PDF Processing Skill Guide

Description

The PDF skill provides a rich set of tools and examples to handle any PDF-related processing. Whether you need to extract text, merge files, create watermarks, or add password protection, the skill integrates Python libraries and command-line utilities to ensure robust functionality.

When to Use the Skill

• •Extracting tables or text from a PDF for data analysis.
• •Merging or splitting PDF documents for organization.
• •Adding encryption, watermarks, or metadata to enhance security and professionalism.
• •Handling scanned PDFs via OCR to make them searchable or extract readable content.
• •Creating brand-new PDF documents with dynamic content.

Usage Guide

Code Examples

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)

Extract Text from Scanned PDFs

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)

Command-Line Usage

Extract Text with pdftotext

pdftotext input.pdf output.txt

Merge PDFs with qpdf

qpdf --empty --pages file1.pdf file2.pdf -- merged.pdf

Inputs and Outputs

Inputs

• •File path: Path to the input PDF file(s) (e.g., input.pdf).
• •Operation: The specific processing task (e.g., merge, split, extract).
• •Additional arguments: Optional arguments such as passwords, metadata, or specific pages.

Outputs

• •Result file: Path to the output PDF file (e.g., output.pdf).
• •Extracted data: Text, tables, or other extracted formats depending on the task.

Best Practices and Known Limitations

• •Always ensure that Python libraries (pypdf, pdfplumber) and external tools (pdftotext, qpdf) are correctly installed in your environment.
• •OCR processes (e.g., pytesseract) rely on high-resolution scanned documents for optimal accuracy.
• •Avoid using Unicode subscripts/superscripts with ReportLab due to font limitations.

Example Workflows

Creating PDFs from Scratch

from reportlab.lib.pagesizes import letter
from reportlab.pdfgen import canvas

c = canvas.Canvas("hello_world.pdf", pagesize=letter)
c.drawString(100, 750, "Hello, World!")
c.save()

Adding Watermarks to Pages

from pypdf import PdfReader, PdfWriter

watermark = PdfReader("watermark.pdf").pages[0]
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)

Version History and Changelog