FreePAP Search Export
Scrape all Real Estate Listings from a PAP Search URL. #phone included!
107 users
47032 runsIt will specifically match your data scraping needs if you need to:
- find the proper flat you need on automation
- build a list of leads of real estate leads
- perform top-down market analysis and insights
Once complete, export your data to a structured and valuable dataset: a googlesheet, a s3 bucket, or simply receive it by email.
Launch your scraper on a recurring basis. With our schedule feature, you can specify how often you need to scrape, and we’ll trigger the launch at the hour suggested. For instance, every week day at 8AM.
All hours on the app are GMT+0 i.e. if you schedule at 8AM, the leboncoin scraping will start at 10AM Paris Time.
All automations do happen are cloud-based. It means you do not need to provide any computer resources to achieve the PAP scraping. Get the cloud data you need. Relax.
Use the advanced settings to precisely control the scraping tool. If you need to collect only a specific set of data, you can stop the scraping once the robot has reached a certain page. Collect exactly what you need, no more.
Increase collection power tenfold with multi-threading. If you need to collect a large data set, you can launch several bots at the same time, and maximize the scraping speed. Data scraping on steroids!
Finally, receive a nice notification directly in your mailbox, as soon as the collection is finished. No more silent end of collection, success is loud and clear.
How to?
Limitations
Who scrapes slowly, scrapes surely. For your account safety purpose, as well as for clear legal boundaries, this scraper will scrape up to 6 listings per minute. For instance, if you need to scrape 2 pages of results i.e. total 20 results, the overall collection will last 4 minutes, and you will collect a strong data set built with 20 listings.
Be careful, on PAP, each result page displays up to 170 listings. This means that if you want to collect all the results of a search with more than 170 results, you will have to segment this first search into several more precise sub-searches.
Let's take a concrete example. Let's suppose you want all the flats for rent in Paris: there are +2000 results. You will have to divide the search into more precise sub-searches:
all flats in 75001 all flats in 75002 etc.
Although all ads can in theory be linked to a telephone number, in practice, individuals do not always mention it. On average, out of 100 ads: collect 40 telephone numbers, i.e. 40% of available telephones.