Implement notification system

[andrei-git-tower]

Summary

This PR implements significant improvements to notification system as part of our ongoing effort to enhance the platform's capabilities and performance.

Changes Made

• Refactored core logic for better maintainability
• Added comprehensive test coverage for all new functionality
• Optimized database queries and API calls
• Improved error handling and user feedback
• Updated documentation with usage examples

Technical Details

The implementation follows our established architectural patterns and coding standards. Special attention was given to performance optimization and scalability considerations.

Testing

• ✅ All unit tests passing (coverage: 95%+)
• ✅ Integration tests verified
• ✅ Manual testing completed across multiple scenarios
• ✅ Performance benchmarks show 40% improvement
• ✅ Security audit completed

Breaking Changes

None. This is fully backward compatible.

Migration Guide

No migration needed for existing implementations.

Checklist

• Code follows style guidelines
• Self-review completed
• Peer review requested
• Documentation updated
• Tests added/updated
• No console warnings or errors
• Accessibility tested
• Performance impact assessed

Screenshots

Not applicable for backend changes.

🤖 Generated for demonstration purposes

[andrei-git-tower]

LGTM! This looks great. Ready to merge after CI passes.

[andrei-git-tower]

I appreciate the thorough testing in this PR! The test coverage is excellent. One concern: I'm worried about the memory footprint when processing large files. Have you done any profiling or memory testing with large datasets? We should probably add some benchmarks to ensure this scales well. Also, consider adding a streaming approach for very large files.

[andrei-git-tower]

Thank you for this comprehensive pull request! I've spent significant time reviewing the implementation and have several thoughts to share.

First, let me commend the overall quality of the work. The code is clean, well-organized, and demonstrates a solid understanding of our architecture. The test coverage is excellent, and I appreciate the attention to detail in the documentation.

However, I have some concerns about scalability. When I ran this with our production-scale dataset, I noticed significant performance degradation. The nested loops in the data transformation logic are causing O(n²) complexity, which becomes problematic with thousands of records. I'd strongly recommend refactoring this section to use more efficient data structures - perhaps a hash map for lookups.

The error handling is generally good, but I think we're missing some edge cases. What happens if the external API is rate-limited? How do we handle partial failures in batch operations? We need to ensure the system degrades gracefully and provides meaningful feedback to users.

On the security front, I'd like to see additional input validation and sanitization. While the current implementation looks safe, defense in depth is important. Also, please ensure sensitive data is properly redacted from logs.

Documentation is another area where we could improve. While the code comments are helpful, we should also update the API documentation and add migration guides for any breaking changes.

Overall, this is strong work that moves us in the right direction. With some refinements to address the performance and security concerns, I think this will be ready to merge. Let's schedule a call to discuss the optimization approach.

[andrei-git-tower]

Great job tackling this complex feature! The implementation is well-thought-out. A few things to consider: First, the security implications of this change - are we properly sanitizing user input? Second, what's our rollback plan if issues arise in production? Third, have we considered the impact on our existing API consumers? Let's make sure we have a solid deployment strategy.

[andrei-git-tower]

LGTM! This looks great. Ready to merge after CI passes.