# Netto Scraper - Danish Grocery Products & Prices (`blackfalcondata/netto-scraper`) Actor Scrape Netto (Salling Group), Denmark's largest discount-grocery chain. Get the full product catalog with current shelf prices, Netto+ member offers, and per-unit comparison pricing — ready for price monitoring and grocery analytics. - **URL**: https://apify.com/blackfalcondata/netto-scraper.md - **Developed by:** [Black Falcon Data](https://apify.com/blackfalcondata) (community) - **Categories:** E-commerce, Automation, Lead generation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $2.00 / 1,000 results This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. 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 ### What does Netto Scraper do? Netto Scraper extracts structured product data from [netto.dk](https://netto.dk) — including current shelf price and campaign flags, per-unit comparison pricing, product labels (organic, store-brand, …), and multi-resolution product images. It supports keyword search and controllable result limits, so you can run the same query consistently over time. **New to Apify?** [Sign up free](https://console.apify.com/sign-up?fpr=1h3gvi) and use the included $5 monthly platform credit to test this actor. ### Key features - **🔍 Keyword search or full catalog** — search with `query` ("mælk", "økologisk", "kaffe", brand names …) across product names, descriptions and category terms. Leave `query` empty to dump the entire Netto catalog (~4,300 products) in a single run. - **💰 Current price + Netto+ member offers** — every product carries the active shelf `price` (DKK), an `inStock` flag, and an `isInCurrentLeaflet` flag for this week's avis. When a Netto+ membership offer is active you also get `memberPrice`, `memberOriginalPrice`, `memberSavings`, `memberDiscountPercent`, the offer title, and the offer window (`memberOfferFrom` / `memberOfferTo`). `isOnOffer` flags anything currently discounted. - **⚖️ Per-unit comparison pricing** — `comparePrice` + `compareUnit` (kr/kg, kr/ltr, kr/stk) on every product — the same per-unit number consumer law requires on the shelf label — plus `normalComparePrice` so you can read the regular versus current per-unit rate. Compare value across pack sizes without writing your own normalizer. - **🔖 Tilbud-only filters** — flip `campaignsOnly` to emit only products on offer this week (in the avis or a Netto+ member offer), or `memberOffersOnly` for just the Netto+ deals — the SKU set the chain is pushing this week, in a single filter. - **🥗 Ingredients + structured nutrition** — product rows carry the `ingredients` text and a structured `nutrition[]` array (name/value pairs — energy, fat, carbohydrate, protein, salt, …) whenever the source publishes them. No regex over marketing prose. - **🏷️ Structured unit size, brand + labels** — `unitSize`, `unitMeasure` (g, kg, stk, ltr, …) and `brand` as separate fields, plus a `labels[]` array (Økologisk, Svanemærket, Allergi Venlig, …) and `ageLimit` for age-restricted items. Filter and group without parsing the product name. - **♻️ Incremental price tracking** — run on a schedule with `incrementalMode` + a `stateKey` and get back only what changed since last time — NEW products, price/offer `UPDATED`, and `EXPIRED` (delisted) SKUs, each with `firstSeenAt` / `lastSeenAt`. Pair it with a basket and notifications to be alerted the moment your shopping list changes price. - **🛒 Basket monitoring** — track a specific shopping list by EAN via `productIds` (+ optional `quantities`). Each row gets `quantity`, `lineSubtotal`, the Netto+ `lineMemberTotal` and `lineSavings`, and the run writes a `basket-summary` (products, units, subtotal, Netto+ saving) — ideal for watching your weekly Netto shop cost over time. - **🔔 Notifications** — push a digest of each run to Telegram, Discord, Slack, WhatsApp, or a generic webhook (n8n / Make / Zapier). Wire your shopping basket to a channel and get the current prices delivered automatically. - **📦 Compact mode** — drop the heavy fields (ingredients, full nutrition table, image variants, member-offer detail, category arrays) and keep shopping essentials: identity, current price, per-unit price, offer flags, member price, unit size + brand, and image. Smaller rows for AI agents, MCP servers, and LLM context windows. ### What data can you extract from netto.dk? Each result includes Core listing fields (`ean`, `articleId`, `name`, `productType`, `brand`, `subBrand`, `manufacturer`, and `categoryLvl0`, and more) and detail fields when enrichment is enabled (`description` and `offerDescription`). In standard mode, all fields are always present — unavailable data points are returned as `null`, never omitted. In compact mode, only core fields are returned. ### Input The main inputs are a search keyword and a result limit. Additional filters and options are available in the input schema. Key parameters: - **`productIds`** — Track a specific shopping list by EAN/barcode (e.g. ["5701115583819", "5712876736208"]). Returns just those products with per-line basket economics (quantity, line subtotal, Netto+ member total and saving). Pair with 🔢 Quantities to weight each item. (default: `[]`) - **`quantities`** — Optional per-product counts for basket mode. Two accepted forms: • Object map: `{"5701115583819": 2, "5712876736208": 6}` (compact, preferred for the Console editor) • Array of pairs: `[{"ean": "5701115583819", "qty": 2}]` (useful from Make / n8n / Zapier flows) Drives the basket subtotal and Netto+ saving roll-up. Default qty=1 per product when omitted. Ignored outside basket mode. (default: `{}`) - **`query`** — Keyword search across the Netto catalog (e.g. "mælk", "økologisk", "kaffe"). Searches product names, brands and categories. Leave empty to scan the entire catalog. Ignored when 🛒 Basket EANs are supplied. - **`categories`** — Limit to specific top-level categories (e.g. ["Mejeri & køl", "Frugt & grønt"]). Leave empty for all categories. Accepts a comma-separated string or a JSON array. (default: `[]`) - **`maxResults`** — Maximum total products (0 = unlimited; full catalog ≈ 4,300). (default: `200`) - **`campaignsOnly`** — Only emit products currently on offer — in this week's leaflet (avis) or a Netto+ member offer. (default: `false`) - **`memberOffersOnly`** — Only emit products with an active Netto+ membership offer (cpOffer), with member price and discount %. (default: `false`) - **`inStockOnly`** — Drop products flagged as out of stock. (default: `false`) - **`compact`** — Keep only shopping essentials (identity, current price, per-unit price, offer flags, member price, units, image) and drop heavy fields (nutrition, ingredients, image variants, member-offer detail). Smaller rows for AI agents and dashboards. Same row count, same billing. (default: `false`) - **`excludeEmptyFields`** — Drop null, empty-string and empty-array fields from each record before push. (default: `false`) - **`incrementalMode`** — Compare against the previous run's state and emit only NEW / UPDATED / EXPIRED products (price changes, new SKUs, delistings). Requires 🔑 State Key. EXPIRED detection only fires for a basket or a full uncapped catalog scan (a keyword search can't tell delisted from out-of-scope). (default: `false`) - **`stateKey`** — Stable identifier for incremental tracking (e.g. "my-weekly-basket"). Required when Incremental Mode is on so multiple baskets / queries don't share state. - ...and 13 more parameters ### Input examples **Basic search** — Keyword-driven search with a result cap. → Full payload per result — all standard fields populated where the source provides them. ```json { "query": "mælk", "maxResults": 50 } ```` **Incremental tracking** — Only emit products that changed since the previous run with this `stateKey`. → First run builds the baseline state. Subsequent runs emit only records that are new or whose tracked content changed. Set `emitUnchanged: true` to include unchanged records as well. ```json { "query": "mælk", "maxResults": 200, "incrementalMode": true, "stateKey": "mælk-tracker" } ``` **Compact