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pdf skill

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This skill helps you manipulate PDFs programmatically by extracting text and tables, merging, splitting, and creating documents at scale.

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SKILL.md
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---
name: pdf
description: Comprehensive PDF manipulation toolkit for extracting text and tables, creating new PDFs, merging/splitting documents, and handling forms. When Claude needs to fill in a PDF form or programmatically process, generate, or analyze PDF documents at scale.
license: Proprietary. LICENSE.txt has complete terms
---

# PDF Processing Guide

## Overview

This guide covers essential PDF processing operations using Python libraries and command-line tools. For advanced features, JavaScript libraries, and detailed examples, see reference.md. If you need to fill out a PDF form, read forms.md and follow its instructions.

## Quick Start

```python
from pypdf import PdfReader, PdfWriter

# Read a PDF
reader = PdfReader("document.pdf")
print(f"Pages: {len(reader.pages)}")

# Extract text
text = ""
for page in reader.pages:
    text += page.extract_text()
```

## Python Libraries

### pypdf - Basic Operations

#### Merge PDFs
```python
from pypdf import PdfWriter, PdfReader

writer = PdfWriter()
for pdf_file in ["doc1.pdf", "doc2.pdf", "doc3.pdf"]:
    reader = PdfReader(pdf_file)
    for page in reader.pages:
        writer.add_page(page)

with open("merged.pdf", "wb") as output:
    writer.write(output)
```

#### Split PDF
```python
reader = PdfReader("input.pdf")
for i, page in enumerate(reader.pages):
    writer = PdfWriter()
    writer.add_page(page)
    with open(f"page_{i+1}.pdf", "wb") as output:
        writer.write(output)
```

#### Extract Metadata
```python
reader = PdfReader("document.pdf")
meta = reader.metadata
print(f"Title: {meta.title}")
print(f"Author: {meta.author}")
print(f"Subject: {meta.subject}")
print(f"Creator: {meta.creator}")
```

#### Rotate Pages
```python
reader = PdfReader("input.pdf")
writer = PdfWriter()

page = reader.pages[0]
page.rotate(90)  # Rotate 90 degrees clockwise
writer.add_page(page)

with open("rotated.pdf", "wb") as output:
    writer.write(output)
```

### pdfplumber - Text and Table Extraction

#### Extract Text with Layout
```python
import pdfplumber

with pdfplumber.open("document.pdf") as pdf:
    for page in pdf.pages:
        text = page.extract_text()
        print(text)
```

#### Extract Tables
```python
with pdfplumber.open("document.pdf") as pdf:
    for i, page in enumerate(pdf.pages):
        tables = page.extract_tables()
        for j, table in enumerate(tables):
            print(f"Table {j+1} on page {i+1}:")
            for row in table:
                print(row)
```

#### Advanced Table Extraction
```python
import pandas as pd

with pdfplumber.open("document.pdf") as pdf:
    all_tables = []
    for page in pdf.pages:
        tables = page.extract_tables()
        for table in tables:
            if table:  # Check if table is not empty
                df = pd.DataFrame(table[1:], columns=table[0])
                all_tables.append(df)

# Combine all tables
if all_tables:
    combined_df = pd.concat(all_tables, ignore_index=True)
    combined_df.to_excel("extracted_tables.xlsx", index=False)
```

### reportlab - Create PDFs

#### Basic PDF Creation
```python
from reportlab.lib.pagesizes import letter
from reportlab.pdfgen import canvas

c = canvas.Canvas("hello.pdf", pagesize=letter)
width, height = letter

# Add text
c.drawString(100, height - 100, "Hello World!")
c.drawString(100, height - 120, "This is a PDF created with reportlab")

# Add a line
c.line(100, height - 140, 400, height - 140)

# Save
c.save()
```

#### Create PDF with Multiple Pages
```python
from reportlab.lib.pagesizes import letter
from reportlab.platypus import SimpleDocTemplate, Paragraph, Spacer, PageBreak
from reportlab.lib.styles import getSampleStyleSheet

doc = SimpleDocTemplate("report.pdf", pagesize=letter)
styles = getSampleStyleSheet()
story = []

# Add content
title = Paragraph("Report Title", styles['Title'])
story.append(title)
story.append(Spacer(1, 12))

body = Paragraph("This is the body of the report. " * 20, styles['Normal'])
story.append(body)
story.append(PageBreak())

# Page 2
story.append(Paragraph("Page 2", styles['Heading1']))
story.append(Paragraph("Content for page 2", styles['Normal']))

# Build PDF
doc.build(story)
```

## Command-Line Tools

### pdftotext (poppler-utils)
```bash
# Extract text
pdftotext input.pdf output.txt

# Extract text preserving layout
pdftotext -layout input.pdf output.txt

# Extract specific pages
pdftotext -f 1 -l 5 input.pdf output.txt  # Pages 1-5
```

