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:

bash

pip install PyPDF2 pdfplumber

Quick start

Basic text extraction with PyPDF2

python

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:

python

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

python

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

python

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

python

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

python

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

•
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

•

Handle errors gracefully:

python

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

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