Skool Members Scraper (Pay Per Results)
Pay $5.00 for 1,000 members/users
Skool Members Scraper (Pay Per Results)
Pay $5.00 for 1,000 members/users
Boost your business leads with our Skool.com Groups' Members/Users Scraper. Gather user details like names, emails, and social media links (Facebook, Instagram, LinkedIn, Twitter, etc.). It is ideal for market research, competitor analysis, and lead generation. Save time with our advanced scraper.
You can access the Skool Members Scraper (Pay Per Results) 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 "startUrls": [{ "url": "https://www.skool.com/ai-automation-mastery/-/members" }],
10 "cookies": [],
11 "proxy": {
12 "useApifyProxy": True,
13 "apifyProxyGroups": ["RESIDENTIAL"],
14 },
15}
16
17# Run the Actor and wait for it to finish
18run = client.actor("memo23/skool-members-scraper").call(run_input=run_input)
19
20# Fetch and print Actor results from the run's dataset (if there are any)
21print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
22for item in client.dataset(run["defaultDatasetId"]).iterate_items():
23 print(item)
24
25# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-startSkool Members Scraper (Pay Per Results) API in Python
The Apify API client for Python is the official library that allows you to use Skool Members Scraper (Pay Per Results) API in Python, providing convenience functions and automatic retries on errors.
Install the apify-client
pip install apify-clientOther API clients include:
Muhamed DidovicActor Metrics
30 monthly users
-
13 stars
>99% runs succeeded
0.41 hours response time
Created in Jun 2024
Modified 20 days ago
