# Open Food Facts Product & Nutrition Data (`jungle_synthesizer/openfoodfacts-product-nutrition-scraper`) Actor Scrape food product data from Open Food Facts — the world's largest open food database. Search by category, tag, or country; look up products by barcode; or run full-catalog sweeps. Returns Nutri-Score, NOVA group, Eco-Score, nutriments per 100g, allergens, ingredients, and more for 3.5M+ products. - **URL**: https://apify.com/jungle\_synthesizer/openfoodfacts-product-nutrition-scraper.md - **Developed by:** [BowTiedRaccoon](https://apify.com/jungle_synthesizer) (community) - **Categories:** AI, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing Pay per event This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. 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 ## Open Food Facts Product & Nutrition Data Scrape food product data from [Open Food Facts](https://world.openfoodfacts.org) — the world's largest open food database with 3.5M+ products. The actor supports two modes: - **search** — faceted search by category tag, country, or both; returns paginated results - **barcode** — bulk product lookup by EAN/UPC barcode list Every record includes Nutri-Score grade, NOVA food-processing group, Eco-Score, a full nutriments panel (energy, fat, carbohydrates, sugar, fiber, protein, salt per 100g), allergens, ingredients text, and category/label/packaging tags. --- ### Use cases - **Grocery & CPG apps** — enrich product catalogues with nutrition data, allergen flags, and sustainability scores - **Diet & allergen apps** — filter products by allergen tags, Nutri-Score, or NOVA group - **Sustainability analytics** — benchmark Eco-Score distributions across categories or brands - **LLM grounding & RAG** — build a structured food-product knowledge base from open data - **Retail product enrichment** — add standardised nutriments and classification tags to SKU databases --- ### Input | Field | Type | Default | Description | |---|---|---|---| | `mode` | string | `search` | `"search"` for category/tag browse; `"barcode"` for individual product lookup | | `categoriesTags` | string[] | `["en:breakfast-cereals"]` | Category tags to filter (search mode only) | | `countriesTag` | string | — | Country filter, e.g. `"en:france"` (search mode only) | | `barcodes` | string[] | — | EAN/UPC barcode list (barcode mode only) | | `maxItems` | integer | 10 | Maximum number of products to return | #### Search mode example ```json { "mode": "search", "categoriesTags": ["en:breakfast-cereals", "en:mueslis"], "countriesTag": "en:united-kingdom", "maxItems": 500 } ```` #### Barcode lookup example ```json { "mode": "barcode", "barcodes": ["3017620422003", "0737628064502", "4056489641926"], "maxItems": 3 } ``` *** ### Output Each record is a flat object with the following fields: | Field | Type | Description | |---|---|---| | `code` | string | EAN/UPC barcode (primary key) | | `product_name` | string | Product name | | `brands` | string | Brand name(s), comma-separated | | `quantity` | string | Net quantity / weight as displayed on packaging | | `serving_size` | string | Serving size as stated on the package | | `nutriscore_grade` | string | Nutri-Score grade: `a` (best) to `e` (worst) | | `nova_group` | integer | NOVA food-processing group: `1` (unprocessed) to `4` (ultra-processed) | | `ecoscore_grade` | string | Eco-Score environmental grade: `a` to `e` | | `categories_tags` | string | Category taxonomy tags, comma-separated | | `countries_tags` | string | Country availability tags, comma-separated | | `ingredients_text` | string | Full ingredients list | | `allergens_tags` | string | Allergen tags, comma-separated (e.g. `en:milk,en:nuts`) | | `traces_tags` | string | May-contain allergen traces, comma-separated | | `additives_tags` | string | Food additive tags (E-numbers), comma-separated | | `labels_tags` | string | Certification tags (e.g. `en:organic,en:vegan`), comma-separated | | `packaging_tags` | string | Packaging material tags, comma-separated | | `energy_kcal_100g` | number | Energy per 100g in kcal | | `fat_100g` | number | Total fat per 100g in grams | | `saturated_fat_100g` | number | Saturated fat per 100g in grams | | `carbohydrates_100g` | number | Carbohydrates per 100g in grams | | `sugars_100g` | number | Sugars per 100g in grams | | `fiber_100g` | number | Dietary fiber per 100g in grams | | `proteins_100g` | number | Protein per 100g in grams | | `salt_100g` | number | Salt per 100g in grams | | `sodium_100g` | number | Sodium per 100g in grams | | `image_url` | string | URL of the product front image | | `last_modified_t` | integer | Unix timestamp of last modification in Open Food Facts | #### Sample output record ```json { "code": "3017620422003", "product_name": "Nutella", "brands": "Nutella", "quantity": null, "serving_size": null, "nutriscore_grade": "e", "nova_group": 4, "ecoscore_grade": "unknown", "categories_tags": "en:Petit-déjeuners,en:Produits à tartiner,en:Pâtes à tartiner", "countries_tags": "en:france,en:italy,en:united-states", "ingredients_text": "Sucre, huile de palme, NOISETTES 13%, cacao maigre 7,4%...", "allergens_tags": "en:milk,en:nuts,en:soybeans", "traces_tags": "", "additives_tags": "en:e322", "labels_tags": "", "packaging_tags": "", "energy_kcal_100g": 539, "fat_100g": 30.9, "saturated_fat_100g": 10.6, "carbohydrates_100g": 57.5, "sugars_100g": 56.3, "fiber_100g": null, "proteins_100g": 6.3, "salt_100g": 0.107, "sodium_100g": 0.042, "image_url": "https://images.openfoodfacts.org/images/products/.../front_en.jpg", "last_modified_t": 1700000000 } ``` *** ### Category tags Common category tags for the `categoriesTags` input: | Tag | Description | |---|---| | `en:breakfast-cereals` | Breakfast cereals (muesli, granola, cornflakes) | | `en:beverages` | All beverages | | `en:dairy` | Dairy products | | `en:meats` | Meat products | | `en:cheeses` | Cheese products | | `en:chocolates` | Chocolate products | | `en:biscuits-and-cakes` | Biscuits, cookies, cakes | | `en:snacks` | Snack foods | | `en:sauces` | Sauces and condiments | | `en:pastas` | Pasta products | Browse the full taxonomy at [world.openfoodfacts.org/categories](https://world.openfoodfacts.org/categories). *** ### Data licence Open Food Facts data is published under the [Open Database Licence (ODbL)](https://opendatacommons.org/licenses/odbl/1.0/). Individual contents (product photos, text) are under the [Database Contents Licence (DbCL)](https://opendatacommons.org/licenses/dbcl/1.0/). You must credit Open Food Facts and share any derived database under the same ODbL licence. *** ### Rate limits & best practices The actor sends a descriptive User-Agent and respects Open Food Facts project guidelines (≤10 requests/minute for search). For full-database ingestion, Open Food Facts publishes [bulk JSONL/CSV exports](https://world.openfoodfacts.org/data) updated daily — contact us if you need bulk access at scale. # Actor input Schema ## `sp_intended_usage` (type: `string`): Please describe how you plan to use the data extracted by this crawler. ## `sp_improvement_suggestions` (type: `string`): Provide any feedback or suggestions for improvements. ## `sp_contact` (type: `string`): Provide your email address so we can get in touch with you. ## `maxItems` (type: `integer`): Maximum number of records to return. Leave blank for unlimited. ## `mode` (type: `string`): "search" fetches products matching your category/country filter via the Open Food Facts search API. "barcode" looks up specific products by EAN/UPC barcode. ## `categoriesTags` (type: `array`): Filter search results by category tag (e.g. "en:breakfast-cereals", "en:beverages"). Only used in search mode. Leave empty to search across all categories. ## `countriesTag` (type: `string`): Filter search results by country availability tag (e.g. "en:france", "en:united-states"). Only used in search mode. Leave empty for all countries. ## `barcodes` (type: `array`): List of EAN/UPC barcodes to look up individually. Only used in barcode mode. ## Actor input object example ```json { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "maxItems": 10, "mode": "search", "categoriesTags": [ "en:breakfast-cereals" ], "barcodes": [ "3017620422003", "7613035353626" ] } ``` # Actor