> ## Documentation Index
> Fetch the complete documentation index at: https://fdocs.info/llms.txt
> Use this file to discover all available pages before exploring further.

# How to search employees without 2500 limit?

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.

## Code demonstration

For instance, let’s say you need a lead list with the following criteria:

* **Job title includes**: owner, founder, or director

* **Location**: United States

* **Industry**: Software Development

* **Company headcount range**: 11-50

* **For more filters**: Please check out this [page](/tutorial/understanding-employee-search-filters)

Below is how you can do it easily in the Python language, step by step.

<Steps>
  <Step title="Initiate a Search">
    ```python theme={null}
    import requests
    import time

    # Replace this with your actual API key
    api_key = "YOUR_API_KEY"

    # API base URL
    api_host = "web-scraping-api2.p.rapidapi.com"

    def initiate_search():
        url = f"https://{api_host}/lead-search-at-scale"
        payload = {
            "geo_codes": [103644278],  # United States
            "title_keywords": ["Owner", "Founder", "Director"],
            "industry_codes": [4],  # Software Development
            "company_headcounts": ["11-50", "51-200"]
        }
        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")
    ```
  </Step>

  <Step title="Check Search Progress">
    ```python theme={null}
    def check_search_status(request_id):
        url = f"https://{api_host}/check-search-status"
        querystring = {"request_id": request_id}
        headers = {
            "x-rapidapi-key": api_key
        }

        response = requests.get(url, headers=headers, params=querystring)
        response_data = response.json()
        print("Check Search Status Response:", response_data)
        return response_data.get("status") #pending, processing, or done


    ```
  </Step>

  <Step title="Retrieve Search Results">
    ```python theme={null}
    def get_search_results(request_id):
        url = f"https://{api_host}/get-search-results"
        headers = {
            "x-rapidapi-key": api_key
        }

        all_results = []
        page = 1

        while True:
            querystring = {"request_id": request_id, "page": page}
            response = requests.get(url, headers=headers, params=querystring)
            response_data = response.json()

            if response_data.get("data"):
                all_results.extend(response_data.get("data"))
                page += 1
            else:
                #no more results
                break

        return all_results

    ```
  </Step>

  <Step title="Put All Together">
    ```python theme={null}
    def main():
        # initiate search
        request_id = initiate_search()
        if not request_id:
            print("Failed to initiate search")
            return

        # monitor search progress
        while True:
            status = check_search_status(request_id)
            if status == "done":
                #search completed
                break
            # wait for some minutes
            time.sleep(300)

        # ready to fetch results
        results = get_search_results(request_id)
        print(f"Total Results Fetched: {len(results)}")
        print("Results:", results)

    if __name__ == "__main__":
        main()
    ```
  </Step>
</Steps>

## Prerequisites

Before running the script, ensure you have:

1. Permission to use the search feature. Please reach out us at: [support@fdocs.info](mailto:support@fdocs.info) to obtain it.
2. Python installed on your system.
3. The requests library installed. You can install it using:

```bash theme={null}
pip install requests
```

## How much does it cost?

Each stage of the search process costs a different number of credits:

1. **Search initiation: 50 credits. Even if the search returns no results you’ll be charged 50 credits. Then each result costs 1 credits, and will be charged in advanced before you actually fetch the results.**

2. **Status monitoring**: free of charge. You can check it as frequently as needed until the job is complete.

3. **Result fetching**: free of charge.

For example, if your search yields 10,000 results, the total credit cost would be:

50 credits + (1\*10000 credits) = **10050** credits.