PDF Extractor

A Streamlit web application that extracts and displays metadata and text content from PDF files.

Features

• Upload Multiple PDFs: Upload one or more PDF files through a simple interface
• Extract Metadata: Automatically extract all available metadata from each PDF
• View PDF Content: View the full text content of each PDF
• Tab Navigation: Easily navigate between multiple PDFs using tabs
• Export to CSV: Export all metadata to a CSV file for further analysis
• Clean UI: Streamlined user interface with custom styling

Installation

Prerequisites

• Python 3.7 or higher
• pip (Python package installer)

Setup

1. Clone this repository:

   git clone https://github.com/username/pdf-extractor.git
   cd pdf-extractor
   

2. Install the required dependencies:

   pip install -r requirements.txt
   

Usage

Running the Application

Run the application with the following command:

streamlit run pdf_extractor.py

For deployment with a custom base URL path:

streamlit run pdf_extractor.py --server.baseUrlPath="/pdf"

Using the Application

1. Upload PDF Files:

   • Click the "Choose PDF files" button in the sidebar
   • Select one or more PDF files from your computer

2. View Metadata:

   • The application will automatically extract and display metadata for each PDF
   • Navigate between PDFs using the tabs at the top

3. View PDF Content:

   • Click the "PDF DATA" expander to view the full text content of the PDF

4. Export Metadata:

   • Use the "Export Metadata" button in the sidebar to download a CSV file
   • Optionally include the full PDF text content in the export

Docker Support

A Dockerfile is included for containerized deployment:

docker build -t pdf-extractor .
docker run -p 8501:8501 pdf-extractor

To run the application with a custom base URL path in Docker:

docker run -p 8501:8501 -e BASE_URL_PATH="/pdf" pdf-extractor

The BASE_URL_PATH environment variable is optional. If not specified, the application will run at the root path.

Technical Details

Dependencies

• streamlit: Web application framework
• pdfminer.six: PDF parsing and text extraction
• pandas: Data manipulation and CSV export

Code Structure

• pdf_extractor.py: Main application file containing:
  • PDF metadata extraction functions
  • Text content extraction
  • Streamlit UI components
  • CSV export functionality

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

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