Profile Tracker helps you monitor changes in job titles and company affiliations for a list of LinkedIn profiles. It compares current profile data against your records and generates reports of any changes detected.
- 🔍 Automated profile validation against LinkedIn
- 📊 CSV-based input and output
- 🖥️ User-friendly GUI for file selection
- 🔐 Secure credential handling
- 📝 Detailed change tracking
- 🐞 Debug mode for troubleshooting
- Python 3.7+
- Chrome browser installed
- ChromeDriver matching your Chrome version
- LinkedIn account with login credentials
pip install pandas selenium tkinterYour input CSV must contain the following columns:
- Company Name
- First Name
- Last Name
- Job Title
- LinkedIn URL
First Name,Last Name,Company Name,Job Title,LinkedIn URL
John,Doe,Tech Corp,Software Engineer,https://www.linkedin.com/in/johndoe
Jane,Smith,Data Inc,Data Scientist,https://www.linkedin.com/in/janesmith
- Clone the repository:
https://github.com/XenosWarlocks/ProfileTracker.git
- Run the script:
python linkedin_validator.py
- Follow the GUI prompts to:
- Select your input CSV file
- Enter LinkedIn credentials
- Wait for the validation process
- Review the generated report
The tool generates a timestamped CSV file (linkedin_updates_YYYYMMDD_HHMMSS.csv) containing:
- First Name
- Last Name
- Original Company
- Original Job Title
- New Company
- New Job Title
- LinkedIn URL
- Update Date
Enable debug mode for detailed logging:
validator = LinkedInValidator()
validator.enable_debug()
validator.run()__init__(): Initializes the validator and GUI componentsvalidate_csv_file(): Handles CSV file selection and validationverify_profiles(): Performs the profile verification processsave_updates(): Generates the output reportcleanup(): Handles resource cleanup
- Rate Limiting: Add delays between profile checks to avoid - LinkedIn's rate limits
- Error Handling: Enable debug mode when troubleshooting issues
- Data Privacy: Never commit LinkedIn credentials to version control
- CSV Backup: Keep backups of your input CSV files