Funda.nl Scraper ๐Ÿ 

Funda.nl Scraper ๐Ÿ 

Scrape property listings from Funda.nl - Extract detailed real estate data including prices, locations, property features, and more. Perfect for real estate analysis and market research in the Netherlands.

REAL_ESTATEINTEGRATIONSApify

๐Ÿ” What does Funda.nl Scraper do?

This actor scrapes real estate listings from Funda.nl, the Netherlands' leading property website. It extracts comprehensive property data, enabling you to gather valuable real estate market insights.

โœจ Features

  • ๐Ÿ˜๏ธ Scrapes detailed property listings from search results
  • ๐Ÿ“Š Extracts comprehensive property information
  • ๐Ÿ”„ Supports pagination and dynamic loading
  • ๐Ÿš€ High-performance with built-in proxy rotation
  • โšก Handles rate limiting and anti-bot measures
  • ๐Ÿ’พ Outputs structured JSON data

๐ŸŽฏ Use Cases

  • ๐Ÿ“ˆ Real estate market analysis
  • ๐Ÿข Property investment research
  • ๐Ÿ’ฐ Price trend monitoring
  • ๐Ÿ—บ๏ธ Geographic market analysis
  • ๐Ÿ“Š Data aggregation for real estate platforms

๐Ÿ’ก Input Parameters

The actor accepts the following input parameters:

  • searchUrls (Required): Array of Funda.nl search URLs to scrape
  • maxItems (Optional): Maximum number of items to scrape
  • proxyConfiguration (Optional): Proxy settings for the scraper

๐Ÿ“ Output Format

The actor outputs data in JSON format, including:

  • Property details (price, location, size)
  • Property features and amenities
  • Listing information
  • Images and media links
  • Agent contact information

๐Ÿ”จ Usage

  1. Input your Funda.nl search URL(s)
  2. Configure optional parameters
  3. Run the actor and collect the results

๐Ÿ’ช Limitations

  • Respects Funda.nl's terms of service
  • Rate limiting applied to prevent blocking
  • Maximum of 10000 results per search URL

Input Example

A full explanation of an input example in JSON.

1{
2        "searchUrls": ["https://www.funda.nl/en/zoeken/koop?selected_area=%5B%22bergen-li%22%5D&search_result=1"],
3        "maxItems": 30,
4        "proxyConfiguration": {
5            "useApifyProxy": false,
6            "apifyProxyGroups": [
7                "RESIDENTIAL"
8            ]
9        }
10    }

Output sample

The results will be wrapped into a dataset which you can always find in theย Storageย tab. Here's an excerpt from the data you'd get if you apply the input parameters above:

And here is the same data but in JSON. You can choose in which format to download your data: JSON, JSONL, Excel spreadsheet, HTML table, CSV, or XML.

1[
2	{
3		"highlight": {},
4		"agent": [
5			{
6				"logo_type": "new",
7				"relative_url": "/makelaar/13026-smedema-makelaars-en-taxateurs/",
8				"is_primary": true,
9				"logo_id": 141935042,
10				"name": "Smedema Makelaars & Taxateurs",
11				"association": "NVM",
12				"id": 13026
13			}
14		],
15		"number_of_bedrooms": 3,
16		"address": {
17			"country": "NL",
18			"province": "Limburg",
19			"wijk": "Nieuw-Bergen",
20			"city": "Bergen (LI)",
21			"neighbourhood": "Nieuw-Bergen Kern",
22			"identifiers": [
23				"nl",
24				"bergen-li/straat-siebengewaldseweg",
25				"bergen-li",
26				"gemeente-bergen-li",
27				"provincie-limburg",
28				"bergen-li/nieuw-bergen-kern",
29				"bergen-li/wijk-nieuw-bergen",
30				"5854pc",
31				"5854",
32				"regio-noord-limburg"
33			],
34			"municipality": "Bergen (LI)",
35			"is_bag_address": true,
36			"house_number": "38",
37			"postal_code": "5854PC",
38			"street_name": "Siebengewaldseweg"
39		},
40		"plot_area_range": {
41			"gte": 456,
42			"lte": 456
43		},
44		"blikvanger": {
45			"enabled": false
46		},
47		"object_type": "house",
48		"energy_label": "A",
49		"floor_area": [
50			125
51		],
52		"floor_area_range": {
53			"gte": 125,
54			"lte": 125
55		},
56		"type": "single",
57		"thumbnail_id": [
58			199527498,
59			199527499,
60			199527500,
61			199527501,
62			199527503,
63			199527505,
64			199527509,
65			199527512,
66			199527514,
67			199527517,
68			199527520,
69			199527524,
70			199527527,
71			199527530,
72			199527533,
73			199527536,
74			199527538,
75			199527541,
76			199527542,
77			199527543,
78			199527546,
79			199527547,
80			199527548,
81			199527549,
82			199527550,
83			199527553,
84			199527556,
85			199527559,
86			199527562,
87			199527567,
88			199527569,
89			199527572,
90			199527575,
91			199527581,
92			199527584,
93			199527586,
94			199527588,
95			199527589,
96			199527590,
97			199527592,
98			199527594,
99			199527597,
100			199527600,
101			199527605,
102			199527602,
103			199527631
104		],
105		"offering_type": [
106			"buy"
107		],
108		"price": {
109			"selling_price": [
110				499000
111			],
112			"selling_price_range": {
113				"gte": 499000,
114				"lte": 499000
115			},
116			"selling_price_type": "regular",
117			"selling_price_condition": "kosten_koper"
118		},
119		"plot_area": [
120			456
121		],
122		"id": 7332972,
123		"available_media_types": [
124			"floor_plan",
125			"photo_360",
126			"video"
127		],
128		"publish_date": "2024-10-25T15:15:02.5130000",
129		"object_detail_page_relative_url": "/detail/koop/bergen-li/huis-siebengewaldseweg-38/43787335/",
130		"status": "none",
131		"number_of_rooms": 7,
132		"_index": "listings-wonen-searcher-alias-prod",
133		"_id": "7332972",
134		"_score": null,
135		"sort": [
136			"basis",
137			59000,
138			7332972
139		],
140		"_click_id": 0,
141		"placement": "listing_results_normal",
142		"globalId": 7332972
143	},
144    ...
145]

Frequently Asked Questions

Is it legal to scrape job listings or public data?

Yes, if you're scraping publicly available data for personal or internal use. Always review Websute's Terms of Service before large-scale use or redistribution.

Do I need to code to use this scraper?

No. This is a no-code tool โ€” just enter a job title, location, and run the scraper directly from your dashboard or Apify actor page.

What data does it extract?

It extracts job titles, companies, salaries (if available), descriptions, locations, and post dates. You can export all of it to Excel or JSON.

Can I scrape multiple pages or filter by location?

Yes, you can scrape multiple pages and refine by job title, location, keyword, or more depending on the input settings you use.

How do I get started?

You can use the Try Now button on this page to go to the scraper. Youโ€™ll be guided to input a search term and get structured results. No setup needed!