This project provides a tool for scraping job listings from Glassdoor using Python and Selenium for web browsing and BeautifulSoup for parsing HTML. It automates the process of fetching job data including titles, companies, locations, and salaries, making it easier to analyze the job market or to find job opportunities automatically.

• Scrape job listings from Glassdoor based on job title and location.
• Automatically handle pop-ups and web page navigations.
• Save job listings data into a CSV file for easy use and analysis.
• Run in both standard and headless mode for efficient background execution.

Before you begin, ensure you have met the following requirements:

• Python 3.6+
• pip

Clone the repository:

git clone https://github.com/yourusername/glassdoor-job-scraper.git
cd glassdoor-job-scraper

Install the required packages:

pip install -r requirements.txt

To run the scraper, navigate to the project directory and run:

python glassdoor_scraper.py

Edit the main() function in glassdoor_scraper.py to specify different job titles and locations:

def main():
    driver = setup_driver()
    try:
        login_to_glassdoor(driver, "Data Scientist", "New York, United States")
        load_more_jobs(driver)
        job_data = scrape_jobs(driver)
        save_to_csv(job_data, "glassdoor_jobs.csv")
    finally:
        driver.quit()

The script will output a CSV file named glassdoor_jobs.csv containing the scraped job listings. Each row represents a different job and includes columns for the job title, company, location, salary, and a link to the job posting.

Distributed under the MIT License.