LinkedIn Applicant Scraper

This project is a LinkedIn applicant scraping tool built using Python and Selenium. It automates the process of logging into LinkedIn, navigating to a specific job posting, collecting applicant data (name, location, email, phone, and profile link), and saving this data into a CSV file.

Features

• Login to LinkedIn: The scraper can log into LinkedIn using provided credentials.
• Navigate to Job Postings: Once logged in, it navigates to a specified job URL to collect applicant data.
• Collect Applicant Data: For each applicant, it gathers key details such as:
  • Name
  • Location
  • Email
  • Phone number
  • LinkedIn profile link
• Handle Pagination: The scraper handles pagination and processes all applicants across multiple pages.
• Save to CSV: After collecting data, it saves the information into a CSV file for further analysis or processing.

Requirements

Before running the scraper, ensure that you have the following dependencies installed:

• Python 3.x
• pip (Python package installer)

You can install the necessary Python packages using the following command:

pip install -r requirements.txt

Setup and Configuration

1. Clone the Repository: Clone this project to your local machine:

git clone https://github.com/lucasudar/linkedin_applicants_scraper.git

2. Configure LinkedIn Credentials: Create a configuration file app-config.properties with your LinkedIn credentials and job URL. Example app-config.properties file:

username=your_linkedin_username
password=your_linkedin_password
url=https://www.linkedin.com/jobs/view/job-id

3. Setup your env.
4. Run script.