### qpdf
```bash
# Merge PDFs
qpdf --empty --pages file1.pdf file2.pdf -- merged.pdf

# Split pages
qpdf input.pdf --pages . 1-5 -- pages1-5.pdf
qpdf input.pdf --pages . 6-10 -- pages6-10.pdf

# Rotate pages
qpdf input.pdf output.pdf --rotate=+90:1  # Rotate page 1 by 90 degrees

# Remove password
qpdf --password=mypassword --decrypt encrypted.pdf decrypted.pdf
```

### pdftk (if available)
```bash
# Merge
pdftk file1.pdf file2.pdf cat output merged.pdf

# Split
pdftk input.pdf burst

# Rotate
pdftk input.pdf rotate 1east output rotated.pdf
```

## Common Tasks

### Extract Text from Scanned PDFs
```python
# Requires: pip install pytesseract pdf2image
import pytesseract
from pdf2image import convert_from_path

# Convert PDF to images
images = convert_from_path('scanned.pdf')

# OCR each page
text = ""
for i, image in enumerate(images):
    text += f"Page {i+1}:\n"
    text += pytesseract.image_to_string(image)
    text += "\n\n"

print(text)
```

### Add Watermark
```python
from pypdf import PdfReader, PdfWriter

# Create watermark (or load existing)
watermark = PdfReader("watermark.pdf").pages[0]

# Apply to all pages
reader = PdfReader("document.pdf")
writer = PdfWriter()

for page in reader.pages:
    page.merge_page(watermark)
    writer.add_page(page)

with open("watermarked.pdf", "wb") as output:
    writer.write(output)
```

### Extract Images
```bash
# Using pdfimages (poppler-utils)
pdfimages -j input.pdf output_prefix

# This extracts all images as output_prefix-000.jpg, output_prefix-001.jpg, etc.
```

### Password Protection
```python
from pypdf import PdfReader, PdfWriter

reader = PdfReader("input.pdf")
writer = PdfWriter()

for page in reader.pages:
    writer.add_page(page)

# Add password
writer.encrypt("userpassword", "ownerpassword")

with open("encrypted.pdf", "wb") as output:
    writer.write(output)
```

## Quick Reference

| Task | Best Tool | Command/Code |
|------|-----------|--------------|
| Merge PDFs | pypdf | `writer.add_page(page)` |
| Split PDFs | pypdf | One page per file |
| Extract text | pdfplumber | `page.extract_text()` |
| Extract tables | pdfplumber | `page.extract_tables()` |
| Create PDFs | reportlab | Canvas or Platypus |
| Command line merge | qpdf | `qpdf --empty --pages ...` |
| OCR scanned PDFs | pytesseract | Convert to image first |
| Fill PDF forms | pdf-lib or pypdf (see forms.md) | See forms.md |

## Next Steps

- For advanced pypdfium2 usage, see reference.md
- For JavaScript libraries (pdf-lib), see reference.md
- If you need to fill out a PDF form, follow the instructions in forms.md
- For troubleshooting guides, see reference.md

Overview

This skill is a comprehensive PDF manipulation toolkit for extracting text and tables, creating new PDFs, merging and splitting documents, and handling forms programmatically. It focuses on reliable Python libraries and command-line utilities to process PDFs at scale. Use it when you need repeatable, scriptable PDF workflows like extraction, generation, watermarking, OCR, or encryption.

How this skill works

The skill combines pypdf for reading/writing, pdfplumber for accurate text and table extraction, and reportlab for PDF generation. It integrates command-line tools (pdftotext, qpdf, pdfimages) and OCR (pytesseract + pdf2image) for scanned documents. Typical flows: read pages, extract text/tables, transform or assemble pages, then write new PDFs or apply metadata, watermarks, and passwords.

When to use it

  • Extract structured tables from reports or invoices for downstream analysis.
  • Merge multiple documents into a single PDF or split large PDFs into page-level files.
  • Create programmatic reports, invoices, or multi-page documents from templates.
  • Automate OCR for scanned PDFs to make content searchable.
  • Apply watermarks, rotate pages, or add password protection for distribution.

Best practices

  • Prefer pdfplumber for layout-preserving text and table extraction; validate extracted tables before ingestion.
  • Stream pages through PdfReader/PdfWriter to avoid loading entire files into memory for large PDFs.
  • Use pdftotext or pdfimages for fast command-line extraction when integration speed matters.
  • Perform OCR only on pages that lack extractable text to reduce processing time and costs.
  • Store intermediate outputs (extracted tables, images) in structured formats like CSV/Parquet for easier downstream use.

Example use cases

  • Batch-extract tables from monthly financial reports and combine them into a single Excel workbook.
  • Automatically fill and flatten PDF forms for contract processing and archival.
  • Create templated PDF reports using reportlab and merge them with scanned appendices.
  • Rotate and watermark a set of deliverables before client distribution, then encrypt for secure delivery.
  • Run OCR on scanned archival documents and index the resulting text for search.

FAQ

Which library should I use for table extraction?

Use pdfplumber for most table extraction tasks; convert complex scans to images and run OCR first when tables are embedded in scanned pages.

How do I avoid memory issues with large PDFs?

Stream pages with PdfReader/PdfWriter and write output incrementally. Avoid reading entire files into memory and process pages in batches.