pdfcoordex 0.1.1

Extract text, images, and tables from PDF files with analysis

pdfcoordex

Extract text, images, and tables from PDF files with automatic analysis.

Installation

pip install pdfcoordex

Features

• ✅ Extract all text content from PDFs
• ✅ Analyze embedded images (size, format, type)
• ✅ Extract tables with data preservation
• ✅ Save results to plain text file
• ✅ Simple and easy to use

Quick Start

from pdfcoordex import PDFCoordExtractor

# Create extractor
extractor = PDFCoordExtractor("document.pdf")

# Save to text file
extractor.save_to_text_file("output.txt")

# Close when done
extractor.close()

Usage Examples

Extract Single Page

from pdfcoordex import PDFCoordExtractor

extractor = PDFCoordExtractor("document.pdf")

# Get page 1 data
page_data = extractor.extract_page(1)

print("Text:", page_data['text'])
print("Images:", len(page_data['images']))
print("Tables:", len(page_data['tables']))

extractor.close()

Extract All Pages

from pdfcoordex import PDFCoordExtractor

extractor = PDFCoordExtractor("document.pdf")

# Get all pages
all_pages = extractor.extract_all_pages()

for page_name, data in all_pages.items():
    print(f"{page_name}: {len(data['text'])} characters")

extractor.close()

Using Context Manager

from pdfcoordex import PDFCoordExtractor

# Automatically closes the PDF
with PDFCoordExtractor("document.pdf") as extractor:
    extractor.save_to_text_file("output.txt")

Output Format

The text file output includes:

Text Content

All text from each page as plain text.

Image Analysis

• Image format (PNG, JPEG, etc.)
• Image dimensions (width x height)
• Orientation (landscape, portrait, square)
• Type classification (diagram, icon, chart)
• Color mode information

Tables

Tables are formatted with pipe separators for easy reading:

Header1 | Header2 | Header3
Data1   | Data2   | Data3

Requirements

• Python >= 3.8
• pdfplumber >= 0.10.3
• PyMuPDF >= 1.23.8
• Pillow >= 10.0.0

License

MIT License

Support

For issues and questions, please visit the GitHub repository.