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PDF to Text Converter

Convert PDF documents to plain text with advanced extraction options, page range selection, and metadata preservation.

Quick Start

# Basic conversion
pyforge convert document.pdf

# With page range
pyforge convert document.pdf --pages "1-10"

# With metadata
pyforge convert document.pdf --metadata

# Custom output file
pyforge convert document.pdf extracted_text.txt

Overview

The PDF to Text converter uses PyMuPDF (fitz) to extract text from PDF documents with high accuracy and performance. It supports:

  • Text Extraction: High-quality text extraction preserving formatting
  • Page Selection: Convert specific pages or page ranges
  • Metadata Extraction: Include document metadata in output
  • Layout Preservation: Maintain basic text layout and structure
  • Error Recovery: Handle corrupted or complex PDF files

Command Syntax

pyforge convert <pdf_file> [output_file] [options]

Basic Examples

# Convert entire PDF
pyforge convert report.pdf

# Specify output file
pyforge convert report.pdf extracted_report.txt

# Convert with progress tracking
pyforge convert large_document.pdf --verbose

Page Selection

Control which pages to convert using the --pages option:

Page Range Syntax

Syntax Description Example
"1-10" Pages 1 through 10 --pages "1-10"
"5-" Page 5 to end of document --pages "5-"
"-10" First 10 pages --pages "-10"
"1,3,5" Specific pages only --pages "1,3,5"
"1-5,10-15" Multiple ranges --pages "1-5,10-15"

Page Selection Examples

# First 5 pages
pyforge convert manual.pdf --pages "-5"

# Pages 10 to 20
pyforge convert manual.pdf --pages "10-20"

# From page 25 to end
pyforge convert manual.pdf --pages "25-"

# Specific pages
pyforge convert manual.pdf --pages "1,5,10,25"

# Multiple ranges
pyforge convert manual.pdf --pages "1-3,10-12,20-25"

# Complex selection
pyforge convert manual.pdf summary.txt --pages "1,3-7,15,20-"

Metadata Options

Include document metadata in the output using --metadata:

# Include metadata
pyforge convert document.pdf --metadata

# Combine with page selection
pyforge convert document.pdf --pages "1-10" --metadata

Metadata Information

When --metadata is enabled, the output includes:

  • Document title
  • Author information
  • Creation and modification dates
  • Page count
  • File size
  • PDF version
  • Security settings

Example Output with Metadata: 

========================================
PDF METADATA
========================================
Title: Annual Report 2023
Author: Finance Department
Creator: Microsoft Word
Producer: Adobe PDF Library
Creation Date: 2023-12-01 14:30:25
Modification Date: 2023-12-15 09:45:12
Pages: 45
File Size: 2.4 MB
PDF Version: 1.7
Security: Not Encrypted
========================================

[Document text content follows...]

Advanced Options

Output Control

# Force overwrite existing files
pyforge convert document.pdf --force

# Specify custom output location
pyforge convert document.pdf /path/to/output.txt

# Verbose output for debugging
pyforge convert document.pdf --verbose

Error Handling

# Attempt to process corrupted PDFs
pyforge convert damaged.pdf --force

# Skip problematic pages
pyforge convert complex.pdf --skip-errors

Text Extraction Quality

What Works Well

  • Standard Text: Regular paragraphs and headings
  • Tables: Simple table structures (converted to aligned text)
  • Lists: Bulleted and numbered lists
  • Headers/Footers: Page headers and footers
  • Multi-column: Basic multi-column layouts

Limitations

  • Complex Layouts: Heavily formatted documents may lose structure
  • Images: Text within images is not extracted (OCR not included)
  • Forms: Interactive form fields may not be captured
  • Annotations: Comments and annotations are not included
  • Embedded Objects: Charts, diagrams converted to placeholder text

Quality Tips

Best Results

For the best text extraction:

  • Use PDFs created from text documents (not scanned images)
  • Prefer PDFs with selectable text
  • Avoid heavily graphical or artistic layouts
  • Consider the source application (Word docs convert better than InDesign layouts)

File Information

Get detailed information about a PDF before conversion:

# Basic file info
pyforge info document.pdf

# Detailed information
pyforge info document.pdf --verbose

Example Output: 

📄 File: annual_report.pdf
📊 Type: PDF Document
📏 Size: 2.4 MB
📋 Pages: 45
🔒 Encrypted: No
📝 Text Extractable: Yes
🎨 Has Images: Yes
📑 Has Forms: No

