python-patterns

Team conventions for Python development — credentials, API clients, LLM response parsing, testing patterns, and data pipeline structure. Covers dotenv loading, retry logic, secret validation, and pipe

SKILL.md

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Python Patterns — Team Conventions

Unified conventions for team Python projects: credential management, API clients, testing discipline, and data pipeline structure. Supplements standard patterns with team-specific rules.

When to Activate

  • Writing credential/secret handling code or .env files
  • Creating or modifying API clients (GitHub, Stripe, LLM APIs)
  • Parsing LLM responses or structured API outputs
  • Writing or reviewing tests (TDD workflow, mocking external APIs)
  • Building or debugging data pipeline stages
  • Reviewing code that handles HTTP responses or LLM output

Quick Rules

Credentials:

  • Never hardcode or use real defaults. Fail fast if missing. Always create .env.example.

APIs:

  • Always timeout (30s). Only retry transient errors (429, 5xx). Always validate response structure.

Tests:

  • Mock external APIs. Set random_state=42. Target 80%+ coverage. Test behavior, not internals.

Pipelines:

  • Each stage is independently runnable. Validate input before processing. Include metadata in every output. Fail fast on invalid data.

Details

Read references/credentials.md, references/api-clients.md, references/testing.md, and references/pipelines.md for full examples and anti-patterns.