Enhancement Roadmap: Comprehensive Feature Plan

[jdrhyne]

Enhancement Roadmap: Nutrient DWS Python Client

Overview

This issue tracks the comprehensive enhancement plan for the Nutrient DWS Python Client based on OpenAPI specification v1.9.0 analysis. The goal is to expand from ~30% to ~80% API coverage while maintaining our high standards for code quality and backward compatibility.

Enhancement Categories

🔵 Priority 1: Enhanced Existing Methods

Improve current methods with additional OpenAPI capabilities

• feat: Core components - exceptions, file handling, and HTTP client #1 Multi-Language OCR Support - Support multiple languages in ocr_pdf()
• build(deps): bump codecov/codecov-action from 4 to 5 #2 Image Watermark Support - Add image watermarks to watermark_pdf()
• Add support for missing Nutrient DWS API tools #3 Selective Annotation Flattening - Add annotation ID filtering to flatten_annotations()

🟢 Priority 2: Core Missing Methods

Add commonly requested document operations

• Minor cleanup #4 Create Redactions - Implement create_redactions() with text/regex/preset strategies
• Add integration tests to CI workflow for pull requests #5 Import Annotations - Implement import_annotations() for Instant JSON/XFDF
• docs: add PyPI badges and changelog #6 Extract Page Range - Simple extract_pages() method (simpler than split_pdf)

🟡 Priority 3: Format Conversion Methods

Enable output format flexibility

• feat: integrate fork features with comprehensive Direct API methods a… #7 Convert to PDF/A - Implement convert_to_pdfa() for archival compliance
• Test with keyring token #8 Convert to Images - Implement convert_to_images() for PNG/JPEG/WebP
• Enhancement Roadmap: Comprehensive Feature Plan #9 Extract Content as JSON - Implement extract_content() for structured data
• Enhancement: Multi-Language OCR Support #10 Convert to Office Formats - Implement convert_to_office() for DOCX/XLSX/PPTX

🟠 Priority 4: Advanced Features

Sophisticated document processing capabilities

• Enhancement: Image Watermark Support #11 AI-Powered Redaction - Implement ai_redact() using AI entity detection
• Enhancement: Selective Annotation Flattening #12 Digital Signatures - Implement sign_pdf() with visual signatures
• Feature: Create Redactions Method #13 Batch Processing - Client-side batch_process() for bulk operations

Implementation Timeline

Phase 1 (Weeks 1-4)

Focus on Priority 1 enhancements that improve existing methods:

• Multi-language OCR
• Image watermarks
• Selective flattening

Phase 2 (Weeks 5-8)

Add Priority 2 core methods:

• Create redactions
• Import annotations
• PDF/A conversion

Phase 3 (Weeks 9-12)

Implement Priority 3 format conversions:

• Image extraction
• Content extraction
• Office format export

Phase 4 (Weeks 13-16)

Advanced features for Priority 4:

• AI redaction
• Digital signatures
• Batch processing

Success Metrics

• API Coverage: Increase from ~30% to ~80%
• Test Coverage: Maintain 95%+ coverage
• Documentation: 100% method documentation with examples
• Performance: Sub-second operations for common tasks
• Backward Compatibility: Zero breaking changes

Implementation Guidelines

For each enhancement:

1. Review OpenAPI specification for exact requirements
2. Implement with backward compatibility in mind
3. Add comprehensive unit and integration tests
4. Include detailed docstrings with examples
5. Update documentation and changelog
6. Consider performance implications

Related Documents

• FUTURE_ENHANCEMENTS_PLAN.md - Detailed enhancement specifications
• OPENAPI_COMPLIANCE_REVIEW.md - Current compliance status
• openapi_spec.yml - Official API specification v1.9.0

Contributing

We welcome contributions! Please:

1. Comment on the specific issue you'd like to work on
2. Follow the implementation template in each issue
3. Ensure all tests pass
4. Update documentation
5. Submit PR referencing the issue number

Questions?

Feel free to ask questions in the comments or open a discussion for broader topics.

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Labels: roadmap, enhancement, meta-issue
Milestone: v2.0.0