Fast LinkedIn Ad Library Scraper (pay per result) avatar

Fast LinkedIn Ad Library Scraper (pay per result)

Try for free

Pay $3.00 for 1,000 results

View all Actors
Fast LinkedIn Ad Library Scraper (pay per result)

Fast LinkedIn Ad Library Scraper (pay per result)

aymorato/fast-linkedin-ad-library-scraper-pay-per-result
Try for free

Pay $3.00 for 1,000 results

Easily Scrape LinkedIn's Unlimited Scroll Ad Library without the Need for Proxies.

You can access the Fast LinkedIn Ad Library Scraper (pay per result) 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    "startUrl": "https://www.linkedin.com/ad-library/search?accountOwner=amd",
10    "maxItems": 1000,
11}
12
13# Run the Actor and wait for it to finish
14run = client.actor("aymorato/fast-linkedin-ad-library-scraper-pay-per-result").call(run_input=run_input)
15
16# Fetch and print Actor results from the run's dataset (if there are any)
17print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
18for item in client.dataset(run["defaultDatasetId"]).iterate_items():
19    print(item)
20
21# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

Fast LinkedIn Ad Library Scraper (pay per result) API in Python

The Apify API client for Python is the official library that allows you to use Fast LinkedIn Ad Library Scraper (pay per result) API in Python, providing convenience functions and automatic retries on errors.

Install the apify-client

pip install apify-client

Other API clients include:

Developer
Maintained by Community
Actor metrics
  • 4 monthly users
  • 1 star
  • 100.0% runs succeeded
  • Created in Mar 2024
  • Modified 5 months ago