Having a big employee search? No problem, we now can scrape searches that are up to 50k results without using your own LinkedIn account, without providing any cookies, and without requiring a browser extension. All you need to do is provide the search criteria.
Below is how you can do it easily in the Python language, step by step.
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Initiate a Search
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import requestsimport time# Replace this with your actual API keyapi_key = "YOUR_API_KEY"# API base URLapi_host = "fresh-linkedin-profile-data.p.rapidapi.com"def initiate_search(): url = f"https://{api_host}/big-search-employees" payload = { "geo_codes": [103644278], # United States "title_keywords": ["Owner", "Founder", "Director"], "industry_codes": [4], # Software Development "company_headcounts": ["11-50", "51-200"], "limit": 50 #set max number of results to be scraped } headers = { "x-rapidapi-key": api_key, "Content-Type": "application/json" } response = requests.post(url, json=payload, headers=headers) response_data = response.json() print("Initiate Search Response:", response_data) return response_data.get("request_id")
Each stage of the search process costs a different number of credits:
Search initiation: 50 credits. Even if the search returns no results you’ll be charged 50 credits. Then each result costs 0.7 credits, and will be charged in advanced before you actually fetch the results.
Status monitoring: free of charge. You can check it as frequently as needed until the job is complete.
Result fetching: free of charge.
For example, if your search yields 10,000 results, the total credit cost would be:50 credits + (0.7*10000 credits) = 7050 credits.