PDF Reader

This skill helps you extract and read text content from PDF files using Python libraries.

When to use this skill

Use this skill when:

• Reading text content from PDF files
• Extracting specific pages from PDFs
• Analyzing PDF document structure
• Converting PDF text to plain text
• The user mentions “PDF”, “read PDF”, “extract text from PDF”

Requirements

Install required packages:

pip install PyPDF2 pdfplumber

Quick start

Basic text extraction with PyPDF2

import PyPDF2

def read_pdf_pypdf2(pdf_path):
    """Extract all text from a PDF file using PyPDF2"""
    with open(pdf_path, 'rb') as file:
        pdf_reader = PyPDF2.PdfReader(file)
        
        # Get number of pages
        num_pages = len(pdf_reader.pages)
        print(f"PDF has {num_pages} pages")
        
        # Extract text from all pages
        full_text = ""
        for page_num in range(num_pages):
            page = pdf_reader.pages[page_num]
            text = page.extract_text()
            full_text += f"\n--- Page {page_num + 1} ---\n{text}"
        
        return full_text

# Usage
text = read_pdf_pypdf2("document.pdf")
print(text)

Advanced extraction with pdfplumber

pdfplumber provides better text extraction and table detection:

import pdfplumber

def read_pdf_pdfplumber(pdf_path):
    """Extract text with better formatting using pdfplumber"""
    with pdfplumber.open(pdf_path) as pdf:
        full_text = ""
        
        for i, page in enumerate(pdf.pages):
            # Extract text
            text = page.extract_text()
            full_text += f"\n--- Page {i + 1} ---\n{text}\n"
            
            # Optionally extract tables
            tables = page.extract_tables()
            if tables:
                full_text += f"\n[Found {len(tables)} table(s) on page {i + 1}]\n"
        
        return full_text

# Usage
text = read_pdf_pdfplumber("document.pdf")
print(text)

Extract specific pages

def read_pdf_pages(pdf_path, page_numbers):
    """Extract text from specific pages only"""
    with pdfplumber.open(pdf_path) as pdf:
        text = ""
        for page_num in page_numbers:
            if 0 <= page_num < len(pdf.pages):
                page = pdf.pages[page_num]
                text += f"\n--- Page {page_num + 1} ---\n"
                text += page.extract_text()
            else:
                print(f"Warning: Page {page_num + 1} doesn't exist")
        return text

# Usage: Read pages 1, 3, and 5 (0-indexed: 0, 2, 4)
text = read_pdf_pages("document.pdf", [0, 2, 4])
print(text)

Get PDF metadata

def get_pdf_info(pdf_path):
    """Get metadata and information about the PDF"""
    with pdfplumber.open(pdf_path) as pdf:
        info = {
            'num_pages': len(pdf.pages),
            'metadata': pdf.metadata,
        }
        
        # Get dimensions of first page
        if pdf.pages:
            first_page = pdf.pages[0]
            info['page_width'] = first_page.width
            info['page_height'] = first_page.height
    
    return info

# Usage
info = get_pdf_info("document.pdf")
print(f"Pages: {info['num_pages']}")
print(f"Title: {info['metadata'].get('Title', 'N/A')}")
print(f"Author: {info['metadata'].get('Author', 'N/A')}")

Common use cases

Search for text in PDF

def search_in_pdf(pdf_path, search_term):
    """Search for a term and return pages where it appears"""
    results = []
    
    with pdfplumber.open(pdf_path) as pdf:
        for i, page in enumerate(pdf.pages):
            text = page.extract_text()
            if search_term.lower() in text.lower():
                results.append({
                    'page': i + 1,
                    'text_snippet': text[:200]  # First 200 chars as preview
                })
    
    return results

# Usage
results = search_in_pdf("document.pdf", "important keyword")
for result in results:
    print(f"Found on page {result['page']}")

Extract tables from PDF

def extract_tables(pdf_path):
    """Extract all tables from PDF"""
    all_tables = []
    
    with pdfplumber.open(pdf_path) as pdf:
        for i, page in enumerate(pdf.pages):
            tables = page.extract_tables()
            for j, table in enumerate(tables):
                all_tables.append({
                    'page': i + 1,
                    'table_number': j + 1,
                    'data': table
                })
    
    return all_tables

# Usage
tables = extract_tables("document.pdf")
for table_info in tables:
    print(f"Table {table_info['table_number']} from page {table_info['page']}")
    print(table_info['data'])

Tips and best practices

1. Choose the right library:

   • Use PyPDF2 for simple text extraction and PDF manipulation
   • Use pdfplumber for better text extraction and table detection
   • Use both if needed for different tasks

2. Handle errors gracefully:

   try:
       text = read_pdf_pdfplumber("document.pdf")
   except FileNotFoundError:
       print("PDF file not found")
   except Exception as e:
       print(f"Error reading PDF: {e}")
   

3. Memory management: For large PDFs, process pages one at a time instead of loading all text at once

4. Text quality: Some PDFs (especially scanned images) may not have extractable text. Consider OCR tools like pytesseract for those cases.

Troubleshooting

• No text extracted: The PDF might be image-based. Use OCR tools.
• Garbled text: Try pdfplumber instead of PyPDF2, it often handles formatting better.
• Missing packages: Run pip install PyPDF2 pdfplumber

Related skills

• For PDF form filling: Consider creating a pdf-forms skill
• For PDF merging/splitting: Consider creating a pdf-manipulation skill
• For OCR on image PDFs: Consider using pytesseract with pdf2image