PrepRabbit Backend Development Skill

Build FastAPI endpoints using Test-Driven Development by strictly applying the Red-Green-Refactor-Verify cycle. This ensures API endpoint creation is thoroughly tested throughout development and integrates seamlessly with existing Python backend services.

Parse Spark event logs to detect optimization opportunities by analyzing the log data using DuckDB. This approach allows you to identify specific performance improvements, such as detecting data skew or finding broadcast join opportunities in your Spark jobs.

The best way to implement a data skew detector for Spark jobs is to follow strict TDD principles and a Spark-centric architecture. This ensures the new detector is thoroughly tested and integrates seamlessly with your existing FastAPI backend.

You can use DuckDB for optimization detection within a FastAPI backend. It processes parsed Spark event logs to identify performance bottlenecks like data skew and broadcast join opportunities while maintaining a Python-based Spark-centric architecture.

Backend API development requires the Red-Green-Refactor-Verify cycle when adhering to strict Test-Driven Development methodologies. This cycle enforces writing failing tests first, implementing code to pass them, refactoring, and verifying the final API behavior.