The PDF skill provides tools for processing PDF documents, including merging, splitting, extracting text and metadata, and rotating pages. It leverages Pytho...
Install
npx promptshop add pdfDetails
What This Skill Does
The PDF skill provides tools for processing PDF documents, including merging, splitting, extracting text and metadata, and rotating pages. It leverages Python libraries like pypdf and pdfplumber for basic and advanced operations. This skill is useful for automating PDF-related tasks and extracting information from PDF files.
When to Use
- Merge multiple PDF files into one.
- Split a PDF into individual pages.
- Extract metadata from a PDF document.
- Rotate pages within a PDF file.
- Extract text content with layout using pdfplumber.
- Extract tables from a PDF document.
Key Features
- Uses pypdf for basic PDF operations.
- Supports merging and splitting PDF files.
- Extracts metadata like title, author, and subject.
- Rotates pages clockwise by a specified angle.
- Uses pdfplumber for text and table extraction.
- Provides code examples for common tasks.
Manual Installation
Manual installation
- View Full Skill Content.
- The complete markdown content that gets installed.
- 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
- from pypdf import Pdf.
- Reader, Pdf.
- Writer.
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
- from pypdf import Pdf.
- Writer, Pdf.
- Reader.
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 - Text and Table Extraction
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 = get.
- Sample.
- Style.
- Sheet().
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)
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
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
- from pypdf import Pdf.
- Reader, Pdf.
- Writer.
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 Pdf.
- Reader, Pdf.
- Writer.
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.mdPDF Processing Guide