PDF Structured Data Extractor PRO — Python Tkinter App (Full Source Code)

PDF Structured Data Extractor PRO is an enterprise-grade Python desktop application built with Tkinter and ttkbootstrap for scanning folders, extracting structured fields from PDFs, storing results in SQLite, and exporting formatted Excel reports.

This repository contains the full source code, allowing you to customize:

• Structured field detection logic
• OCR confidence filtering
• AI-based handwriting suppression
• Multi-threaded processing
• SQLite database storage
• Excel export formatting
• UI styling and branding

Designed for professional document automation workflows.

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🌟 SCREENSHOT

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🌟 FEATURES

• 📂 Recursive Folder Scanning — Scan any directory for PDF files
• 📄 Digital PDF Text Extraction — Extract embedded text using pdfplumber
• 🔎 Smart OCR Fallback — Automatically applies OCR when digital text is unavailable
• 🧠 AI-Based Handwriting Suppression — Filters low-confidence and irregular OCR results
• 🏷 Structured Field Extraction — Extracts fields such as:
  • Name
  • Date
  • Document ID
  • (Custom fields easily configurable via regex)
• 🗄 SQLite Database Storage — Automatically stores extracted records
• 📊 Live Results Table — Displays extracted structured fields in real time
• 📤 Formatted Excel Export (.xlsx) — Styled headers, auto column width, frozen rows
• ⚡ Multi-threaded Processing — Faster concurrent PDF handling
• ⏸ Pause / Resume / Stop Controls — Real-time scanning control
• 🖥 Modern UI — Clean ttkbootstrap-powered interface

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🚀 INSTALLATION

1. Clone or download this repository:

git clone https://github.com/rogers-cyber/PDFStructuredDataExtractorPRO.git
cd PDFStructuredDataExtractorPRO

2. Install required Python packages:

pip install ttkbootstrap pdfplumber pytesseract pdf2image pillow openpyxl

3. Install external dependencies:

Tesseract OCR (Required for OCR fallback)
Download: https://github.com/tesseract-ocr/tesseract
Ensure Tesseract is added to your system PATH.

Poppler (Required for pdf2image)

Windows:

• Install Poppler and add to PATH

macOS:

brew install poppler

Linux:

sudo apt install poppler-utils

4. Run the application:

python main.py

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💡 USAGE

1. Select Folder

   • Click "Select Folder"
   • Choose the directory containing PDF documents

2. Automatic Processing

   • The app scans recursively for .pdf files
   • If digital text exists → extracts directly
   • If not → applies OCR
   • AI-based filtering removes low-confidence and irregular (handwritten) text

3. Structured Field Detection

The engine automatically extracts:

• Name (example: Name: John Smith)
• Date (example: 12/31/2025)
• Document ID (example: ID: ABC-12345)

You can modify the regex logic inside:

• extract_name()
• extract_date()
• extract_id()

4. Pause / Resume / Stop Scan

• Pause anytime
• Resume processing
• Stop the scan completely

5. Database Storage

Each processed document is stored in:

extracted_data.db

Table Structure:

Column	Description
file_name	PDF file name
name	Extracted name field
date	Extracted date field
document_id	Extracted ID field

6. Export to Excel

• Click "Export Excel"
• Generates formatted .xlsx file
• Bold headers
• Auto-sized columns
• Frozen header row

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⚙ CONFIGURATION OPTIONS

Option	Description
OCR Confidence Threshold	Default > 75 (adjust in code)
Minimum Word Length	Filters short noisy text
Bounding Box Filter	Removes irregular OCR shapes
Thread Handling	Adjustable worker threads
Database Engine	SQLite (Upgradeable to PostgreSQL)
Field Patterns	Regex-based, fully customizable
Excel Styling	OpenPyXL formatting logic

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📦 OUTPUT

Application Displays:

• File Name
• Extracted Name
• Extracted Date
• Extracted Document ID

Database Output:

• extracted_data.db (SQLite)

Excel Output:

• Formatted .xlsx report
• Clean structured rows
• Ready for analysis or reporting

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📦 DEPENDENCIES

• Python 3.10+
• Tkinter (Built-in)
• ttkbootstrap — Modern UI styling
• pdfplumber — Digital text extraction
• pytesseract — OCR engine interface
• pdf2image — PDF to image conversion
• Pillow — Image processing
• openpyxl — Excel export formatting
• sqlite3 — Embedded database
• concurrent.futures — Multi-threading
• threading / os / re / time — System operations

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🧠 AI HANDWRITING SUPPRESSION LOGIC

This application reduces handwritten noise using:

• OCR confidence filtering (>75 default)
• Minimum word length validation
• Bounding box size filtering
• Structured pattern validation
• Regex-based field validation

Only validated text is stored in the database.

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🌐 SaaS EXPANSION READY

This desktop version can be upgraded into:

• FastAPI backend service
• Cloud deployment (AWS / DigitalOcean / Render)
• PostgreSQL database
• Stripe subscription billing
• Web dashboard (React / Next.js)
• REST API document processing

Designed with modular architecture for scaling.

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📝 NOTES

• Fully offline desktop application
• Designed for consistently formatted structured PDFs
• OCR is only triggered when digital text is unavailable
• Handwritten annotations are filtered out
• Performance depends on CPU and PDF size
• Cross-platform compatible (Windows, macOS, Linux)

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👤 ABOUT

PDF Structured Data Extractor PRO is maintained by Mate Technologies, delivering intelligent document automation tools for structured PDF processing, business workflows, and scalable SaaS deployment.

Website / Contact:
https://matetools.gumroad.com

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📜 LICENSE

Distributed as source code.

You may use it for personal or educational projects.
Redistribution, resale, or commercial use requires explicit written permission from Mate Technologies.