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Python Observability Patterns

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0xdarkmatter·vlatest·backend·MIT

Helps with Python, patterns as part of developing backend services and APIs workflows.

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This skill no longer installs under the name python-observability-patterns. 0xdarkmatter/claude-mods has no skill named "python-observability-patterns" any more. It was renamed, moved or deleted upstream.

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0xdarkmatter

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About this skill

What it does

This skill provides Python code snippets and patterns for implementing observability practices in backend systems. It focuses on structured logging, metrics collection (using Prometheus), and distributed tracing (with Jaeger). The goal is to aid in debugging, performance monitoring, and understanding system behavior through automated instrumentation.

When to use it

  • You're building a Python-based API and need help setting up structured logging.
  • You want to instrument your application to collect metrics for dashboards like Grafana.
  • You are troubleshooting slow requests in a microservices architecture and require distributed tracing.
  • You’re looking for standardized patterns for integrating observability tools into existing Python codebases.

Key capabilities

  • Structured logging with JSON format
  • Prometheus metrics collection
  • Jaeger distributed tracing integration
  • Code snippets for common observability tasks

Example prompts

  • "Generate a Python function that logs a request to a service using structured logging."
  • "Show me how to expose a Prometheus metric from my Flask application."
  • "Give me an example of initializing Jaeger client in Python."

Tips & gotchas

This skill assumes familiarity with basic Python programming and concepts related to observability. You may need to install dependencies like prometheus_client or jaeger-client separately within your project environment.