SQLAlchemy plugins

Centers Python backend development around async patterns, FastAPI, Django, and modern tooling, providing architectural guidance, testing strategies with pytest, and production best practices for scalable APIs and services.

Look up Python code examples and enforce Pythonic style — fetch syntax, concurrency, ML, and HPC references from pythonsheets.com while writing, debugging, or optimizing code, and get linting guidance for readable, idiomatic Python.

Enforce Python code quality with a verified-issue workflow: review FastAPI routing, SQLAlchemy database patterns, PostgreSQL queries, pytest tests, and general Python type safety, using parallel linters (ruff, mypy) and multi-step verification to eliminate false positives.

Guides Python application development with FastAPI, SQLAlchemy, and Temporal patterns, plus TypeScript support for Drizzle, Fastify, and Vitest. Includes architecture guidance, stub-driven TDD, automated code review, commit conventions, and documentation generation.

Build modern Python web apps with Django and FastAPI, define SQLAlchemy models and Alembic migrations, write pytest tests, debug errors, and review code quality using specialized agents that orchestrate database tasks and full codebase reviews.

Accelerate and improve DataHub connector development and metadata management with skills for planning connectors, reviewing code against golden standards, enriching metadata, tracing lineage, managing data quality, searching the catalog, setting up environments, and scaffolding micro frontends.

Summon Python specialists to scaffold production Django/FastAPI projects with uv/Docker/PostgreSQL, enforce Mypy/PEP8/security reviews, audit codebases for multi-agent parallelization, implement Celery tasks/WebSockets, and generate pytest strategies—all using 2025 patterns and official docs.

Build full-stack Litestar applications with integrated patterns for data access (SQLAlchemy, sqlspec), authentication, DTOs, HTMX/Inertia frontends, realtime WebSocket/SSE, task queues (SAQ), email, Vite bundling, and deployment to Docker/Kubernetes/Cloud Run. Includes an AI agent for PR review and MCP tool exposure.

Scaffold a production-ready FastAPI backend using async/await patterns, Mem0 for AI memory persistence, SQLAlchemy ORM with PostgreSQL database, and built-in deployment configurations.