Mediamarkt Product Search Scraper
3 days trial then $20.00/month - No credit card required now
Mediamarkt Product Search Scraper
3 days trial then $20.00/month - No credit card required now
The Mediamarkt Product Search Scraper extracts detailed product data from Mediamarkt, including name, price, brand, etc., using search query URLs. It's perfect for market research, trend analysis, lead generation, and campaign planning.
You can access the Mediamarkt Product Search 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, you’ll 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 "urls": ["https://www.mediamarkt.de/de/category/playstation-635.html?page=2"],
10 "max_retries_per_url": 2,
11 "proxy": {
12 "useApifyProxy": True,
13 "apifyProxyGroups": ["RESIDENTIAL"],
14 "apifyProxyCountry": "US",
15 },
16}
17
18# Run the Actor and wait for it to finish
19run = client.actor("ecomscrape/mediamarkt-product-search-scraper").call(run_input=run_input)
20
21# Fetch and print Actor results from the run's dataset (if there are any)
22print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
23for item in client.dataset(run["defaultDatasetId"]).iterate_items():
24 print(item)
25
26# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-startMediamarkt Product Search Scraper API in Python
The Apify API client for Python is the official library that allows you to use Mediamarkt Product Search Scraper API in Python, providing convenience functions and automatic retries on errors.
Install the apify-client
pip install apify-clientOther API clients include:
ecomscrapeActor Metrics
1 monthly user
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>99% runs succeeded
Created in Jan 2025
Modified 17 hours ago
