# variable linkedin_url is equal to the list comprehension We have to assign the "linkedin_urls" variable to equal the list comprehension, which contains a For Loop that unpacks each value and extracts the text for each element in the list. Linkedin_urls = driver.find_elements_by_class_name( 'iUh30') To avoid extracting unwanted advertisements, we will only specify the "iUh30" class to ensure we only extract LinkedIn profile URL's. LinkedIn user URLĪs you can see above, the class value "iUh30" for LinkedIn URLs is different to that of the advertisement values of "UdQCqe". Using Inspect Element on the webpage I checked to see if there was any unique identifier separating LinkedIn URL's from the advertisement URLs. Similarly to what we have previously done, we will select an attribute for the main search form on Google. click() to mimic button clickĪfter successfully logging into your LinkedIn account, we will navigate back to Google to perform a specific search query. Sign_in_button = driver.find_element_by_xpath(. # driver.get method() will navigate to a page given by the URL address # specifies the path to the chromedriver.exeĭriver = webdriver.Chrome( '/Users/username/bin/chromedriver') # writerow() method to the write to the file object Writer = csv.writer(open(parameters.file_name, 'wb')) # defining new variable passing two parameters """ filename: script.py """ # imports from selenium import webdriver If your LinkedIn credentials were correct, a new Google Chrome window should have appeared, navigated to the LinkedIn webpage and logged into your account.Ĭode so far. # Navigate to the directory where the file is cd Desktop Within a new terminal (not ipython) navigate to the directory that the file is contained in and execute the file using a similar command. Once all command lines from the ipython terminal have successfully tested, copy each line into a new python file (Desktop/script.py). click() to mimic button click log_ in_button.click() # locate submit button by_xpath log_ in_button = driver.find_element_by_xpath(. # locate submit button by_class_id log_ in_button = driver.find_element_by_class_id( 'login submit-button') # locate submit button by_class_name log_ in_button = driver.find_element_by_class_name( 'login-submit') The click() method will mimic a button click which submits our login request. Below are 3 different ways in which we can find this attribute but we only require one. Password = driver.find_element_by_class_name( 'login-password')Īdditionally we have to locate the submit button in order to successfully log in. nd_keys( the password attribute is the same process as the email attribute, with the values for its class and id being "login-password". Username = driver.find_element_by_class_name( 'login-email') The below lines will find the email element on the page and the send_keys() method contains the email address to be entered, simulating key strokes. Its offers different features including proper indentation and syntax highlighting. Open a new terminal window and type "ipython", which is an interactive shell built with Python. In order to guarantee access to user profiles, we will need to login to a LinkedIn account, so will also automate this process. Open your Terminal and enter the following install commands needed for this task. Also you will need to have a Google Chrome browser application for this to work. Prerequisite Downloads & Installsĭownload ChromeDriver, which is a separate executable that WebDriver uses to control Chrome. The number of web pages you can scrape on LinkedIn is limited, which is why I will only be scraping key data points from 10 different user profiles. Tools Requiredįor this task I will be using Selenium, which is a tool for writing automated tests for web applications. With this in mind, I decided to attempt extracting data from LinkedIn profiles just to see how difficult it would, especially as I am still in my infancy of learning Python. LinkedIn have since made its site more restrictive to web scraping tools. This technique known as Web Scraping, is the automated process where the HTML of a web page is used to extract data. HiQ Labs used software to extract LinkedIn data in order to build algorithms for products capable of predicting employee behaviours, such as when an employee might quit their job.
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