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 messages

Validation

Input validation and type checking

Logging

Configurable logging with timestamps

Type hints

Full type annotations for IDE support

CLI interface

:

--help

flag for all scripts

Exit codes

Proper exit codes for automation

✅ Comprehensive workflows

PDF Forms

Complete form processing pipeline

Table Extraction

Advanced table detection and extraction

OCR Processing

Scanned PDF text extraction

Batch Operations

Process multiple PDFs efficiently

Validation

Pre and post-processing 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 See FORMS.md Table Extraction For complex table extraction: Multi-page tables Merged cells Nested tables Custom table detection Export to CSV/Excel See TABLES.md OCR Processing For scanned PDFs and image-based documents: Tesseract integration Language support Image preprocessing Confidence scoring Batch OCR See OCR.md 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 All scripts require: pip install pdfplumber pypdf pillow pytesseract pandas Optional for OCR:

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 PDFs Enable multiprocessing with --parallel flag (where supported) Cache extracted data to avoid re-processing Validate inputs early to fail fast Use streaming for large PDFs (>50MB) Best practices Always validate inputs before processing Use try-except in custom scripts Log all operations for debugging Test with sample PDFs before production Set timeouts for long-running operations Check exit codes in automation Backup originals before modification Troubleshooting Common issues "Module not found" errors : pip install -r requirements.txt Tesseract not found :

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

Permission errors : chmod +x scripts/*.py 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: FORMS.md - Complete form processing guide TABLES.md - Advanced table extraction OCR.md - Scanned PDF processing