PDF Processing

PDF Processing

Overview

Generate, manipulate, and extract data from PDF documents. This skill covers the Python PDF ecosystem: pypdf for merging/splitting/metadata, pdfplumber for text and table extraction, reportlab for generation, pytesseract for OCR, and strategies for form filling, watermarking, and complex document assembly.

Apply this skill whenever PDFs need to be created, parsed, transformed, or combined through code.

Multi-Phase Process

Phase 1: Requirements

1. Determine operation type (generate, extract, manipulate)
2. Identify input PDF characteristics (scanned, digital, forms)
3. Define output requirements (format, quality, size)
4. Plan data pipeline (source data to PDF or PDF to data)
5. Assess volume and performance requirements

STOP — Do NOT select a library until the operation type and input characteristics are clear.

Phase 2: Implementation

1. Select appropriate library for the task (see decision table)
2. Implement core processing logic
3. Handle edge cases (corrupted files, encrypted PDFs, mixed content)
4. Add error handling and validation
5. Optimize for file size and processing speed

STOP — Do NOT skip edge case handling for encrypted, rotated, or scanned PDFs.

Phase 3: Validation

1. Verify output renders correctly in multiple PDF viewers
2. Check text is selectable (not rasterized) when applicable
3. Validate extracted data accuracy
4. Test with edge case PDFs (large, encrypted, scanned)
5. Verify accessibility (tagged PDF where needed)

Library Selection Decision Table

PDF Generation with ReportLab

from reportlab.lib.pagesizes import A4
from reportlab.lib.styles import getSampleStyleSheet, ParagraphStyle
from reportlab.lib.units import cm, mm
from reportlab.lib.colors import HexColor
from reportlab.platypus import (
    SimpleDocTemplate, Paragraph, Spacer, Table,
    TableStyle, Image, PageBreak
)
from reportlab.lib import colors

def generate_report(output_path, data):
    doc = SimpleDocTemplate(
        output_path,
        pagesize=A4,
        topMargin=2.5*cm,
        bottomMargin=2.5*cm,
        leftMargin=2.5*cm,
        rightMargin=2.5*cm,
    )

    styles = getSampleStyleSheet()
    styles.add(ParagraphStyle(
        name='CustomTitle',
        parent=styles['Title'],
        fontSize=24,
        textColor=HexColor('#2F5496'),
        spaceAfter=20,
    ))

    story = []

    # Title
    story.append(Paragraph(data['title'], styles['CustomTitle']))
    story.append(Spacer(1, 12))

    # Body text
    story.append(Paragraph(data['body'], styles['Normal']))
    story.append(Spacer(1, 20))

    # Table
    table_data = [['Name', 'Value', 'Status']]
    for row in data['rows']:
        table_data.append([row['name'], row['value'], row['status']])

    table = Table(table_data, colWidths=[6*cm, 4*cm, 4*cm])
    table.setStyle(TableStyle([
        ('BACKGROUND', (0, 0), (-1, 0), HexColor('#2F5496')),
        ('TEXTCOLOR', (0, 0), (-1, 0), colors.white),
        ('FONTNAME', (0, 0), (-1, 0), 'Helvetica-Bold'),
        ('FONTSIZE', (0, 0), (-1, 0), 11),
        ('ALIGN', (0, 0), (-1, -1), 'CENTER'),
        ('GRID', (0, 0), (-1, -1), 0.5, colors.grey),
        ('ROWBACKGROUNDS', (0, 1), (-1, -1), [colors.white, HexColor('#F0F4FA')]),
        ('TOPPADDING', (0, 0), (-1, -1), 8),
        ('BOTTOMPADDING', (0, 0), (-1, -1), 8),
    ]))
    story.append(table)

    doc.build(story)

Custom Page Template (Headers/Footers)

from reportlab.platypus import BaseDocTemplate, Frame, PageTemplate
from datetime import datetime

def add_header_footer(canvas, doc):
    canvas.saveState()
    # Header
    canvas.setFont('Helvetica', 9)
    canvas.setFillColor(HexColor('#888888'))
    canvas.drawString(2.5*cm, A4[1] - 1.5*cm, 'Company Name — Confidential')
    canvas.drawRightString(A4[0] - 2.5*cm, A4[1] - 1.5*cm, f'Page {doc.page}')
    # Footer
    canvas.drawCentredString(A4[0]/2, 1.5*cm, f'Generated on {datetime.now():%Y-%m-%d}')
    canvas.restoreState()

doc = BaseDocTemplate(output_path, pagesize=A4)
frame = Frame(2.5*cm, 2.5*cm, A4[0]-5*cm, A4[1]-5*cm)
doc.addPageTemplates([PageTemplate(id='main', frames=[frame],

Text and Table Extraction

pdfplumber

import pdfplumber

with pdfplumber.open('document.pdf') as pdf:
    # Extract text from all pages
    full_text = ''
    for page in pdf.pages:
        full_text += page.extract_text() + '\n'

    # Extract tables
    for page in pdf.pages:
        tables = page.extract_tables()
        for table in tables:
            for row in table:
                print(row)

