Funda In Business Scraper

🏡 What is Fundainbusiness Real Estate Data Scraper?

Our FundainBusiness.nl Real Estate Data Scraper is a powerful tool designed to extract valuable information from commercial real estate listings on FundainBusiness.nl. With this tool, you can effortlessly search for properties in any location and gather essential data points such as prices, addresses, descriptions, and more.

It's important to note that while web scraping can provide valuable insights, it's crucial to respect copyright rules and terms of service of the websites you scrape. Ensure that you're using the scraped data responsibly and in compliance with legal regulations.

For more information on how to use the scraper and ensure legal compliance, please refer to the documentation and guidelines provided with the tool.

Here's an example of the type of data you can extract with our scraper:

1{
2    "url": "https://www.fundainbusiness.nl/winkel/hilversum/object-43438503-huygensstraat-17-a/",
3    "title": "Huygensstraat 17 A",
4    "metaDescription": "Winkel Hilversum | Zoek winkels te koop: Huygensstraat 17 A 1222 TJ Hilversum",
5    "description": "Tegen het centrum  aan  gelegen hoekwinkelpand  in gebruik  als kapsalon.  Het  NS  station, de markt en horecagelegenheden zijn op  loopafstand  bereikbaar.  Indeling:   Winkel heeft een  verkoopruimte van  ca.  45  m² met toilet en berging, Frontbreedte van ca. 10 meter  Voorzien van een c.v. installatie en systeemplafonds inclusief verlichting.  Vigerend bestemmingsplan: Over 't Spoor. Bestemming: Gemengd-1, d.w.z. dienstverlening, wonen en bedrijven. Functieaanduiding is detailhandel.   Indien de functie wordt gewijzigd is dat vergunningsplichtig en daarmee betreft het een toekomstige ontwikkeling  (Parkeerbeleid Hilversum 2023).  Dit betekent dat in elk plan parkeren opgelost dient te worden op eigen terrein. Dit kan zijn op het betreffende perceel zelf, of als dit niet kan op een terrein elders. Ook is het mogelijk om een deel van de parkeereis (de berekende parkeervraag) af te kopen.",
6    "price": "€ 145.000 k.k.",
7    "vraagPrijs": "€ 145.000 kosten koper",
8    "status": "Beschikbaar",
9    "aanvaarding": "In overleg",
10    "eigendomssituatie": "",
11    "hoofdfunctie": "Winkel met showroom",
12    "soortBouw": "Bestaande bouw",
13    "bouwjaar": "1929",
14    "oppervlakte": "45 m²",
15    "bedrijfshalOppervlak": "",
16    "voorzieningen": "",
17    "energielabel": "D",
18    "ligging": "In woonwijk",
19    "bereikbaarheid": "",
20    "buurtNaam": "Johannes Geradtswegbuurt, Hilversum",
21    "constructionDetails": {
22        "hoofdfunctie": "Winkel met showroom",
23        "soort_bouw": "Bestaande bouw",
24        "bouwjaar": "1929"
25    },
26    "amenities": {
27        "treinstation": "Treinstation",
28        "bushalte": "Bushalte",
29        "supermarkt": "Supermarkt"
30    },
31    "surfaceDetails": {
32        "oppervlakte": "45 m²",
33        "verkoopvloeroppervlakte": "45 m²",
34        "breedte_gevel": "10 m"
35    },
36    "transferDetails": {
37        "vraagprijs": "€ 145.000 kosten koper",
38        "aangeboden_sinds": "",
39        "status": "Beschikbaar",
40        "aanvaarding": "In overleg"
41    },
42    "indelingDetails": {
43        "aantal_bouwlagen": "1 bouwlaag"
44    },
45    "objectNumber": "43438503"
46}

Please note that while our scraper can provide valuable insights, it's crucial to respect copyright rules and terms of service of the websites you scrape. Ensure that you're using the scraped data responsibly and in compliance with legal regulations.

How it works

This code is a JavaScript script that uses Cheerio to scrape data from a website. It then stores the website titles in a dataset.

• The crawler starts with URLs provided from the input startUrls field defined by the input schema. Number of scraped pages is limited by maxPagesPerCrawl field from the input schema.
• The crawler uses requestHandler for each URL to extract the data from the page with the Cheerio library and to save the title and URL of each page to the dataset. It also logs out each result that is being saved.

Resources

• Video tutorial on building a scraper using CheerioCrawler
• Written tutorial on building a scraper using CheerioCrawler
• Web scraping with Cheerio in 2023
• How to scrape a dynamic page using Cheerio
• Integration with Zapier, Make, Google Drive and others
• Video guide on getting data using Apify API
• A short guide on how to create Actors using code templates:

Getting started

For complete information see this article. In short, you will:

1. Build the Actor
2. Run the Actor

Pull the Actor for local development

If you would like to develop locally, you can pull the existing Actor from Apify console using Apify CLI:

1. Install apify-cli

   Using Homebrew

   brew install apify-cli
   

   Using NPM

   npm -g install apify-cli
   

2. Pull the Actor by its unique <ActorId>, which is one of the following:

   • unique name of the Actor to pull (e.g. "apify/hello-world")
   • or ID of the Actor to pull (e.g. "E2jjCZBezvAZnX8Rb")

   You can find both by clicking on the Actor title at the top of the page, which will open a modal containing both Actor unique name and Actor ID.

   This command will copy the Actor into the current directory on your local machine.

   apify pull <ActorId>
   

Documentation reference

To learn more about Apify and Actors, take a look at the following resources:

• Apify SDK for JavaScript documentation
• Apify SDK for Python documentation
• Apify Platform documentation
• Join our developer community on Discord