output for AI agents** — Return only core fields for AI-agent and MCP workflows. → Small payload with the most important fields — ideal for piping into LLMs without token overhead. ```json { "query": "mælk", "maxResults": 50, "compact": true } ``` ### Output Each run produces a dataset of structured product records. Results can be downloaded as JSON, CSV, or Excel from the Dataset tab in Apify Console. ### Example product record ```json { "ean": "5740301223825", "articleId": "10400157-EA", "name": "Rejer fra Nordatlanten i lage", "description": "Rejer fra Nordatlanten i lage", "productType": "Rejer i lage. Indeholder sødemiddel", "brand": "Royal Arctic", "subBrand": null, "manufacturer": null, "categoryLvl0": "Mejeri & køl", "categoryLvl1": "Pålæg", "categoryLvl2": "Fiskepålæg", "categoryPath": "Mejeri & køl > Pålæg > Fiskepålæg > Rejer", "labels": [ "Nøglehul" ], "ageLimit": null, "price": 12, "inStock": true, "offerDescription": "Avisvare", "comparePrice": 150, "normalComparePrice": 224.38, "offerComparePrice": 150, "compareUnit": "kg", "multiPromoPrice": 12, "multiPromoQty": null, "isOnOffer": true, "isInCurrentLeaflet": true, "memberOffer": true, "memberPrice": 10, "memberOriginalPrice": 17.95, "memberSavings": 7.95, "memberDiscountPercent": 44, "memberOfferQty": 1, "memberOfferTitle": "Rejer i lage eller røget laks", "memberOfferId": 100823563, "memberOfferFrom": "2026-06-06T02:00:00", "memberOfferTo": "2026-06-13T01:59:59", "unitSize": 80, "unitMeasure": "g", "ingredients": "Rejer (KREBSDYR), vand, salt, surhedsregulerende midler (E330, E262), konserveringsmidler (E211, E202), stabilisatorer (E415, E410), sødemiddel (E954).", "nutrition": [ { "name": "Protein", "value": "15 g" }, { "name": "Kulhydrater", "value": "0 g" }, { "name": "Salt", "value": "2,3 g" }, { "name": "Næringsindhold pr.", "value": "100 g" }, { "name": "- heraf sukkerarter", "value": "0 g" }, { "name": "Energi", "value": "292 kJ" }, { "name": "Fedt", "value": "1,0 g" }, { "name": "Energi", "value": "69 kcal" }, { "name": "- heraf mættede fedtsyrer", "value": "0,2 g" } ], "imageUrl": "https://digitalassets.sallinggroup.com/image/upload/e_trim:2/b_white,c_pad,e_sharpen:80,f_auto,q_auto,w_690,h_690/cbd80fa1ce649ddf27f96dfe2aa87bb0", "images": [ "https://digitalassets.sallinggroup.com/image/upload/e_trim:2/b_white,c_pad,e_sharpen:80,f_auto,q_auto,w_690,h_690/cbd80fa1ce649ddf27f96dfe2aa87bb0" ], "currency": "DKK", "storeId": "7701", "source": "netto.dk", "portalUrl": null, "scrapedAt": "2026-06-08T18:58:17.975Z", "changeType": "NEW", "firstSeenAt": "2026-06-08T18:58:17.978Z", "lastSeenAt": "2026-06-08T18:58:17.978Z", "expiredAt": null, "quantity": null, "lineSubtotal": null, "lineMemberTotal": null, "lineSavings": null, "lineTotal": null } ``` ### Incremental fields When `incremental: true`, each record also carries: - `changeType` — one of `NEW`, `UPDATED`, `UNCHANGED`, `REAPPEARED`, `EXPIRED`. Default output covers `NEW` / `UPDATED` / `REAPPEARED`; set `emitUnchanged: true` or `emitExpired: true` to opt into the others. - `firstSeenAt`, `lastSeenAt` — ISO-8601 timestamps tracking the listing across runs. ### How to scrape netto.dk 1. Go to [Netto Scraper](https://apify.com/blackfalcondata/netto-scraper?fpr=1h3gvi) in Apify Console. 2. Enter a search keyword. 3. Set `maxResults` to control how many results you need. 4. Click **Start** and wait for the run to finish. 5. Export the dataset as JSON, CSV, or Excel. ### Use cases - Extract product data from netto.dk for market research and competitive analysis. - Track pricing trends across regions and categories over time. - Monitor new and changed listings on scheduled runs without processing the full dataset every time. - Feed structured data into AI agents, MCP tools, and automated pipelines using compact mode. - Export clean, structured data to dashboards, spreadsheets, or data warehouses. ### How much does it cost to scrape netto.dk? Netto Scraper uses [pay-per-event](https://docs.apify.com/platform/actors/paid-actors/pay-per-event) pricing. You