python-dev

Comprehensive Python code review across 11 quality domains — anti-patterns, type safety, design, style, resources, resilience, configuration, observability, testing, async, and background jobs

Python asyncio and async/await patterns — asyncio.gather, semaphores, async context managers, event loop, coroutines, tasks. MUST consult when writing async Python code, building concurrent systems, using async frameworks (FastAPI, aiohttp, asyncpg), or managing I/O-bound operations with non-blocking patterns.

Python anti-pattern checklist. MUST consult before finalizing any Python implementation, during Python code review, or when a Python bug traces to mutable defaults, bare except, circular imports, or other known traps.

Python background job patterns — Celery, RQ, dramatiq, task queues, workers. MUST consult when adding background tasks, job queues, long-running operations, worker processes, or decoupling work from request/response cycles in Python.

Python code style — ruff, black, isort, naming conventions, docstrings. MUST consult when configuring Python linters/formatters, establishing project style standards, or when style questions arise during Python code review.

Python configuration management — pydantic-settings, environment variables, .env files, secrets. MUST consult when externalizing config, adding settings classes, managing secrets, or implementing environment-specific behavior in Python.

Python design patterns — KISS, SoC, SRP, composition over inheritance, dependency injection. MUST consult when refactoring Python classes, choosing between inheritance and composition, implementing dependency injection, extracting abstractions, or restructuring Python modules.

Python observability — structlog, logging, OpenTelemetry, Prometheus, tracing. MUST consult when adding logging to Python code, implementing metrics/counters, setting up distributed tracing, or instrumenting Python services.

Python resilience — tenacity, retries, exponential backoff, circuit breakers, timeouts. MUST consult when adding retry logic, implementing timeouts, wrapping external API calls with fault tolerance, or handling transient failures in Python.

Python resource management — context managers, __enter__/__exit__, contextlib, cleanup patterns. MUST consult when writing context managers, managing connections/file handles, implementing cleanup logic, or building streaming responses in Python.

Python test patterns — pytest fixtures, parametrize, mocking, conftest, coverage. MUST consult as a reference when writing pytest fixtures, parametrized tests, mock strategies, or structuring Python test suites. Complements superpowers:test-driven-development (which drives the workflow).

Python type safety — type hints, generics, Protocol, TypeVar, mypy, pyright. MUST consult when adding type annotations, implementing generic classes, defining structural interfaces (Protocol), or configuring mypy/pyright in Python projects.