Linkedin Company Lookalike & Suggestions Scraper
3 days trial then $25.00/month - No credit card required now
Linkedin Company Lookalike & Suggestions Scraper
3 days trial then $25.00/month - No credit card required now
Extract company lookalike and suggestions from linkedin based on the same sector / industry. Get data about name, website, phonenumber, location, description, hashtag, employee range, linkedin employee, linkedin company job url, followers, crunchbase funding data
You can access the Linkedin Company Lookalike & Suggestions 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 = { "companies": [
9 "https://www.linkedin.com/company/financial-times/",
10 "https://www.linkedin.com/company/les-echos/",
11 ] }
12
13# Run the Actor and wait for it to finish
14run = client.actor("saswave/linkedin-company-parser-with-companies-suggestions").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
Linkedin Company Lookalike & Suggestions Scraper API in Python
The Apify API client for Python is the official library that allows you to use Linkedin Company Lookalike & Suggestions 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
1 monthly user
-
3 stars
>99% runs succeeded
Created in Oct 2023
Modified 14 days ago