pay a small fee when the run starts and then for each result that is actually produced. - **Run start:** $0.01 per run - **Per result:** $0.002 per product record Example costs: - 10 results: **$0.03** - 25 results: **$0.06** - 100 results: **$0.21** - 200 results: **$0.41** - 500 results: **$1.01** #### Example: recurring monitoring savings These examples compare full re-scrapes with incremental runs at different churn rates. Churn is the share of listings that are new or whose tracked content changed since the previous run. Actual churn depends on your query breadth, source activity, and polling frequency — the scenarios below are examples, not predictions. Example setup: 250 results per run, daily polling (30 runs/month). Event-pricing examples scale linearly with result count. | Churn rate | Full re-scrape run cost | Incremental run cost | Savings vs full re-scrape | Monthly cost after baseline | |---|---:|---:|---:|---:| | 5% — stable niche query | $0.51 | $0.04 | $0.47 (93%) | $1.05 | | 15% — moderate broad query | $0.51 | $0.08 | $0.43 (83%) | $2.55 | | 30% — high-volume aggregator | $0.51 | $0.16 | $0.35 (69%) | $4.80 | Full re-scrape monthly cost at daily polling: $15.30. First month with incremental costs $1.53 / $2.97 / $5.15 for the 5% / 15% / 30% scenarios because the first run builds baseline state at full cost before incremental savings apply. Platform usage (compute and proxies) is billed separately by Apify based on actual consumption. Incremental runs consume less on result processing, though fixed per-run overhead stays the same. ### FAQ #### How many results can I get from netto.dk? The number of results depends on the search query and available listings on netto.dk. Use the `maxResults` parameter to control how many results are returned per run. #### Does Netto Scraper support recurring monitoring? Yes. Enable incremental mode to only receive new or changed listings on subsequent runs. This is ideal for scheduled monitoring where you want to track changes over time without re-processing the full dataset. #### Can I integrate Netto Scraper with other apps? Yes. Netto Scraper works with Apify's [integrations](https://apify.com/integrations?fpr=1h3gvi) to connect with tools like Zapier, Make, Google Sheets, Slack, and more. You can also use webhooks to trigger actions when a run completes. #### Can I use Netto Scraper with the Apify API? Yes. You can start runs, manage inputs, and retrieve results programmatically through the [Apify API](https://docs.apify.com/api/v2). Client libraries are available for JavaScript, Python, and other languages. #### Can I use Netto Scraper through an MCP Server? Yes. Apify provides an [MCP Server](https://apify.com/apify/actors-mcp-server?fpr=1h3gvi) that lets AI assistants and agents call this actor directly. Use compact mode and `excludeEmptyFields` to keep payloads manageable for LLM context windows. #### Is it legal to scrape netto.dk? This actor extracts publicly available data from netto.dk. Web scraping of public information is generally considered legal, but you should always review the target site's terms of service and ensure your use case complies with applicable laws and regulations, including GDPR where relevant. #### Your feedback If you have questions, need a feature, or found a bug, please [open an issue](https://apify.com/blackfalcondata/netto-scraper/issues?fpr=1h3gvi) on the actor's page in Apify Console. Your feedback helps us improve. ### You might also like - [REMA 1000 Scraper - Danish Grocery Products & Prices](https://apify.com/blackfalcondata/rema1000-scraper?fpr=1h3gvi) — Scrape rema1000.dk — Denmark's largest discount-grocery chain with 3900 SKUs. Search products by. ### Getting started with Apify New to Apify? [Create a free account with $5 credit](https://console.apify.com/sign-up?fpr=1h3gvi) — no credit card required. 