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PDF Processing Pro
Production-ready PDF processing toolkit with pre-built scripts, comprehensive error handling, and support for complex workflows.
Quick start
Extract text from PDF
import pdfplumber
with pdfplumber.open("document.pdf") as pdf:
text = pdf.pages[0].extract_text()
print(text)
Analyze PDF form (using included script)
python scripts/analyze_form.py input.pdf --output fields.json
# Returns: JSON with all form fields, types, and positions
Fill PDF form with validation
python scripts/fill_form.py input.pdf data.json output.pdf
# Validates all fields before filling, includes error reporting
Extract tables from PDF
python scripts/extract_tables.py report.pdf --output tables.csv
# Extracts all tables with automatic column detection
Features
✅ Production-ready scripts
All scripts include:
Error handling : Graceful failures with detailed error messagesValidation : Input validation and type checkingLogging : Configurable logging with timestampsType hints : Full type annotations for IDE supportCLI interface : --help flag for all scriptsExit codes : Proper exit codes for automation
✅ Comprehensive workflows
PDF Forms : Complete form processing pipelineTable Extraction : Advanced table detection and extractionOCR Processing : Scanned PDF text extractionBatch Operations : Process multiple PDFs efficiently
Validation
Advanced topics
PDF Form Processing For complete form workflows including:
Field analysis and detection
Dynamic form filling
Validation rules
Multi-page forms
Checkbox and radio button handling
Table Extraction For complex table extraction:
Multi-page tables
Merged cells
Nested tables
Custom table detection
Export to CSV/Excel
OCR Processing For scanned PDFs and image-based documents:
Tesseract integration
Language support
Image preprocessing
Confidence scoring
Batch OCR
Included scripts
Form processing analyze_form.py - Extract form field information
python scripts/analyze_form.py input.pdf [--output fields.json] [--verbose]
fill_form.py - Fill PDF forms with data
python scripts/fill_form.py input.pdf data.json output.pdf [--validate]
validate_form.py - Validate form data before filling
python scripts/validate_form.py data.json schema.json
Table extraction extract_tables.py - Extract tables to CSV/Excel
python scripts/extract_tables.py input.pdf [--output tables.csv] [--format csv|excel]
Text extraction extract_text.py - Extract text with formatting preservation
python scripts/extract_text.py input.pdf [--output text.txt] [--preserve-formatting]
Utilities merge_pdfs.py - Merge multiple PDFs
python scripts/merge_pdfs.py file1.pdf file2.pdf file3.pdf --output merged.pdf
split_pdf.py - Split PDF into individual pages
python scripts/split_pdf.py input.pdf --output-dir pages/
validate_pdf.py - Validate PDF integrity
python scripts/validate_pdf.py input.pdf
Common workflows
Workflow 1: Process form submissions # 1. Analyze form structure
python scripts/analyze_form.py template.pdf --output schema.json
# 2. Validate submission data
python scripts/validate_form.py submission.json schema.json
# 3. Fill form
python scripts/fill_form.py template.pdf submission.json completed.pdf
# 4. Validate output
python scripts/validate_pdf.py completed.pdf
Workflow 2: Extract data from reports # 1. Extract tables
python scripts/extract_tables.py monthly_report.pdf --output data.csv
# 2. Extract text for analysis
python scripts/extract_text.py monthly_report.pdf --output report.txt
Workflow 3: Batch processing import glob
from pathlib import Path
import subprocess
# Process all PDFs in directory
for pdf_file in glob.glob("invoices/*.pdf"):
output_file = Path("processed") / Path(pdf_file).name
result = subprocess.run([
"python", "scripts/extract_text.py",
pdf_file,
"--output", str(output_file)
], capture_output=True)
if result.returncode == 0:
print(f"✓ Processed: {pdf_file}")
else:
print(f"✗ Failed: {pdf_file} - {result.stderr}")
Error handling All scripts follow consistent error patterns:
# Exit codes
# 0 - Success
# 1 - File not found
# 2 - Invalid input
# 3 - Processing error
# 4 - Validation error
# Example usage in automation
result = subprocess.run(["python", "scripts/fill_form.py", ...])
if result.returncode == 0:
print("Success")
elif result.returncode == 4:
print("Validation failed - check input data")
else:
print(f"Error occurred: {result.returncode}")
Dependencies pip install pdfplumber pypdf pillow pytesseract pandas
# Install tesseract-ocr system package
# macOS: brew install tesseract
# Ubuntu: apt-get install tesseract-ocr
# Windows: Download from GitHub releases
Performance tips
Use batch processing for multiple PDFsEnable multiprocessing with --parallel flag (where supported)Cache extracted data to avoid re-processingValidate inputs early to fail fastUse streaming for large PDFs (>50MB)
Best practices
Always validate inputs before processingUse try-except in custom scriptsLog all operations for debuggingTest with sample PDFs before productionSet timeouts for long-running operationsCheck exit codes in automationBackup originals before modification
Troubleshooting
Common issues "Module not found" errors :
pip install -r requirements.txt
# Install tesseract system package (see Dependencies)
Memory errors with large PDFs :
# Process page by page instead of loading entire PDF
with pdfplumber.open("large.pdf") as pdf:
for page in pdf.pages:
text = page.extract_text()
# Process page immediately
Getting help All scripts support --help:
python scripts/analyze_form.py --help
python scripts/extract_tables.py --help
For detailed documentation on specific topics, see:
