, meal planning and nutrition apps, food bloggers and inventory teams**. Scanned a shelf of products? Turn the barcode list into ready-to-use catalogue data in one run, with no signup and no API key. ### What you get for each product - **name**, **brands**, **quantity** and **servingSize** - **ingredients** as written on the label, plus **allergens** and **additives** - **nutriScore** (A to E), **novaGroup** (1 to 4, how processed it is) and **ecoScore** - **nutritionPer100g**: calories, fat, saturated fat, carbohydrates, sugars, fiber, proteins, salt - **categories**, **labels** (organic, vegan, fair trade...), **countries** where it is sold - **imageUrl**: a product photo, ready for your listing or app - **productUrl**: the product's public page for reference ### Example output ```json { "input": "3017624010701", "mode": "barcode", "found": true, "barcode": "3017624010701", "name": "Nutella", "brands": "Ferrero", "quantity": "400 g", "categories": ["breakfasts", "spreads", "hazelnut spreads"], "allergens": ["milk", "nuts", "soybeans"], "nutriScore": "E", "novaGroup": 4, "nutritionPer100g": { "energyKcal": 539, "fat": 30.9, "sugars": 56.3, "proteins": 6.3, "salt": 0.107 }, "imageUrl": "https://images.openfoodfacts.org/images/products/301/762/401/0701/front_en.jpg", "productUrl": "https://world.openfoodfacts.org/product/3017624010701" } ```` ### Barcodes or searches? - **Barcodes**: exact, one row per number. EAN-13, EAN-8 and UPC-A all work, dashes and spaces are fine. Mistyped numbers are caught by the check digit before they waste a lookup. - **Searches**: free text like "oat milk" or "lindt dark chocolate". Set how many best matches you want per search (default 3). ### Pricing **$0.002 per product found.** Barcodes and searches that match nothing are **free**, and the first 2 rows of every run are free. Enriching a 1,000 product inventory costs about $2, versus the monthly minimums of commercial food data APIs. ### How to run it via API ```bash curl -X POST "https://api.apify.com/v2/acts/scrapemint~food-product-data-scraper/run-sync-get-dataset-items?token=YOUR_TOKEN" \ -H "Content-Type: application/json" \ -d '{"barcodes": ["3017624010701", "5449000000996"], "searches": ["oat milk"]}' ``` ### Frequently asked questions **Where does the data come from?** [Open Food Facts](https://world.openfoodfacts.org), the open database of more than 3 million food products, maintained by volunteers worldwide and used by hundreds of nutrition apps. Data is available under the [Open Database License (ODbL)](https://opendatacommons.org/licenses/odbl/1-0/); database © Open Food Facts contributors. **A barcode I scanned was not found.** Very new, very local or store-brand products are sometimes missing from the database. Those rows are free and marked `found: false` so you can handle them separately. **Some fields are null.** Coverage varies by product and country: popular European products tend to be complete, niche items may lack a Nutri-Score or a photo. You are only charged when a product is found at all. **Does it include prices?** No. Prices are store-specific and live behind retailer sites; this tool covers the label data (ingredients, nutrition, brand) that catalogues and apps need. ### More tools from Scrapemint - [Book Data Scraper](https://apify.com/scrapemint/book-data-scraper): bulk ISBN and title lookups for books. - [Product Recall Finder](https://apify.com/scrapemint/product-recall-finder): US food, drug and product recalls by keyword. - [Shopify Store Products Scraper](https://apify.com/scrapemint/shopify-store-products-scraper): product data from any Shopify store. # Actor input Schema ## `barcodes` (type: `array`): Product barcodes, one per line: EAN-13, EAN-8 or UPC-A. Dashes and spaces are fine. Each barcode returns exactly the matching product. ## `searches` (type: `array`): Free text searches like a product name or a brand ("oat milk", "lindt dark chocolate"). Each search returns the best matches. ## `maxResultsPerQuery` (type: `integer`): How many best matches to return for each name search. Barcodes always return one. ## `maxRows` (type: `integer`): Stop after this many rows in total. ## Actor input object example ```json { "barcodes": [ "3017624010701", "5449000000996", "8076800195057" ], "searches": [ "oat milk", "peanut butter" ], "maxResultsPerQuery": 3, "maxRows": 1000 } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "barcodes": [ "3017624010701", "5449000000996", "8076800195057" ], "searches": [ "oat milk", "peanut butter" ] }; // Run the Actor and wait for it to finish const run = await client.actor("scrapemint/food-product-data-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "barcodes": [ "3017624010701", "5449000000996", "8076800195057", ], "searches": [ "oat milk", "peanut butter", ], } # Run the Actor and wait for it to finish run = client.actor("scrapemint/food-product-data-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "barcodes": [ "3017624010701", "5449000000996", "8076800195057" ], "searches": [ "oat milk", "peanut butter" ] }' | apify call scrapemint/food-product-data-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scrapemint/food-product-data-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Food Product Data Scraper: Barcode & Name Lookup", "description": "Look up food products in bulk by barcode (EAN/UPC) or by name. For each product: name, brand, quantity, ingredients, allergens, Nutri-Score, NOVA group, nutrition per 100g and a photo URL. For grocery apps, e-commerce listings and nutrition tools. No API key needed.", "version": "0.1", "x-build-id": "dcYeAHShCSOFqThUF" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scrapemint~food-product-data-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scrapemint-food-product-data-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/scrapemint~food-product-data-scraper/runs": { "post": { "operationId": "runs-sync-scrapemint-food-product-data-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/scrapemint~food-product-data-scraper/run-sync": { "post": { "operationId": "run-sync-scrapemint-food-product-data-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "barcodes": { "title": "Barcodes (EAN / UPC)", "type": "array", "description": "Product barcodes, one per line: EAN-13, EAN-8 or UPC-A. Dashes and spaces are fine. Each barcode returns exactly the matching product.", "items": { "type": "string" } }, "searches": { "title": "Product name searches", "type": "array", "description": "Free text searches like a product name or a brand (\"oat milk\", \"lindt dark chocolate\"). Each search returns the best matches.", "items": { "type": "string" } }, "maxResultsPerQuery": { "title": "Matches per search", "minimum": 1, "maximum": 50, "type": "integer", "description": "How many best matches to return for each name search. Barcodes always return one.", "default": 3 }, "maxRows": { "title": "Max rows", "minimum": 1, "maximum": 50000, "type": "integer", "description": "Stop after this many rows in total.", "default": 1000 } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```