Facebook Marketplace Scraper
Pay $5.00 for 1,000 results
Facebook Marketplace Scraper
Pay $5.00 for 1,000 results
Extract data from one or multiple Facebook Marketplace listings. Scrape data on apartments, whole categories, items for sale, prices, location and sellers. Export scraped data in JSON, CSV, and Excel, run the scraper via API, schedule and monitor runs or integrate with other tools.
Do you want to learn more about this Actor?
Get a demoYou can access the Facebook Marketplace Scraper programmatically from your own Python applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, youāll need an Apify account and your API token, found in Integrations settings in Apify Console.
1from apify_client import ApifyClient
2
3# Initialize the ApifyClient with your Apify API token
4# Replace '<YOUR_API_TOKEN>' with your token.
5client = ApifyClient("<YOUR_API_TOKEN>")
6
7# Prepare the Actor input
8run_input = {
9 "startUrls": [
10 { "url": "https://www.facebook.com/marketplace/prague/home-improvements" },
11 { "url": "https://www.facebook.com/marketplace/prague/search/?query=apartment" },
12 ],
13 "resultsLimit": 20,
14}
15
16# Run the Actor and wait for it to finish
17run = client.actor("apify/facebook-marketplace-scraper").call(run_input=run_input)
18
19# Fetch and print Actor results from the run's dataset (if there are any)
20print("š¾ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
21for item in client.dataset(run["defaultDatasetId"]).iterate_items():
22 print(item)
23
24# š Want to learn more š? Go to ā https://docs.apify.com/api/client/python/docs/quick-start
š Facebook Marketplace Scraper API in Python
The Apify API client for Python is the official library that allows you to use Facebook Marketplace Scraper API in Python, providing convenience functions and automatic retries on errors.
Install the apify-client
pip install apify-client
Other API clients include:
Actor Metrics
61 monthly users
-
10 stars
>99% runs succeeded
28 days response time
Created in May 2024
Modified 3 days ago