Immobiliare.it Listings Scraper
Pricing
$0.56 / 1,000 results
Immobiliare.it Listings Scraper
Extract sale or rent search listings from Immobiliare.it with price, area, rooms, location, agency, photo, and coordinates when available.
Pricing
$0.56 / 1,000 results
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MLG Data
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7 hours ago
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Immobiliare.it Scraper
Scrape Immobiliare.it property listings and export Immobiliare.it data to CSV, JSON, or Excel for research and reporting. This Immobiliare.it API alternative collects public property listings with clear inputs and structured output.
Collect public Italian property listings from a sale or rent city search. Export asking price, floor area, rooms, address, neighborhood, agency, photos, coordinates, and direct listing links.
What data can you extract from Immobiliare.it?
Each dataset row is one property listing. The field names below are the keys in the JSON export; optional fields remain null when the public source does not supply a value.
| Field | Description | Example |
|---|---|---|
id | Immobiliare.it listing ID | "132449092" |
title | Listing headline | "Quadrilocale via Giovanni Livraghi, Precotto, Milano" |
price | Advertised price in EUR | 630000 |
surfaceM2 | Advertised floor area in square metres | 123 |
rooms | Room count or range as shown on the card | "4" |
bathrooms | Bathroom count when listed | 3 |
floor | Floor label | "1" |
address | Public listing address | "Via Giovanni Livraghi" |
zone | Microzone or macrozone | "Precotto" |
city | City | "Milano" |
agencyName | Advertising agency or builder name | "Gastone Di Paola Immobiliare" |
listingUrl | Direct listing URL | "https://www.immobiliare.it/annunci/132449092/" |
mainPhoto | Main photo URL | "https://pwm.im-cdn.it/image/2005115806/xxl.jpg" |
latitude | Approximate latitude when supplied | 45.5162 |
longitude | Approximate longitude when supplied | 9.224 |
How to scrape Immobiliare.it
- Paste a supported sale or rent city searchUrl, or enter city and choose contract.
- Set maxItems and maxPages for the size of the property dataset you need.
- Run the actor and review the city, price, and listingUrl columns.
- Download CSV, JSON, or Excel; keep listing IDs to compare future snapshots.
A run stores its results in the default dataset. Review a few rows there before exporting, especially if you plan to combine several searches or compare snapshots over time. Keep the record ID or source URL in your export so you can remove duplicates and return to the public page behind a result.
Input
Enter these values in the actor input. A prefilled example is a starting point, while a default is the value used when the field is omitted. Required inputs are identified below.
| Name | Type | Default | Description |
|---|---|---|---|
searchUrl | string | "https://www.immobiliare.it/vendita-case/milano/" | Immobiliare.it sale or rent city search URL. Takes precedence over city and contract. |
city | string | "—" | City slug or name, such as milano. Used when searchUrl is empty. |
contract | string | "sale" | Sale or rent. Used with city when searchUrl is empty. |
maxItems | integer | 100 | Stop after this many matching listings. 0 means no item cap. |
maxPages | integer | 20 | Maximum search result pages to request (25 cards per page). |
proxyConfiguration | object | {"useApifyProxy": true} | Apify Proxy configuration. The actor uses Italy geolocation and escalates from datacenter to residential when blocked. |
A realistic input:
{"searchUrl": "https://www.immobiliare.it/vendita-case/milano/","maxItems": 50,"maxPages": 20}
The example keeps the run small enough to inspect while showing the main search path. Increase the item limit only after the initial results match your intended scope. When multiple filters are available, start with the most important one and then refine the next run based on the public results.
Output example
The following item came from a successful published run. Long review or description text is shortened here for readability; the dataset keeps the full value.
{"id": "132449092","title": "Quadrilocale via Giovanni Livraghi, Precotto, Milano","price": 630000,"surfaceM2": 123,"rooms": "4","bathrooms": 3,"floor": "1","address": "Via Giovanni Livraghi","zone": "Precotto","city": "Milano","agencyName": "Gastone Di Paola Immobiliare","listingUrl": "https://www.immobiliare.it/annunci/132449092/","mainPhoto": "https://pwm.im-cdn.it/image/2005115806/xxl.jpg","latitude": 45.5162,"longitude": 9.224}
The example shows the shape of one record, not a guarantee that every optional value will be present in every result. CSV and Excel exports present the same fields as columns. JSON retains the native number, boolean, array, and null values that make further filtering easier.
Use cases
- Property analysts can compare asking prices and floor area within a city.
