Python Backend Architecture Review

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Evaluates Python backend architectures across multiple dimensions, including system design patterns, database modeling, and API consistency. It provides actionable feedback on technology stack selection, security controls, and observability, specifically tailored to the Python ecosystem. Whether reviewing a new design document or optimizing an existing system, this skill helps developers identify bottlenecks, security gaps, and over-engineering while suggesting framework-specific best practices for tools like FastAPI, Django, and SQLAlchemy.

Características Principales

• Performance and scalability review focusing on async/await patterns, load balancing, and resource management.
• In-depth analysis of system design patterns, including microservices, event-driven, and serverless architectures.
• 5 GitHub stars
• Security architecture assessment including authentication, authorization, and vulnerability prevention.
• Database evaluation covering modeling, normalization, caching strategies, and ORM-specific optimizations.
• Observability guidance for logging, distributed tracing, and metrics collection.

Casos de Uso

• Reviewing system design documents before beginning development of a new Python application.
• Auditing existing backend infrastructure for security vulnerabilities and scalability bottlenecks.
• Optimizing data flow and API design for complex microservices-based systems.