# Food & Nutrition Scraper (Open Food Facts) (`ponderable_hydrometer/openfoodfacts-scraper`) Actor Get food & nutrition data from Open Food Facts — barcode, keyword or category. Brand, Nutri-Score, NOVA, ingredients, per-100g nutrients. Free, keyless, no proxies. - **URL**: https://apify.com/ponderable\_hydrometer/openfoodfacts-scraper.md - **Developed by:** [Ponderable Hydrometer](https://apify.com/ponderable_hydrometer) (community) - **Categories:** E-commerce, Automation, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $3.00 / 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. 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/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 & Nutrition Scraper (Open Food Facts) **Food product and nutrition data from Open Food Facts — 4M+ products — by barcode, keyword or category, with per-100g nutrients and food scores.** Free, keyless, no proxies. The barbell in food data is free-but-incomplete (USDA) vs $1,850/mo (Nutritionix). This actor gives no-code buyers (fitness/diet/CPG apps) a clean, reliable keyless feed with the scores and nutrients they actually log. ### What you get One row per product: - **Identity** — `barcode`, `name`, `brands`, `quantity`, `categories`, `countries` - **Food scores** — `nutriscore` (a–e), `novaGroup` (1–4 processing level), `ecoscore` (a–e) - **Ingredients & labels** — `ingredientsText`, `labels` - **Per-100g nutrients** — `energyKcal100g`, `fat100g`, `saturatedFat100g`, `carbohydrates100g`, `sugars100g`, `fiber100g`, `proteins100g`, `salt100g`, `sodium100g` - **Media & link** — `imageUrl`, canonical Open Food Facts `url` ### Output sample ```json { "barcode": "3017620422003", "name": "Nutella", "brands": "Nutella, Ferrero", "quantity": "400 g", "categories": "Spreads, Sweet spreads", "countries": "France, United States", "nutriscore": "e", "novaGroup": 4, "ecoscore": "d", "ingredientsText": "Sugar, palm oil, hazelnuts…", "labels": "Gluten-free", "energyKcal100g": 539, "fat100g": 30.9, "saturatedFat100g": 10.6, "carbohydrates100g": 57.5, "sugars100g": 56.3, "fiber100g": 0, "proteins100g": 6.3, "salt100g": 0.107, "sodium100g": 0.0428, "imageUrl": "https://images.openfoodfacts.org/…/front.jpg", "url": "https://world.openfoodfacts.org/product/3017620422003" } ```` ### Input | Field | Type | Default | Description | |-------|------|---------|-------------| | `searchTerms` | array | `["nutella"]` | Keywords to search by name/brand, e.g. `oat milk` | | `barcodes` | array | — | Product barcodes (EAN/UPC) to look up directly | | `category` | string | — | Category tag to list, e.g. `breakfast-cereals`, `chocolates` | | `maxResults` | integer | `200` | Cap per search term / category | Provide at least one of `searchTerms`, `barcodes` or `category`. ### Example input ```json { "searchTerms": ["oat milk"], "category": "breakfast-cereals", "maxResults": 200 } ``` Direct barcode lookup: ```json { "barcodes": ["3017620422003", "5449000000996"] } ``` ### Why this actor - **Three lookup modes in one** — barcode, keyword search and category listing. - **The scores buyers log** — Nutri-Score, NOVA and Eco-Score plus full per-100g nutrients. - **Keyless & resilient** — auto-retry on Open Food Facts' occasional 503s so results aren't silently dropped. - **Fair flat pricing** vs metered nutrition APIs. ### Pricing Pay per result — **$3.00 per 1,000 results** (one product = one result). No subscription or platform fees. ### Related actors - **USDA FoodData Scraper** — official USDA nutrient database (bring your own key). - **PubChem Scraper** — chemical compound properties, for ingredient/additive research. - **Package Registry Scraper** — unrelated tooling; see our full catalog for more. ### Notes & limits - Data is Open Food Facts' free public API; the actor retries on 503/429 so results aren't dropped. - Field completeness depends on contributors — popular products are rich; obscure items may miss fields. - Nutrients are per 100g/100ml where provided. - Data is © Open Food Facts contributors (ODbL) — attribute and use accordingly. This actor is an independent tool, not affiliated with Open Food Facts. # Actor input Schema ## `searchTerms` (type: `array`): Keywords to search products by name/brand, e.g. "nutella", "oat milk". ## `barcodes` (type: `array`): Product barcodes (EAN/UPC) to look up directly, e.g. "3017620422003". ## `category` (type: `string`): Open Food Facts category tag to list products from, e.g. "breakfast-cereals", "chocolates". ## `maxResults` (type: `integer`): Cap on products returned per search term or category. ## Actor input object example ```json { "searchTerms": [ "nutella" ], "maxResults": 200 } ``` # 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 = { "searchTerms": [ "nutella" ] }; // Run the Actor and wait for it to finish const run = await client.actor("ponderable_hydrometer/openfoodfacts-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 = { "searchTerms": ["nutella"] } # Run the Actor and wait for it to finish run = client.actor("ponderable_hydrometer/openfoodfacts-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 '{ "searchTerms": [ "nutella" ] }' | apify call ponderable_hydrometer/openfoodfacts-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=ponderable_hydrometer/openfoodfacts-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Food & Nutrition Scraper (Open Food Facts)", "description": "Get food & nutrition data from Open Food Facts — barcode, keyword or category. Brand, Nutri-Score, NOVA, ingredients, per-100g nutrients. Free, keyless, no proxies.", "version": "0.1", "x-build-id": "oLoRhviDk00MvBmuA" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/ponderable_hydrometer~openfoodfacts-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-ponderable_hydrometer-openfoodfacts-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/ponderable_hydrometer~openfoodfacts-scraper/runs": { "post": { "operationId": "runs-sync-ponderable_hydrometer-openfoodfacts-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/ponderable_hydrometer~openfoodfacts-scraper/run-sync": { "post": { "operationId": "run-sync-ponderable_hydrometer-openfoodfacts-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "searchTerms": { "title": "Search terms", "type": "array", "description": "Keywords to search products by name/brand, e.g. \"nutella\", \"oat milk\".", "items": { "type": "string" } }, "barcodes": { "title": "Barcodes", "type": "array", "description": "Product barcodes (EAN/UPC) to look up directly, e.g. \"3017620422003\".", "items": { "type": "string" } }, "category": { "title": "Category tag", "type": "string", "description": "Open Food Facts category tag to list products from, e.g. \"breakfast-cereals\", \"chocolates\"." }, "maxResults": { "title": "Max results per search/category", "minimum": 1, "type": "integer", "description": "Cap on products returned per search term or category.", "default": 200 } } }, "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 } } } } } } } } } } ```