    # Extract text from specific area
    page = pdf.pages[0]
    bbox = (50, 100, 400, 300)  # (x0, top, x1, bottom)
    cropped = page.within_bbox(bbox)
    text = cropped.extract_text()

Table Extraction Settings

table_settings = {
    "vertical_strategy": "lines",    # or "text", "explicit"
    "horizontal_strategy": "lines",
    "snap_tolerance": 3,
    "join_tolerance": 3,
    "edge_min_length": 3,
    "min_words_vertical": 3,
    "min_words_horizontal": 1,
}

tables = page.extract_tables(table_settings)

Form Filling

from pypdf import PdfReader, PdfWriter

reader = PdfReader('form.pdf')
writer = PdfWriter()
writer.append(reader)

# Fill form fields
writer.update_page_form_field_values(
    writer.pages[0],
    {
        'full_name': 'Alice Johnson',
        'email': 'alice@example.com',
        'date': '2025-03-15',
        'agree_terms': '/Yes',  # Checkbox
    },
    auto_regenerate=False,
)

with open('filled_form.pdf', 'wb') as f:
    writer.write(f)

OCR (Scanned PDFs)

from pdf2image import convert_from_path
import pytesseract

def ocr_pdf(pdf_path, language='eng'):
    images = convert_from_path(pdf_path, dpi=300)
    full_text = ''
    for i, image in enumerate(images):
        text = pytesseract.image_to_string(image, lang=language)
        full_text += f'\n--- Page {i+1} ---\n{text}'
    return full_text

# For better accuracy with specific layouts:
def ocr_with_config(image):
    custom_config = r'--oem 3 --psm 6'  # LSTM engine, assume uniform block
    return pytesseract.image_to_string(image, config=custom_config)

Merge and Split

from pypdf import PdfReader, PdfWriter

# Merge multiple PDFs
def merge_pdfs(input_paths, output_path):
    writer = PdfWriter()
    for path in input_paths:
        reader = PdfReader(path)
        for page in reader.pages:
            writer.add_page(page)
    with open(output_path, 'wb') as f:
        writer.write(f)

# Split PDF by page ranges
def split_pdf(input_path, ranges, output_dir):
    reader = PdfReader(input_path)
    for i, (start, end) in enumerate(ranges):
        writer = PdfWriter()
        for page_num in range(start - 1, min(end, len(reader.pages))):
            writer.add_page(reader.pages[page_num])
        with open(f'{output_dir}/part_{i+1}.pdf', 'wb') as f:
            writer.write(f)

# Extract specific pages
def extract_pages(input_path, page_numbers, output_path):
    reader = PdfReader(input_path)
    writer = PdfWriter()
    for num in page_numbers:
        writer.add_page(reader.pages[num - 1])
    with open(output_path, 'wb') as f:
        writer.write(f)

Watermarking

from pypdf import PdfReader, PdfWriter
from reportlab.pdfgen import canvas as rl_canvas
from reportlab.lib.pagesizes import A4
from io import BytesIO

def create_watermark(text, opacity=0.1):
    buffer = BytesIO()
    c = rl_canvas.Canvas(buffer, pagesize=A4)
    c.setFillAlpha(opacity)
    c.setFont('Helvetica-Bold', 60)
    c.setFillColorRGB(0.5, 0.5, 0.5)
    c.translate(A4[0]/2, A4[1]/2)
    c.rotate(45)
    c.drawCentredString(0, 0, text)
    c.save()
    buffer.seek(0)
    return PdfReader(buffer)

def apply_watermark(input_path, output_path, watermark_text):
    watermark = create_watermark(watermark_text)
    reader = PdfReader(input_path)
    writer = PdfWriter()

    for page in reader.pages:
        page.merge_page(watermark.pages[0])
        writer.add_page(page)

    with open(output_path, 'wb') as f:
        writer.write(f)

Metadata Handling

from pypdf import PdfReader, PdfWriter

# Read metadata
reader = PdfReader('document.pdf')
info = reader.metadata
print(f'Title: {info.title}')
print(f'Author: {info.author}')
print(f'Pages: {len(reader.pages)}')

# Write metadata
writer = PdfWriter()
writer.append(reader)
writer.add_metadata({
    '/Title': 'Updated Title',
    '/Author': 'Author Name',
    '/Subject': 'Document Subject',
    '/Creator': 'My Application',
})
with open('updated.pdf', 'wb') as f:
    writer.write(f)

Anti-Patterns / Common Mistakes

Anti-Rationalization Guards

• Do NOT use OCR without first attempting direct text extraction -- check the PDF type.
• Do NOT skip encryption detection -- handle it explicitly even if "most PDFs aren't encrypted."
• Do NOT assume A4 page size -- read dimensions from the source document.
• Do NOT test in only one PDF viewer -- rendering varies across Adobe, Preview, and Chrome.
• Do NOT process large PDFs without memory-conscious patterns (streaming, chunking).

Integration Points

Skill Type

FLEXIBLE — Select the appropriate library and approach based on the specific PDF task. ReportLab for generation, pdfplumber for extraction, pypdf for manipulation. Combine as needed.