PDF Processing Skill

Quick Start

Use pdfplumber to extract text from PDFs:

import pdfplumber

with pdfplumber.open("document.pdf") as pdf:
    text = pdf.pages[0].extract_text()
    print(text)

Capabilities

1. Text Extraction

Extract all text from a PDF document:

def extract_all_text(pdf_path):
    with pdfplumber.open(pdf_path) as pdf:
        full_text = ""
        for page in pdf.pages:
            full_text += page.extract_text() or ""
        return full_text

2. Table Extraction

Extract tables from PDF pages. For detailed table extraction, see [[TABLES.md]].

Basic example:

with pdfplumber.open("document.pdf") as pdf:
    tables = pdf.pages[0].extract_tables()
    for table in tables:
        print(table)

3. Form Filling

Fill PDF forms programmatically. For comprehensive form-filling guide, see [[FORMS.md]].

Best Practices

• Performance: For large PDFs, process page-by-page to avoid memory issues
• OCR: For scanned PDFs without text layer, recommend using OCR tools first
• Encoding: Handle UTF-8 encoding properly when extracting text

Common Use Cases

• Invoice text extraction
• Table data scraping from reports
• PDF form automation
• Document merging and splitting