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Found 9 Skills
structlog - structured logging library for Python with native JSON support, context binding, and processor pipeline. Integrates with FastAPI, Django, and standard logging module. USE WHEN: user mentions "structlog", "python structured logging", "context binding", asks about "JSON logging python", "fastapi logging", "django structured logging" DO NOT USE FOR: Standard Python logging - use `python-logging` instead, Node.js logging - use `pino` or `winston`, Java logging - use `slf4j` or `logback` instead
Structured logging for Python applications with context support and powerful processors
Configures structured logging (Serilog/.NET, structlog/Python)
Application monitoring and observability setup for Python/React projects. Use when configuring logging, metrics collection, health checks, alerting rules, or dashboard creation. Covers structured logging with structlog, Prometheus metrics for FastAPI, health check endpoints, alert threshold design, Grafana dashboard patterns, error tracking with Sentry, and uptime monitoring. Does NOT cover incident response procedures (use incident-response) or deployment (use deployment-pipeline).
Observability patterns for Python applications. Triggers on: logging, metrics, tracing, opentelemetry, prometheus, observability, monitoring, structlog, correlation id.
Monitoring, logging, and tracing implementation using OpenTelemetry as the unified standard. Use when building production systems requiring visibility into performance, errors, and behavior. Covers OpenTelemetry (metrics, logs, traces), Prometheus, Grafana, Loki, Jaeger, Tempo, structured logging (structlog, tracing, slog, pino), and alerting.
Modern Python development with uv, the fast Python package and project manager. Covers project management (uv init, uv add, uv sync, uv lock), virtual environments, Python version management (uv python install/pin), script runners (uv run), tool management (uvx), workspace support for monorepos, and publishing to PyPI. Includes Python patterns for FastAPI, Pydantic, async/await, type checking, pytest, structlog, and CLI tools. Use when initializing Python projects, managing dependencies with uv, configuring pyproject.toml, setting up virtual environments, running scripts, managing Python versions, building monorepos with workspaces, containerizing Python apps, or writing modern Python with type hints.
Expert guidance for building production-ready FastAPI applications with modular architecture where each business domain is an independent module with own routes, models, schemas, services, cache, and migrations. Uses UV + pyproject.toml for modern Python dependency management, project name subdirectory for clean workspace organization, structlog (JSON+colored logging), pydantic-settings configuration, auto-discovery module loader, async SQLAlchemy with PostgreSQL, per-module Alembic migrations, Redis/memory cache with module-specific namespaces, central httpx client, OpenTelemetry/Prometheus observability, conversation ID tracking (X-Conversation-ID header+cookie), conditional Keycloak/app-based RBAC authentication, DDD/clean code principles, and automation scripts for rapid module development. Use when user requests FastAPI project setup, modular architecture, independent module development, microservice architecture, async database operations, caching strategies, logging patterns, configuration management, authentication systems, observability implementation, or enterprise Python web services. Supports max 3-4 route nesting depth, cache invalidation patterns, inter-module communication via service layer, and comprehensive error handling workflows.
Implements OpenTelemetry (OTEL) logging with trace context correlation and structured logging. Use when setting up production logging with OTEL exporters, structlog/loguru integration, trace context propagation, and comprehensive test patterns. Covers Python implementations for FastAPI, Kafka consumers, and background jobs. Includes OTLP, Jaeger, and console exporters.