# Fotocasa Property \[$0.99] Scraper · Spain Real Estate Listings (`memo23/fotocasa-scraper`) Actor \[Only $0.99 per 1000 results] Scrape Fotocasa.es property listings — any buy/rent search URL with filters. Returns price, €/m², type, rooms, bathrooms, m², full address, coordinates, photos, agency, energy certificate (optional) and more as clean JSON/CSV. One row per property. No browser - **URL**: https://apify.com/memo23/fotocasa-scraper.md - **Developed by:** [Muhamed Didovic](https://apify.com/memo23) (community) - **Categories:** Real estate, AI, Agents - **Stats:** 18 total users, 16 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.99 / 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.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 ## Fotocasa Property Scraper Scrape property listings from **Fotocasa.es** — Spain's major real-estate portal. Paste any buy or rent search URL and get clean, structured rows: price, property type, rooms, bathrooms, surface (m²), full address, GPS coordinates, photos, agency, features and listing date. One row per property. Pure HTTP, no browser. ![How it works](https://raw.githubusercontent.com/muhamed-didovic/muhamed-didovic.github.io/main/assets/how-it-works-fotocasa.png) ### Why use this scraper - **Everything on the listing page** — price, m², rooms, coordinates, photos and agency all come from one fetch; no slow per-property crawling. - **Buy *and* rent** — works on any `comprar` or `alquiler` search, with all your on-site filters honoured and paginated automatically. - **Clean, flat output** — one row per property; nested address/features flattened for CSV by default. - **Pure HTTP, no browser** — fast and cheap; no Playwright, no headless Chrome. - **Optional agency email enrichment** — discover the listing agency's website and harvest a contact email (opt-in, billed only on a hit). ### What it does Give it one or more Fotocasa **search/listing** URLs. For each, it reads the live results and emits one dataset row per property with all the fields below. Searches paginate automatically until you hit `Maximum items`. ### Supported inputs | Input | Example | |---|---| | Buy search | `fotocasa.es/es/comprar/viviendas/madrid-capital/todas-las-zonas/l` | | Rent search | `fotocasa.es/es/alquiler/viviendas/barcelona-capital/todas-las-zonas/l` | | Filtered search | run any search on fotocasa.es, copy the URL from the address bar | ### Use cases - **Real-estate market & price research** across Spanish cities and zones. - **Lead generation** — agency names, listing URLs (optional contact emails). - **Investment analysis** — €/m², price distribution, new-build vs resale. - **Aggregation & portals** — pull fresh listings into your own product. ### How it works 1. You paste Fotocasa search URLs. 2. The actor reads each listing page's embedded property data and paginates through results. 3. Each property is normalised into one flat row and pushed to the dataset. ### Input configuration | Field | Type | Description | |---|---|---| | `startUrls` | array | Fotocasa **search** URLs (auto-paginated). | | `maxItems` | integer | Hard cap on properties collected. Default 10000. | | `fetchDetails` | boolean | Opt-in: open each property's detail page for **energy certificate** (A–G), **exact street**, **construction type**, **ground surface**, **quality rating**, **rent price index** and a **decoded feature list**. +1 request/property, billed per `additional-data` event. Default off. | | `flatten` | boolean | Flatten nested objects/arrays into CSV columns (default on). | | `enrichEmails` | boolean | Opt-in agency contact-email enrichment (billed per email found). | | `maxConcurrency` | integer | Parallel row processing (mainly for enrichment). Default 8. | | `proxy` | object | Proxy config. Defaults to Apify Residential. | ### Output sample ```json { "portal": "fotocasa", "id": "189623514", "url": "https://www.fotocasa.es/es/comprar/vivienda/madrid-capital/.../189623514/d", "transactionType": "buy", "propertyType": "Flat", "price": "410.000 €", "rawPrice": 410000, "rooms": 3, "bathrooms": 2, "surface": 90, "address": { "neighborhood": "Moratalaz", "city": "Madrid", "province": "Madrid", "zipCode": "28030" }, "latitude": 40.4091, "longitude": -3.6432, "photoCount": 19, "agency": "VOhome Moratalaz", "isNewConstruction": false, "listedDate": "2026-05-08T12:36:07.170Z" } ```` ### Key output fields | Field | Description | |---|---| | `id` / `url` | Fotocasa property id + listing URL | | `transactionType` | buy / rent | | `propertyType` / `propertySubtype` | e.g. Flat / Penthouse | | `price` / `rawPrice` | display text + numeric value | | `rooms` / `bathrooms` / `surface` | counts + m² | | `address.