# 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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