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.
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.
The actor accepts the following input parameters:
searchUrls
(Required): Array of Funda.nl search URLs to scrapemaxItems
(Optional): Maximum number of items to scrapeproxyConfiguration
(Optional): Proxy settings for the scraperThe actor outputs data in JSON format, including:
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 }
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]
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.
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.
It extracts job titles, companies, salaries (if available), descriptions, locations, and post dates. You can export all of it to Excel or JSON.
Yes, you can scrape multiple pages and refine by job title, location, keyword, or more depending on the input settings you use.
You can use the Try Now button on this page to go to the scraper. Youโll be guided to input a search term and get structured results. No setup needed!