*` | street, neighborhood, district, city, municipality, province, zipCode | | `latitude` / `longitude` | GPS coordinates | | `photos` / `photoCount` | image URLs + count | | `agency` / `agencyUrl` | listing agency + profile URL | | `features` | parsed feature map (heating, elevator, antiquity…) | | `listedDate` | when the listing was posted | | `contactEmail` / `contactWebsite` | agency contact (only when `enrichEmails` is on) | | `energyRating` / `environmentImpactRating` / `street` / `constructionType` / `qualityRate` / `rentPriceIndex` / `detailFeatures` | property detail (only when `fetchDetails` is on) | ### FAQ **Buy and rent both?** Yes — pass a `comprar` (buy) or `alquiler` (rent) search URL; `transactionType` is set accordingly. **Do filters work?** Yes — any filter you set on fotocasa.es is encoded in the URL and honoured. **Full description?** The listing description shown on the search results is included; everything else (price, rooms, m², coordinates, photos) comes straight from the page data. **Do I need a proxy?** Apify Residential (the default) is recommended for larger runs. ### Support Found an issue or want a field added? Open an issue on the actor's Issues tab and we'll take a look. ### Additional services Need agency contact emails? Turn on `enrichEmails` to append a best-effort contact email + website per agency (billed only when an email is found). ### Explore more scrapers Check the publisher's profile for more real-estate and directory scrapers (Idealista, Redfin, Zillow, Realtor, Immobilienscout24 and more). ### ⚠️ Disclaimer This actor collects only publicly available property-listing data for legitimate research, lead-generation and aggregation use. Respect Fotocasa's terms of service and applicable laws (including data-protection rules) in your jurisdiction. You are responsible for how you use the scraped data. ### SEO Keywords fotocasa scraper, fotocasa api, fotocasa.es scraper, spain real estate scraper, spanish property data, idealista alternative, comprar vivienda scraper, alquiler scraper, property listings spain, real estate data madrid, real estate data barcelona, m2 price data, property coordinates scraper, real estate lead generation # Actor input Schema ## `startUrls` (type: `array`): Full Fotocasa.es search URLs. Each is paginated automatically until `Maximum items` is reached. ## `flatten` (type: `boolean`): When enabled (default), nested objects/arrays (e.g. `address`, `features`, `photos`) are flattened into CSV-friendly columns. Disable to keep the full nested JSON. ## `fetchDetails` (type: `boolean`): If enabled, opens each property's detail page to add the **energy certificate** rating (A–G + value + environmental impact), **exact street + number**, **construction type**, **ground surface**, **quality rating**, the **rent price index**, and a fully **decoded feature list** (ELEVATOR=NO, FURNISHED=YES…). Adds one extra request per property and charges an `additional-data` event each time. Leave off for the fast/cheap search-only output. ## `enrichEmails` (type: `boolean`): If enabled, tries to find a contact email for each listing agency by discovering the agency's website (Clearbit) and reading its contact/about pages. Adds contactEmail + contactWebsite columns. Best-effort, billed per email found; never charged for misses. ## `maxItems` (type: `integer`): Hard cap on the number of properties collected. Each search page returns ~30 listings and paginates automatically; use this cap to control billing. ## `maxConcurrency` (type: `integer`): Maximum number of rows processed in parallel (mainly relevant when agency-email enrichment is on). 6-12 is the sweet spot. ## `maxRequestRetries` (type: `integer`): Number of retries before a failed request is given up. ## `proxy` (type: `object`): Defaults to Apify Residential. Fotocasa serves data cleanly to good fingerprints; residential IPs are recommended for large runs. ## Actor input object example ```json { "startUrls": [ "https://www.fotocasa.es/es/comprar/viviendas/madrid-capital/todas-las-zonas/l", "https://www.fotocasa.es/es/alquiler/viviendas/barcelona-capital/todas-las-zonas/l" ], "flatten": true, "fetchDetails": false, "enrichEmails": false, "maxItems": 10000, "maxConcurrency": 8, "maxRequestRetries": 5, "proxy": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } ``` # 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 = { "startUrls": [ "https://www.fotocasa.es/es/comprar/viviendas/madrid-capital/todas-las-zonas/l", "https://www.fotocasa.es/es/alquiler/viviendas/barcelona-capital/todas-las-zonas/l" ], "proxy": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }; // Run the Actor and wait for it to finish const run = await client.actor("memo23/fotocasa-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 = { "startUrls": [ "https://www.fotocasa.es/es/comprar/viviendas/madrid-capital/todas-las-zonas/l", "https://www.fotocasa.es/es/alquiler/viviendas/barcelona-capital/todas-las-zonas/l", ], "proxy": { "useApifyProxy": True, "apifyProxyGroups": ["RESIDENTIAL"], }, } # Run the Actor and wait for it to finish run = client.actor("memo23/fotocasa-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 '{ "startUrls": [ "https://www.fotocasa.es/es/comprar/viviendas/madrid-capital/todas-las-zonas/l", "https://www.fotocasa.es/es/alquiler/viviendas/barcelona-capital/todas-las-zonas/l" ], "proxy": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }' | apify call memo23/fotocasa-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=memo23/fotocasa-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Fotocasa Property [$0.99] Scraper · Spain Real Estate Listings", "description": "[Only $0.99 per 1000 results] Scrape Fotocasa.es property listings — any buy/rent search URL with filters. Returns price, €/m², type, rooms, bathrooms, m², full address, coordinates, photos, agency, energy certificate (optional) and more as clean JSON/CSV. One row per property. No browser", "version": "0.0", "x-build-id": "VXtNE2hWy1tnrDdVp" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/memo23~fotocasa-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-memo23-fotocasa-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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/memo23~fotocasa-scraper/runs": { "post": { "operationId": "runs-sync-memo23-fotocasa-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/memo23~fotocasa-scraper/run-sync": { "post": { "operationId": "run-sync-memo23-fotocasa-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": { "startUrls": { "title": "Fotocasa search URLs", "type": "array", "description": "Full Fotocasa.es search URLs. Each is paginated automatically until `Maximum items` is reached.", "items": { "type": "string" } }, "flatten": { "title": "Flatten nested fields for CSV-friendly output", "type": "boolean", "description": "When enabled (default), nested objects/arrays (e.g. `address`, `features`, `photos`) are flattened into CSV-friendly columns. Disable to keep the full nested JSON.", "default": true }, "fetchDetails": { "title": "Fetch full property details (energy certificate, exact address, decoded features)", "type": "boolean", "description": "If enabled, opens each property's detail page to add the **energy certificate** rating (A–G + value + environmental impact), **exact street + number**, **construction type**, **ground surface**, **quality rating**, the **rent price index**, and a fully **decoded feature list** (ELEVATOR=NO, FURNISHED=YES…). Adds one extra request per property and charges an `additional-data` event each time. Leave off for the fast/cheap search-only output.", "default": false }, "enrichEmails": { "title": "Enrich with agency contact emails (experimental, billed per email)", "type": "boolean", "description": "If enabled, tries to find a contact email for each listing agency by discovering the agency's website (Clearbit) and reading its contact/about pages. Adds contactEmail + contactWebsite columns. Best-effort, billed per email found; never charged for misses.", "default": false }, "maxItems": { "title": "Maximum items to scrape", "minimum": 1, "type": "integer", "description": "Hard cap on the number of properties collected. Each search page returns ~30 listings and paginates automatically; use this cap to control billing.", "default": 10000 }, "maxConcurrency": { "title": "Max concurrency", "minimum": 1, "type": "integer", "description": "Maximum number of rows processed in parallel (mainly relevant when agency-email enrichment is on). 6-12 is the sweet spot.", "default": 8 }, "maxRequestRetries": { "title": "Max request retries", "minimum": 0, "type": "integer", "description": "Number of retries before a failed request is given up.", "default": 5 }, "proxy": { "title": "Proxy configuration", "type": "object", "description": "Defaults to Apify Residential. Fotocasa serves data cleanly to good fingerprints; residential IPs are recommended for large runs." } } }, "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 } } } } } } } } } } ```