# Open Food Facts Scraper (`parseforge/open-food-facts-scraper`) Actor Scrape food product data from Open Food Facts covering 3M+ products worldwide. Get names, brands, barcodes, Nutri-Score grades, NOVA processing groups, full ingredient lists, nutrition facts per 100g, and allergen warnings. Filter by category, country, and nutrition grade. - **URL**: https://apify.com/parseforge/open-food-facts-scraper.md - **Developed by:** [ParseForge](https://apify.com/parseforge) (community) - **Categories:** E-commerce, Lead generation, Other - **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 1 bookmarks - **User rating**: No ratings yet ## Pricing from $80.00 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## 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.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.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/platform/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 ![ParseForge Banner](https://raw.githubusercontent.com/ParseForge/apify-assets/main/banner.jpg) ## 🥗 Open Food Facts Scraper Whether you're a nutrition researcher analyzing food products, a health app developer building ingredient databases, or a consumer advocate tracking food quality, this tool makes it easy to collect structured food product data from the world's largest open food database. > **The Open Food Facts Scraper collects food products with names, brands, ingredients, nutritional values, Nutri-Score grades, NOVA groups, allergens, labels, and packaging data. Filter by category, country, nutritional grade, and more.** ### ✨ What Does It Do - 🥫 **Product data** - collect product names, brands, quantities, serving sizes, and barcodes - 🏅 **Nutri-Score grades** - get A through E nutritional quality ratings for each product - 🍎 **Full nutrient profiles** - extract calories, fat, saturated fat, carbs, sugars, fiber, protein, and salt per 100g - 🏭 **NOVA groups** - see food processing levels from 1 (unprocessed) to 4 (ultra-processed) - ⚠️ **Allergen data** - get allergen tags, traces, and ingredient lists for each product - 🌍 **Country and label filters** - search products by country of sale and certification labels ### 🔧 Input - **Category** - filter products by food category (e.g., 'chocolate', 'pizza', 'yogurt') - **Max Items** - how many products to collect (free users get 10 items, paid users up to 1,000,000) - **Search Query** - optional text search within the category - **Country** - filter by country: United States, France, United Kingdom, Germany, Spain, or Italy - **Nutri-Score** - filter by nutritional grade (A is healthiest, E is least healthy) - **NOVA Group** - filter by processing level (1 is unprocessed, 4 is ultra-processed) - **Sort By** - sort by popularity, product name, or date created ```json { "category": "chocolate", "maxItems": 50, "country": "us", "nutriscore": "a" } ```` ### 📊 Output Each product record includes up to 30+ data fields. Download as JSON, CSV, or Excel. | Field | Description | |-------|-------------| | 🔗 url | Product page on Open Food Facts | | 🖼️ imageUrl | Product photo | | 📋 productName | Product name | | 🏷️ brands | Brand name | | 🗂️ categories | Product categories | | 📏 quantity | Package quantity/size | | 🏅 nutriscore | Nutri-Score grade (A-E) | | 🏭 novaGroup | NOVA processing group (1-4) | | 🌿 ecoscore | Eco-Score environmental grade | | 📝 ingredients | Full ingredient list | | 🔢 nutriments | Nutritional values per 100g | | ⚠️ allergens | Allergen information | | 🏷️ labels | Certification labels (organic, etc.) | | 🌍 countries | Countries where sold | ```json { "id": "7622210449283", "productName": "Milka Alpine Milk", "brands": "Milka", "categories": "Snacks, Sweet snacks, Chocolates", "quantity": "100 g", "nutriscore": "e", "nutriscoreScore": 26, "novaGroup": 4, "ecoscore": "d", "ingredients": "Sugar, cocoa butter, skimmed milk powder...", "nutriments": { "energy_kcal": 530, "fat": 29.5, "saturatedFat": 18, "carbohydrates": 59, "sugars": 58, "fiber": 1.9, "proteins": 6.3, "salt": 0.3 }, "allergens": "en:milk, en:soybeans", "labels": "Green