output Schema ## `results` (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 = { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "maxItems": 10, "mode": "search", "categoriesTags": [ "en:breakfast-cereals" ], "countriesTag": "", "barcodes": [ "3017620422003", "7613035353626" ] }; // Run the Actor and wait for it to finish const run = await client.actor("jungle_synthesizer/openfoodfacts-product-nutrition-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 = { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "maxItems": 10, "mode": "search", "categoriesTags": ["en:breakfast-cereals"], "countriesTag": "", "barcodes": [ "3017620422003", "7613035353626", ], } # Run the Actor and wait for it to finish run = client.actor("jungle_synthesizer/openfoodfacts-product-nutrition-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 '{ "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "maxItems": 10, "mode": "search", "categoriesTags": [ "en:breakfast-cereals" ], "countriesTag": "", "barcodes": [ "3017620422003", "7613035353626" ] }' | apify call jungle_synthesizer/openfoodfacts-product-nutrition-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=jungle_synthesizer/openfoodfacts-product-nutrition-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Open Food Facts Product & Nutrition Data", "description": "Scrape food product data from Open Food Facts — the world's largest open food database. Search by category, tag, or country; look up products by barcode; or run full-catalog sweeps. Returns Nutri-Score, NOVA group, Eco-Score, nutriments per 100g, allergens, ingredients, and more for 3.5M+ products.", "version": "0.1", "x-build-id": "vb2hDcwFi1csnN6mm" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/jungle_synthesizer~openfoodfacts-product-nutrition-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-jungle_synthesizer-openfoodfacts-product-nutrition-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/jungle_synthesizer~openfoodfacts-product-nutrition-scraper/runs": { "post": { "operationId": "runs-sync-jungle_synthesizer-openfoodfacts-product-nutrition-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/jungle_synthesizer~openfoodfacts-product-nutrition-scraper/run-sync": { "post": { "operationId": "run-sync-jungle_synthesizer-openfoodfacts-product-nutrition-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": { "sp_intended_usage": { "title": "What is the intended usage of this data?", "minLength": 1, "type": "string", "description": "Please describe how you plan to use the data extracted by this crawler." }, "sp_improvement_suggestions": { "title": "How can we improve this crawler for you?", "minLength": 1, "type": "string", "description": "Provide any feedback or suggestions for improvements." }, "sp_contact": { "title": "Contact Email", "minLength": 1, "type": "string", "description": "Provide your email address so we can get in touch with you." }, "maxItems": { "title": "Max Items", "type": "integer", "description": "Maximum number of records to return. Leave blank for unlimited." }, "mode": { "title": "Mode", "enum": [ "search", "barcode" ], "type": "string", "description": "\"search\" fetches products matching your category/country filter via the Open Food Facts search API. \"barcode\" looks up specific products by EAN/UPC barcode.", "default": "search" }, "categoriesTags": { "title": "Category Tags", "type": "array", "description": "Filter search results by category tag (e.g. \"en:breakfast-cereals\", \"en:beverages\"). Only used in search mode. Leave empty to search across all categories.", "items": { "type": "string" } }, "countriesTag": { "title": "Country Tag", "type": "string", "description": "Filter search results by country availability tag (e.g. \"en:france\", \"en:united-states\"). Only used in search mode. Leave empty for all countries." }, "barcodes": { "title": "Barcodes", "type": "array", "description": "List of EAN/UPC barcodes to look up individually. Only used in barcode mode.", "items": { "type": "string" } } } }, "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 } } } } } } } } } } ```