PDF Processing Guide

Overview

This guide covers PDF transformations — merging, splitting, rotating, watermarking, encrypting, filling forms, extracting images, and OCRing scanned PDFs. Reading text/tables is handled by read_file directly; do NOT use this skill for plain reading. See REFERENCE.md for advanced library usage and FORMS.md for form filling.

Dependencies are pre-installed in the sandbox image — do NOT pip install or npm install anything. Just import or invoke directly.

• Python libraries (always present): pypdf, pdfplumber, pypdfium2, reportlab, pytesseract, pdf2image, Pillow, pandas, numpy.
• JavaScript libraries (always present): pdf-lib, pdfjs-dist.
• CLI tools (present on current sandbox images): pdftotext / pdftoppm / pdfimages (poppler-utils), qpdf, pdftk, pandoc, tesseract. Older sandbox images may be missing some of these — if a CLI tool returns not found, fall back to the equivalent Python library on this page rather than trying to install it.

Reading PDF text — use read_file

For any request to read, summarise, analyse, extract data from, or aggregate the contents of a PDF, call read_file directly:

read_file(path="path/to/document.pdf")

The harness parses PDFs natively via markitdown and returns markdown. Pagination via offset/limit is free (cached). Do NOT pip install pypdf/pdfplumber/pymupdf or write subprocess extraction scripts for reading — that bootstrap is exactly what read_file eliminates.

If read_file fails or times out on a specific PDF (large papers, encrypted, corrupt, or a scanned image-only PDF with no text layer), fall back in this order:

1. pypdf first. It's a pure-Python library that's always importable in the sandbox and doesn't depend on apt packages. Use it to read pages directly — see the snippet below.
2. pdftotext / pandoc (poppler-utils) when pypdf can't handle the specific PDF (e.g. tricky encoding). These are CLI tools and may be missing on older sandbox images; if which pdftotext errors, stay on pypdf.
3. ocr-and-documents skill for scanned image-only PDFs.

# Reliable fallback when read_file times out — chunk by page range
# so a single call doesn't run past the tool timeout on long papers.
from pypdf import PdfReader
reader = PdfReader("path/to/document.pdf")
print(f"Total pages: {len(reader.pages)}")
for i in range(0, len(reader.pages)):
    print(f"--- Page {i + 1} ---")
    print(reader.pages[i].extract_text())

The other Python libraries on this page are for transformations (the next sections), not for plain reading.

Python Libraries

pypdf - Basic Operations

Merge PDFs

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

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

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

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 - Layout-aware text + tables (fallback only)

For plain text/markdown, read_file(path) is the right call (see top of this skill). Use pdfplumber only when you need precise layout preservation or per-table structured extraction that read_file does not give you — e.g., multi-line cells, merged headers, or extracting a specific table on a specific page.

Extract Text with Layout

import pdfplumber

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

Extract Tables

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

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

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

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)

Subscripts and Superscripts

IMPORTANT: Never use Unicode subscript/superscript characters (₀₁₂₃₄₅₆₇₈₉, ⁰¹²³⁴⁵⁶⁷⁸⁹) in ReportLab PDFs. The built-in fonts do not include these glyphs, causing them to render as solid black boxes.

Instead, use ReportLab's XML markup tags in Paragraph objects:

from reportlab.platypus import Paragraph
from reportlab.lib.styles import getSampleStyleSheet

styles = getSampleStyleSheet()

# Subscripts: use <sub> tag
chemical = Paragraph("H<sub>2</sub>O", styles['Normal'])

# Superscripts: use <super> tag
squared = Paragraph("x<super>2</super> + y<super>2</super>", styles['Normal'])

For canvas-drawn text (not Paragraph objects), manually adjust font the size and position rather than using Unicode subscripts/superscripts.

Command-Line Tools

pdftotext (poppler-utils)

# 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

# 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)

# 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

# pytesseract + pdf2image are pre-installed; tesseract-ocr is in the
# sandbox image's apt layer.  Just import and run.
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

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

# 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

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
Read text / tables / aggregate data	read_file	read_file(path="document.pdf")
Merge PDFs	pypdf	writer.add_page(page)
Split PDFs	pypdf	One page per file
Layout-precise text / structured tables (fallback)	pdfplumber	page.extract_text() / page.extract_tables()
Create PDFs	reportlab	Canvas or Platypus
Command line merge	qpdf	qpdf --empty --pages ...
OCR scanned PDFs	ocr-and-documents skill or 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