1. Sign up — $5 platform credit included 2. Open this actor and configure your input 3. Click **Start** — export results as JSON, CSV, or Excel Need more later? [See Apify pricing](https://apify.com/pricing?fpr=1h3gvi). # Actor input Schema ## `productIds` (type: `array`): Track a specific shopping list by EAN/barcode (e.g. \["5701115583819", "5712876736208"]). Returns just those products with per-line basket economics (quantity, line subtotal, Netto+ member total and saving). Pair with 🔢 Quantities to weight each item. ## `quantities` (type: `object,array,string`): Optional per-product counts for basket mode. Two accepted forms: • Object map: `{"5701115583819": 2, "5712876736208": 6}` (compact, preferred for the Console editor) • Array of pairs: `[{"ean": "5701115583819", "qty": 2}]` (useful from Make / n8n / Zapier flows) Drives the basket subtotal and Netto+ saving roll-up. Default qty=1 per product when omitted. Ignored outside basket mode. ## `query` (type: `string`): Keyword search across the Netto catalog (e.g. "mælk", "økologisk", "kaffe"). Searches product names, brands and categories. Leave empty to scan the entire catalog. Ignored when 🛒 Basket EANs are supplied. ## `categories` (type: `array`): Limit to specific top-level categories (e.g. \["Mejeri & køl", "Frugt & grønt"]). Leave empty for all categories. Accepts a comma-separated string or a JSON array. ## `maxResults` (type: `integer`): Maximum total products (0 = unlimited; full catalog ≈ 4,300). ## `campaignsOnly` (type: `boolean`): Only emit products currently on offer — in this week's leaflet (avis) or a Netto+ member offer. ## `memberOffersOnly` (type: `boolean`): Only emit products with an active Netto+ membership offer (cpOffer), with member price and discount %. ## `inStockOnly` (type: `boolean`): Drop products flagged as out of stock. ## `compact` (type: `boolean`): Keep only shopping essentials (identity, current price, per-unit price, offer flags, member price, units, image) and drop heavy fields (nutrition, ingredients, image variants, member-offer detail). Smaller rows for AI agents and dashboards. Same row count, same billing. ## `excludeEmptyFields` (type: `boolean`): Drop null, empty-string and empty-array fields from each record before push. ## `incrementalMode` (type: `boolean`): Compare against the previous run's state and emit only NEW / UPDATED / EXPIRED products (price changes, new SKUs, delistings). Requires 🔑 State Key. EXPIRED detection only fires for a basket or a full uncapped catalog scan (a keyword search can't tell delisted from out-of-scope). ## `stateKey` (type: `string`): Stable identifier for incremental tracking (e.g. "my-weekly-basket"). Required when Incremental Mode is on so multiple baskets / queries don't share state. ## `emitUnchanged` (type: `boolean`): Include products with no detected change in the output (default: skip — only changes are emitted). ## `emitExpired` (type: `boolean`): Include products that disappeared since the prior run (delisted / out of stock). Only meaningful for basket or full-catalog runs. ## `telegramToken` (type: `string`): Telegram bot token (from @BotFather). Required for Telegram notifications. ## `telegramChatId` (type: `string`): Telegram chat or channel ID (e.g. "-100123456789"). Required when telegramToken is set. ## `discordWebhookUrl` (type: `string`): Discord incoming webhook URL. ## `slackWebhookUrl` (type: `string`): Slack incoming webhook URL. ## `whatsappAccessToken` (type: `string`): WhatsApp Cloud API token. Recipient must have messaged the business number within the last 24h. ## `whatsappPhoneNumberId` (type: `string`): Your WhatsApp Business phone-number ID. ## `whatsappTo` (type: `string`): Recipient phone in E.164 format without + (e.g. "4512345678"). ## `webhookUrl` (type: `string`): Receives a JSON POST with {metadata, items} after each run — for n8n / Make / Zapier / custom backends. ## `webhookHeaders` (type: `object`): Optional JSON object of custom headers (e.g. {"Authorization":"Bearer ..."