This project is a LinkedIn scraping tool built using Python and Selenium, designed to automate various LinkedIn tasks, such as scraping the news feed, extracting posts and scraping data from groups.

• Login Automation: Automates the login process to LinkedIn using Selenium and using extracted coockies.
• Feed Scraping: Extracts posts from your LinkedIn feed.
• Post Scraping: Scrapes posts from individual user profiles.
• Group Data Extraction: Retrieves data from LinkedIn groups.

1. Clone the repository:

git clone https://github.com/your-username/LinkedInScraper.git

2. Navigate to the project directory:

cd LinkedInScraper

3. Install the dependencies:

pip install -r requirements.txt

4. If the provided chromedriver version is not compatible with your chrome browser download the appropriate version and place it in the webDriver directory. You can download it from here.

1. Config File: Ensure that the config file, where your LinkedIn credentials and other configurations are stored, has the .py extension (i.e., config.py). Place it inside the LinkedInScraper folder.

2. Cookie Storage: The LinkedIn cookies will be saved and reused to avoid logging in every time. Place the linkedin_cookies.pkl file in the LinkedInScraper folder. This file will be automatically created after the first successful login. Make sure you have the file in place before running scripts that require LinkedIn authentication.

Run the Python file from the command line or terminal:

python main.py

/LinkedInScraper
│
│
├── /webDriver
│   └── chromedriver.exe  # WebDriver executables
│
├── /pages
│   ├── login_page.py  # Login Page Object Model
│   └── feed_page.py  # Feed Scraper
│
├── /utils
│   └── cookies.py  # File that contain linkedin user coockies
│
├── config.py  # Configuration like URLs, credentials, etc.
├── requirements.txt.py  # requirement file.
├── linkedin_cookies.pkl  # Python dependencies
├── README.md  # Read me file
├── init.py  # File to initialize variables
└── main.py  # Main script to run tests