┌─────────────┬─────────────────────────┐
│ Property    │ Value                   │
├─────────────┼─────────────────────────┤
│ Title       │ Annual Report 2023      │
│ Author      │ Finance Department      │
│ Creator     │ Microsoft Word          │
│ Producer    │ Adobe PDF Library       │
│ Created     │ 2023-12-01 14:30:25    │
│ Modified    │ 2023-12-15 09:45:12    │
│ PDF Version │ 1.7                     │
└─────────────┴─────────────────────────┘

Validation

Validate PDF files before conversion:

# Check if file can be processed
pyforge validate document.pdf

# Detailed validation
pyforge validate document.pdf --verbose

Performance

Processing Speed

Document Type Pages Typical Speed
Text-heavy 1-50 10-50 pages/sec
Mixed content 1-50 5-20 pages/sec
Image-heavy 1-50 2-10 pages/sec
Large files 100+ 5-15 pages/sec

Memory Usage

  • Small PDFs (< 10 MB): 50-100 MB RAM
  • Medium PDFs (10-100 MB): 100-500 MB RAM
  • Large PDFs (> 100 MB): 500 MB - 2 GB RAM

Optimization Tips

Large File Processing

For large PDF files:

# Process in smaller chunks
pyforge convert large.pdf --pages "1-50"
pyforge convert large.pdf --pages "51-100"

# Use verbose mode to monitor progress
pyforge convert large.pdf --verbose

# Ensure sufficient disk space (3x file size recommended)

Common Use Cases

# Extract contract text
pyforge convert contract.pdf --pages "1-10" --metadata

# Process multiple legal documents
for file in contracts/*.pdf; do
    pyforge convert "$file" "processed/$(basename "$file" .pdf).txt"
done

Research Paper Processing

# Extract paper content (skip references)
pyforge convert research_paper.pdf --pages "1-25" 

# Include metadata for citation
pyforge convert research_paper.pdf --metadata

Report Processing

# Extract executive summary
pyforge convert annual_report.pdf summary.txt --pages "3-8"

# Full report with metadata
pyforge convert annual_report.pdf --metadata --verbose

Troubleshooting

Common Issues

Issue Symptoms Solution
Encrypted PDF "Password required" error Decrypt PDF first or provide password option
Corrupted File "Invalid PDF" error Try --force option
No Text Output Empty or minimal text PDF may be image-based (needs OCR)
Garbled Text Strange characters Check PDF encoding/font issues
Memory Error Process crashes Reduce page range or close other applications

Troubleshooting Commands

# Check file validity
pyforge validate problematic.pdf

# Try force processing
pyforge convert problematic.pdf --force

# Get detailed file information
pyforge info problematic.pdf --verbose

# Process small page range first
pyforge convert problematic.pdf test.txt --pages "1-5"

Output Format

Text Structure

The extracted text maintains:

  • Paragraph breaks: Preserved from original
  • Line breaks: Maintained where appropriate
  • Spacing: Basic spacing preserved
  • Headers/Footers: Included in extraction
  • Page breaks: Marked with page numbers (if --metadata used)

Example Output Structure

Page 1
======

ANNUAL REPORT 2023
Finance Department

Executive Summary

This report provides a comprehensive overview of our 
financial performance for the fiscal year 2023...

Key Highlights:
• Revenue increased by 15%
• Profit margins improved
• Successful market expansion

Page 2
======

Financial Overview

The following table shows our quarterly performance:

Q1    $2.5M    15%
Q2    $2.8M    18%
Q3    $3.1M    20%
Q4    $3.4M    22%

...

Integration Examples

Bash Scripting

#!/bin/bash
# Process all PDFs in a directory

for pdf in *.pdf; do
    echo "Processing $pdf..."
    pyforge convert "$pdf" "${pdf%.pdf}.txt" --metadata
    echo "✓ Completed $pdf"
done

Python Integration

import subprocess
import os

def extract_pdf_text(pdf_path, output_path=None, pages=None):
    """Extract text from PDF using PyForge CLI"""
    cmd = ["pyforge", "convert", pdf_path]

    if output_path:
        cmd.append(output_path)

    if pages:
        cmd.extend(["--pages", pages])

    cmd.append("--metadata")

    result = subprocess.run(cmd, capture_output=True, text=True)
    return result.returncode == 0

# Usage
success = extract_pdf_text("report.pdf", "extracted.txt", "1-10")

Next Steps