Dot", "countries": "France, Germany, Belgium", "imageUrl": "https://images.openfoodfacts.org/images/products/...", "url": "https://world.openfoodfacts.net/product/7622210449283", "scrapedAt": "2026-04-09T12:00:00.000Z" } ``` ### 💎 Why Choose the Open Food Facts Scraper? | Feature | Our Tool | Manual Browsing | |---------|----------|----------------| | Batch collection | ✅ Up to 1M products | ❌ Browse one at a time | | Nutritional data | ✅ Full nutrient profiles | ⚠️ Click each product | | Multiple filters | ✅ Category, country, Nutri-Score, NOVA | ⚠️ Limited search | | Structured output | ✅ JSON, CSV, Excel | ❌ Web pages only | | Automated scheduling | ✅ Daily/weekly monitoring | ❌ Manual visits | | Allergen data | ✅ Included automatically | ⚠️ Buried in details | ### 📋 How to Use 1. **Sign Up** - [Create a free account w/ $5 credit](https://console.apify.com/sign-up?fpr=vmoqkp) 2. **Configure** - set your food category, country, nutritional filters, and how many products you want 3. **Run It** - click "Start" and get structured food data in seconds No coding, no setup, no manual browsing required. ### 🎯 Business Use Cases - 🔬 **Nutrition researchers** - analyze nutritional profiles across food categories and brands at scale - 📱 **Health app developers** - build food databases with Nutri-Score, NOVA groups, and allergen data - 🏪 **Retailers** - compare product nutritional quality and sourcing across brands and countries - 🏥 **Dietitians** - create evidence-based food guides with detailed ingredient and nutrient data - 📊 **Market analysts** - track food industry trends in nutrition, labeling, and product formulation - 🌿 **Environmental researchers** - study Eco-Score data and packaging materials across product categories ### ❓ FAQ 🥗 **What is Open Food Facts?** Open Food Facts is a free, open-source database of food products from around the world. It contains over 3 million products with nutritional information, ingredients, labels, and packaging data. 🏅 **What is Nutri-Score?** Nutri-Score is a nutrition label system that grades food from A (best nutritional quality) to E (least favorable). It considers calories, sugar, saturated fat, sodium, fiber, protein, and fruit/vegetable content. 🏭 **What are NOVA groups?** NOVA classifies food by processing level: 1 (unprocessed or minimally processed), 2 (processed culinary ingredients), 3 (processed foods), and 4 (ultra-processed food products). 🌍 **Which countries are covered?** Open Food Facts covers products from over 180 countries. You can filter by United States, France, United Kingdom, Germany, Spain, Italy, or search all countries. ⚠️ **Is allergen data reliable?** Allergen data comes from product labels and community contributions. Always verify critical allergen information against the actual product packaging. ### 🔗 Integrate Open Food Facts Scraper with any app - [Make](https://docs.apify.com/platform/integrations/make) - Automate food data workflows - [Zapier](https://docs.apify.com/platform/integrations/zapier) - Get alerts for new products matching your criteria - [Slack](https://docs.apify.com/platform/integrations/slack) - Get notified in your team channel - [Google Drive](https://docs.apify.com/platform/integrations/drive) - Export food data to spreadsheets - [Webhooks](https://docs.apify.com/platform/integrations/webhooks) - Trigger actions when runs complete ### 💡 Recommended Actors Looking for more data collection tools? Check out these related actors: | Actor | Description | Link | |-------|-------------|------| | Hugging Face Model Scraper | Collect AI model data from Hugging Face | [Link](https://apify.com/parseforge/hugging-face-model-scraper) | | Smart Apify Actor Scraper | Scrape actor data with 70+ fields | [Link](https://apify.com/parseforge/smart-apify-actor-scraper) | | PR Newswire Scraper | Collect press releases and news | [Link](https://apify.com/parseforge/pr-newswire-scraper) | | HTML to JSON Smart Parser | Parse any web page into structured data | [Link](https://apify.com/parseforge/html-to-json-smart-parser) | | Lead Formatter Tool | Format and enrich lead data | [Link](https://apify.com/parseforge/lead-formatter) | **Pro