GADI-email_filter

GADI EMAIL FILTER is a Python-based tool that cleans bulk email lists by cross-checking new emails against an existing database. It removes duplicates, filters invalid emails, and logs removed entries. With a user-friendly Tkinter GUI, backup creation, multiple file support, and a summary report, it ensures efficient and accurate email management.

Features

• 📂 Bulk Email Cross-Check – Compares new emails with an existing database and removes duplicates.
• ✅ Invalid Email Detection – Identifies and removes improperly formatted emails (e.g., missing @).
• 📊 Summary Report – Provides counts of removed, invalid, and remaining emails.
• 💾 Automatic Backup – Saves a backup of the collected emails before modification.
• 🔄 Multiple File Support – Allows importing multiple files for comparison.
• 🖥 User-Friendly GUI – Built with Tkinter or PyQt for easy operation.
• Fast Processing – Optimized for handling large datasets (~1 crore emails). 🛠️ Requirements & Installation Before running the project, ensure your system has the necessary dependencies installed.

📌 Requirements

• Python 3.7+
• Required libraries: pandas, openpyxl, tkinter

Installation of Tool

1. Clone the repository*

   git clone https://github.com/20501A0407/GADI-email_filter.git
   cd GADI-email_filter

2. Install dependencies*

   pip install -r requirements.txt

After installation follow the below steps to run the application

##🔧 Running the Tool Navigate to the project directory and execute the script:

cd path/to/GADI-email_filter  # Change to the project directory
python email_filter_tool.py  # Run the tool

If using a GUI version:

python gui_tool.py

📂 How to Use

1. Upload Database: Load your existing email dataset (CSV/Excel).
2. Select Collected Emails File: Choose the new email data file for filtering.
3. Run the Process: Click the button to start filtering.
4. View Results: Check the logs and reports for filtered data.

License

This project is licensed under the MIT License – you are free to modify and distribute it.

Contributing

Feel free to submit pull requests for improvements!