- Brokerage teams can monitor visible competing listings and their advertised agencies.
- Investors can build a shortlist by location, room count, and price.
- Researchers can map approximate listing coordinates where the site supplies them.
- Market-report teams can compare active public sale and rental inventory across city runs.
These workflows use public listing or review data as a starting point. Check the linked source page before acting on a single record, because public content, counts, and availability can change after a run. Store the run date alongside each export when comparing data over time.
How much does it cost to scrape Immobiliare.it?
The price is $0.56 per 1,000 results, with platform usage included. Charges scale with the number of results produced: 100 results cost $0.056, 1,000 results cost $0.56, and 5,000 results cost $2.80. The 5,000-result figure is a pricing illustration, not a promise that a single search exposes that many public results. Set the item limit for the amount of data you need and check the actual result count after the run.
Tips for best results
Use a city-specific search URL from the sale or rent pages, or pass city and contract when you do not have a URL. searchUrl wins if both forms are provided. Narrow a site search before passing its URL when you need a particular segment. Each result page carries about 25 cards; maxPages controls how far the actor follows the search and maxItems caps matching rows. Run separate cities to create a multi-city dataset, then use id or listingUrl to remove repeat listings. Check price and surfaceM2 for null before calculating price per square metre. Coordinates may be approximate, so do not use them as an exact property address.
When creating a repeatable workflow, save the input that produced a useful dataset. Compare later exports by stable ID where available, and inspect a few source links whenever a value matters to a decision. A narrow input usually makes the output easier to validate and reduces time spent processing unrelated results.
Limits
The actor accepts city sale or rent paths under vendita-case or affitto-case, not arbitrary listing or category pages. It keeps results whose city matches the requested city and removes duplicate listing IDs. Availability is bounded by maxPages, the search results returned by the site, and maxItems. A card may omit a public asking price, floor area, bathrooms, floor, agency, photo, or coordinates; the matching output fields are null. Price is the advertised value in euros when public, not a transaction price. Search inventory changes frequently, and a saved dataset is a snapshot.
These limits come from the public data exposed to the actor at run time. Source pages can change, so a run can return fewer rows than its requested maximum. A maximum item count is a stop condition, not a minimum or a guarantee of coverage. Use the source URL in each row when you need to verify a particular detail.
Use with AI agents (MCP)
The actor can be called through the Apify MCP connection with the same input fields shown above. Ask for a bounded result set and name the fields that matter to the task. A useful prompt also asks for source links, so each conclusion can be checked against its public record.
- “Collect current Milan sale listings with price, area, rooms, neighborhood, and listing URL.”
- “Export rental listings for a city and identify entries with public prices and floor area.”
For recurring research, keep the search input and the requested output columns consistent. Compare records by their IDs or source URLs when results from different runs are combined. If an optional field is missing, keep it empty in downstream analysis instead of guessing a value.
FAQ
Is it legal to scrape this data? This actor reads public data. Follow the source site’s terms, applicable law, and GDPR requirements. Do not misuse personal data or republish material without the rights to do so.
Do I need to provide proxies? No. The default proxy configuration is already supplied. You can override proxyConfiguration if your workflow requires different settings.
How fast is a run? Time depends on the number of pages or products, the selected limits, and how quickly public pages respond. Start with a small limit to estimate the time for your search; fetching optional detail pages can add time.
Can I schedule and monitor runs? Yes. Use Apify scheduling and run monitoring for repeat collections. Save each run’s dataset so you can compare snapshots and spot missing or changed records.
Can I export to Google Sheets or Excel? Yes. Download CSV, JSON, or Excel from the dataset, or connect the dataset to Google Sheets through an integration. Keep IDs or URLs as columns for deduplication.
What if a field is empty? The public source did not supply that value for the record, or the value was unavailable in the view used. Treat null as missing data, not as zero or a negative answer.
Can I scrape rentals as well as sales? Yes. Use an affitto-case city URL, or set city and contract to rent.
Will a property URL work as searchUrl? No. The input expects a city search URL for sale or rent.
Are coordinates exact? No. They are the approximate coordinates provided with a listing when available.
Integrations
Use the Apify API to start runs and read the default dataset. Webhooks can notify another system when a run finishes; Zapier, Make, and n8n can move results into reporting workflows or Google Sheets. Scheduling supports regular snapshots, and exported CSV or Excel files work for manual analysis. Keep the source record ID and URL in downstream systems so updates can be matched to earlier exports.
Support
Open an issue on the Issues tab; we reply within 24h and add fields on request.