}). ## `notificationLimit` (type: `integer`): Maximum number of products included in each notification message (1–20). ## `notifyOnlyChanges` (type: `boolean`): When Incremental Mode is on, only send notifications for products with a lifecycle event (NEW / UPDATED). Unchanged products are still pushed to the dataset but don't trigger alerts. ## Actor input object example ```json { "productIds": [], "quantities": {}, "query": "mælk", "categories": [], "maxResults": 50, "campaignsOnly": false, "memberOffersOnly": false, "inStockOnly": false, "compact": false, "excludeEmptyFields": false, "incrementalMode": false, "emitUnchanged": false, "emitExpired": false, "notificationLimit": 5, "notifyOnlyChanges": false } ``` # 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 = { "query": "mælk", "maxResults": 50, "compact": false, "excludeEmptyFields": false }; // Run the Actor and wait for it to finish const run = await client.actor("blackfalcondata/netto-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 = { "query": "mælk", "maxResults": 50, "compact": False, "excludeEmptyFields": False, } # Run the Actor and wait for it to finish run = client.actor("blackfalcondata/netto-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 '{ "query": "mælk", "maxResults": 50, "compact": false, "excludeEmptyFields": false }' | apify call blackfalcondata/netto-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=blackfalcondata/netto-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Netto Scraper - Danish Grocery Products & Prices", "description": "Scrape Netto (Salling Group), Denmark's largest discount-grocery chain. Get the full product catalog with current shelf prices, Netto+ member offers, and per-unit comparison pricing — ready for price monitoring and grocery analytics.", "version": "0.3", "x-build-id": "580g8tIdAr4q7sWjE" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/blackfalcondata~netto-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-blackfalcondata-netto-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/blackfalcondata~netto-scraper/runs": { "post": { "operationId": "runs-sync-blackfalcondata-netto-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/blackfalcondata~netto-scraper/run-sync": { "post": { "operationId": "run-sync-blackfalcondata-netto-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": { "productIds": { "title": "🛒 Basket — product EANs", "type": "array", "description": "Track a specific shopping list by EAN/barcode (e.g. [\"5701115583819\", \"5712876736208\"]). Returns just those products with per-line basket economics (quantity, line subtotal, Netto+ member total and saving). Pair with 🔢 Quantities to weight each item.", "items": { "type": "string" }, "default": [] }, "quantities": { "title": "🔢 Basket — quantities per EAN", "description": "Optional per-product counts for basket mode. Two accepted forms:\n• Object map: `{\"5701115583819\": 2, \"5712876736208\": 6}` (compact, preferred for the Console editor)\n• Array of pairs: `[{\"ean\": \"5701115583819\", \"qty\": 2}]` (useful from Make / n8n / Zapier flows)\nDrives the basket subtotal and Netto+ saving roll-up. Default qty=1 per product when omitted. Ignored outside basket mode.", "default": {} }, "query": { "title": "🔍 Search query", "type": "string", "description": "Keyword search across the Netto catalog (e.g. \"mælk\", \"økologisk\", \"kaffe\"). Searches product names, brands and categories. Leave empty to scan the entire catalog. Ignored when 🛒 Basket EANs are supplied." }, "categories": { "title": "🗂️ Categories", "type": "array", "description": "Limit to specific top-level categories (e.g. [\"Mejeri & køl\", \"Frugt & grønt\"]). Leave empty for all categories. Accepts a comma-separated string or a JSON array.", "items": { "type": "string" }, "default": [] }, "maxResults": { "title": "💯 Max Results", "minimum": 0, "maximum": 10000, "type": "integer", "description": "Maximum total products (0 = unlimited; full catalog ≈ 4,300).", "default": 200 }, "campaignsOnly": { "title": "🏷️ Tilbud only", "type": "boolean", "description": "Only emit products currently on offer — in this week's leaflet (avis) or a Netto+ member offer.", "default": false }, "memberOffersOnly": { "title": "⭐ Netto+ member offers only", "type": "boolean", "description": "Only emit products with an active Netto+ membership offer (cpOffer), with member price and discount %.", "default": false }, "inStockOnly": { "title": "📦 In stock only", "type": "boolean", "description": "Drop products flagged as out of stock.", "default": false }, "compact": { "title": "🧩 Compact Output", "type": "boolean", "description": "Keep only shopping essentials (identity, current price, per-unit price, offer flags, member price, units, image) and drop heavy fields (nutrition, ingredients, image variants, member-offer detail). Smaller rows for AI agents and dashboards. Same row count, same billing.", "default": false }, "excludeEmptyFields": { "title": "🚿 Exclude empty fields", "type": "boolean", "description": "Drop null, empty-string and empty-array fields from each record before push.", "default": false }, "incrementalMode": { "title": "♻️ Incremental Mode", "type": "boolean", "description": "Compare against the previous run's state and emit only NEW / UPDATED / EXPIRED products (price changes, new SKUs, delistings). Requires 🔑 State Key. EXPIRED detection only fires for a basket or a full uncapped catalog scan (a keyword search can't tell delisted from out-of-scope).", "default": false }, "stateKey": { "title": "🔑 State Key", "type": "string", "description": "Stable identifier for incremental tracking (e.g. \"my-weekly-basket\"). Required when Incremental Mode is on so multiple baskets / queries don't share state." }, "emitUnchanged": { "title": "📤 Emit Unchanged", "type": "boolean", "description": "Include products with no detected change in the output (default: skip — only changes are emitted).", "default": false }, "emitExpired": { "title": "🚮 Emit Expired", "type": "boolean", "description": "Include products that disappeared since the prior run (delisted / out of stock). Only meaningful for basket or full-catalog runs.", "default": false }, "telegramToken": { "title": "🔑 Telegram Bot Token", "type": "string", "description": "Telegram bot token (from @BotFather). Required for Telegram notifications." }, "telegramChatId": { "title": "💬 Telegram Chat ID", "type": "string", "description": "Telegram chat or channel ID (e.g. \"-100123456789\"). Required when telegramToken is set." }, "discordWebhookUrl": { "title": "🎮 Discord Webhook URL", "type": "string", "description": "Discord incoming webhook URL." }, "slackWebhookUrl": { "title": "💼 Slack Webhook URL", "type": "string", "description": "Slack incoming webhook URL." }, "whatsappAccessToken": { "title": "📱 WhatsApp Access Token", "type": "string", "description": "WhatsApp Cloud API token. Recipient must have messaged the business number within the last 24h." }, "whatsappPhoneNumberId": { "title": "📞 WhatsApp Phone Number ID", "type": "string", "description": "Your WhatsApp Business phone-number ID." }, "whatsappTo": { "title": "📲 WhatsApp Recipient", "type": "string", "description": "Recipient phone in E.164 format without + (e.g. \"4512345678\")." }, "webhookUrl": { "title": "🪝 Generic Webhook URL", "type": "string", "description": "Receives a JSON POST with {metadata, items} after each run — for n8n / Make / Zapier / custom backends." }, "webhookHeaders": { "title": "📋 Webhook Headers", "type": "object", "description": "Optional JSON object of custom headers (e.g. {\"Authorization\":\"Bearer ...\"})." }, "notificationLimit": { "title": "📊 Max Items Per Notification", "minimum": 1, "maximum": 20, "type": "integer", "description": "Maximum number of products included in each notification message (1–20).", "default": 5 }, "notifyOnlyChanges": { "title": "🔄 Notify Only Changes", "type": "boolean", "description": "When Incremental Mode is on, only send notifications for products with a lifecycle event (NEW / UPDATED). Unchanged products are still pushed to the dataset but don't trigger alerts.", "default": false } } }, "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 } } } } } } } } } } ```