LinkedIn is the best place to meet business professionals. It has millions of users and contains global business information. Most business professionals use LinkedIn data to expand their business networks and help their companies grow. So use LinkedIn scraping to gain access to data.
Why Scrape LinkedIn Public Data?
There are numerous reasons why a company may need to extract company data from LinkedIn. You could be working on a project that necessitates checking your LinkedIn company profile or the profiles of your competitors. Alternatively, you may want to automate the recruitment process and search for great candidates by scraping profiles on a large scale. Web scraping can save your company both time and money by automating this process.
When job seekers want to automate their job search, they can use LinkedIn company scraping. They fill out specific criteria based on the company they want to work for. This is where a scraper can gather this information into a structured format and provide you with the results you seek.
If you need scraped data from LinkedIn, then use our LinkedIn data extractor services.
Using Python, we will scrape the data from this specific LinkedIn profile and save the HTML page in a local folder. We will extract information from this profile. The main point is that we will scrape the page without logging in. I want to save the LinkedIn profile page locally in the LinkedIn_page folder on D drive, which I created with Python. We must first install some packages. This is a website where you can search for and download documents.
Visit the pypi.org website to search for and download the required packages.
For a detailed explanation of LinkedIn data scraping, see the complete code below or watch the video:
import libraries:
import requests
from time import sleep
from selenium import webdriver
import chromedriver_binary
Here we use selenium to send base request for getting cookie:
driver = webdriver.Chrome()
sleep(5)
driver.maximize_window()
sleep(5)
driver.get("https://www.linkedin.com/")
sleep(5)
Save cookie in variable:
cookies_dict = {}
for cookie in driver.get_cookies():
cookies_dict[cookie['name']] = cookie['value']
driver.close()
Set headers & Send a get request:
resp = requests.get("https://www.linkedin.com/company/twitter",
cookies=cookies_dict,
headers={'user-agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/87.0.4280.88 Safari/537.36',
'accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3',
'accept-encoding': 'gzip, deflate, br',
'accept-language': 'en-US,en;q=0.9',
'upgrade-insecure-requests': '1',
'scheme': 'https'})
html = resp.text
Save Profile page in Local Folder:
HtmlPath = "D:/linkedin_pages/1.html"
page_fun = open(HtmlPath,'w',encoding='utf-8')
page_fun.write(html)
page_fun.close()
The data can be extracted from the response text. We can parse the data profile name, employee count, location, followers, about us section, website, Industry, company site, headquarters, type, when it was founded, and locations. Without logging in, it will give us the four-employee name if we need it. It is simply data parsing.
You now understand how to make a LinkedIn request. If you need multiple pages, I explain one so you can use it in a loop. You are not required to open the browser multiple times. Because the cookie is already saved in the cookies_dict variable and we are using it here, you must send a request with a different URL. So we don't have to open it over and over again; all we have to do is change the LinkedIn profile URL.
This tutorial on scraping LinkedIn public data was useful. Aside from that, we can scrape large amounts of data from LinkedIn. The number of people searching for an answer on the popular platform Quora that Is it possible to scrape data from a LinkedIn public profile?
