InboxIQ is a powerful, offline solution for managing your emails. By converting a standard .mbox file into a searchable, filterable, and dashboard-style database, this system gives you full control over your email data without relying on external services.

This project is ideal for anyone who needs to quickly find information in old emails, analyze their email history, or simply access their data in a clean, structured way.

• Offline Access: Your entire email database is stored locally on your machine.
• Powerful Search: Quickly find emails based on subject, sender, body content, or even custom extracted fields.
• Advanced Filtering: Filter your emails by specific criteria like phone numbers, names, or other data points you define.
• Dashboard View: Get a high-level overview of your emails in a clean, table-based interface.
• Full Data Control: Your data remains yours; no cloud uploads or third-party access is required.

The system operates in three main phases, leveraging Python to transform raw email data into a structured and interactive database.

The process begins by using Python's built-in mailbox library to read and process the .mbox file. This script iterates through each email, extracting essential data like the subject, sender, and body content.

A key part of this phase is data extraction. Using regular expressions, the parser can identify and pull out specific information (e.g., names, phone numbers) from the email body, turning unstructured text into valuable, searchable fields.

Once parsed, the extracted email data is stored in a structured database. SQLite is the recommended choice for this project due to its serverless, file-based nature and seamless integration with Python.

A table is created with columns designed to store the parsed data, including a unique message_id, subject, sender, body_text, and any custom extracted fields like extracted_name or extracted_phone.

A lightweight web framework, such as Flask or Django, is used to create a local, browser-based user interface. This front-end connects to the SQLite database to:

• Display a Dashboard: Presenting a list of emails in a clean, tabular format.
• Enable Filtering & Search: Allowing users to dynamically query the database based on their input.
• Provide a Detailed View: Showing the full content of an email, with a convenient option to copy the body text.

To get started with InboxIQ, you'll need a .mbox file and a Python environment. The project is designed to be self-contained and easy to set up.

• Python 3.x
• A .mbox file (most email clients, like Thunderbird or Apple Mail, can export emails in this format)

1. Clone this repository:

   git clone https://github.com/yourusername/InboxIQ.git
   cd InboxIQ

2. Install the required Python packages:

   pip install -r requirements.txt

3. Run the parsing script to create your database:

   python parse_mbox.py path/to/your/emails.mbox

4. Start the web application:

   python run_app.py

5. Open your browser and navigate to http://127.0.0.1:5000 to access the InboxIQ dashboard.

Contributions are welcome! If you have suggestions for new features, improvements, or bug fixes, please open an issue or submit a pull request.

This project is licensed under the MIT License. See the LICENSE file for details.