How to Extract Profiles from LinkedIn using Python and Selenium?

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Today, we would scrape data from a specific LinkedIn profile and save HTML pages in the local folders using Python. We would extract data from these profiles. Here, the critical thing is that we would extract the pages without login. We wish to save a LinkedIn profile page nearby in the folder named linkedin_page in drive D we have created with Python. For that, we need to install a few packages. That is the website from where you could quest and download the vital packages.

Open the pypi.org site, and you can search or download the necessary packages.

Observe Complete Code or Watch Video to Get Detailed Explanation about LinkedIn Profile Data Scraping:

Import libraries:

Here, we utilize selenium for sending base requests to get cookies:

Save all the cookie in variables:

Set headers and send the get request:

Save a profile page in the local folder:

You could parse data from a response text. We could parse profile name, total employees, followers, location, website, Industry, about us section, company website, type, headquarters, found year, places, and more.

Without login, this will provide us with four-employee names if you need them. This is just data parsing.

As you know how to send a request on LinkedIn, we describe one page if you want numerous pages; therefore, you can utilize it for the loop. You don’t need to open a browser many times. You need to send the request with different URLs as the cookies are already saved with cookies_dict variables, which we have applied here. Therefore, we don’t need to open that repeatedly. Only we need to change a LinkedIn profile URL.

We hope this tutorial will help extract LinkedIn public data. Besides this, we can extract bulk data from LinkedIn. For more information, contact Actowiz Solutions now! Contact us for your mobile app or web scraping service requirements.