Tip:** Browse our complete collection of [data collection actors](https://apify.com/parseforge) to find the perfect tool for your needs. ### 🆘 Need Help? - Check the FAQ section above for common questions - Visit the [Apify documentation](https://docs.apify.com) for platform guides - Contact us at [Tally contact form](https://tally.so/r/BzdKgA) ### ⚠️ Disclaimer > This Actor is an independent tool and is not affiliated with, endorsed by, or connected to Open Food Facts or its contributors. It accesses only publicly available data. # Actor input Schema ## `maxItems` (type: `integer`): Free users: Limited to 10 items (preview). Paid users: Optional, max 1,000,000 ## `category` (type: `string`): Filter products by category (e.g., chocolate, pizza, yogurt). ## `query` (type: `string`): Optional text search within the category. ## `country` (type: `string`): Filter products by country. ## `nutriscore` (type: `string`): Filter by Nutri-Score grade (A is healthiest, E is least healthy). ## `novaGroup` (type: `string`): Filter by NOVA food processing group (1 is least processed, 4 is most processed). ## `sortBy` (type: `string`): Sort results by this field. ## Actor input object example ```json { "maxItems": 10, "category": "chocolate" } ``` # Actor output Schema ## `overview` (type: `string`): No description # 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 = { "maxItems": 10, "category": "chocolate" }; // Run the Actor and wait for it to finish const run = await client.actor("parseforge/open-food-facts-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 = { "maxItems": 10, "category": "chocolate", } # Run the Actor and wait for it to finish run = client.actor("parseforge/open-food-facts-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 '{ "maxItems": 10, "category": "chocolate" }' | apify call parseforge/open-food-facts-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=parseforge/open-food-facts-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Open Food Facts Scraper", "description": "Scrape food product data from Open Food Facts covering 3M+ products worldwide. Get names, brands, barcodes, Nutri-Score grades, NOVA processing groups, full ingredient lists, nutrition facts per 100g, and allergen warnings. Filter by category, country, and nutrition grade.", "version": "0.0", "x-build-id": "RED2dWOWB55OZNfmj" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/parseforge~open-food-facts-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-parseforge-open-food-facts-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/parseforge~open-food-facts-scraper/runs": { "post": { "operationId": "runs-sync-parseforge-open-food-facts-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/parseforge~open-food-facts-scraper/run-sync": { "post": { "operationId": "run-sync-parseforge-open-food-facts-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "maxItems": { "title": "Max Items", "minimum": 1, "maximum": 1000000, "type": "integer", "description": "Free users: Limited to 10 items (preview). Paid users: Optional, max 1,000,000" }, "category": { "title": "Category", "type": "string", "description": "Filter products by category (e.g., chocolate, pizza, yogurt)." }, "query": { "title": "Search Query", "type": "string", "description": "Optional text search within the category." }, "country": { "title": "Country", "enum": [ "", "world", "us", "fr", "gb", "de", "es", "it" ], "type": "string", "description": "Filter products by country." }, "nutriscore": { "title": "Nutri-Score", "enum": [ "", "a", "b", "c", "d", "e" ], "type": "string", "description": "Filter by Nutri-Score grade (A is healthiest, E is least healthy)." }, "novaGroup": { "title": "NOVA Group", "enum": [ "", "1", "2", "3", "4" ], "type": "string", "description": "Filter by NOVA food processing group (1 is least processed, 4 is most processed)." }, "sortBy": { "title": "Sort By", "enum": [ "", "popularity", "product_name", "created_t" ], "type": "string", "description": "Sort results by this field." } } }, "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 } } } } } } } } } } ```