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claude-home/development/python-CONTEXT.md
Cal Corum 10c9e0d854 CLAUDE: Migrate to technology-first documentation architecture 
Complete restructure from patterns/examples/reference to technology-focused directories:

• Created technology-specific directories with comprehensive documentation:
  - /tdarr/ - Transcoding automation with gaming-aware scheduling
  - /docker/ - Container management with GPU acceleration patterns
  - /vm-management/ - Virtual machine automation and cloud-init
  - /networking/ - SSH infrastructure, reverse proxy, and security
  - /monitoring/ - System health checks and Discord notifications
  - /databases/ - Database patterns and troubleshooting
  - /development/ - Programming language patterns (bash, nodejs, python, vuejs)

• Enhanced CLAUDE.md with intelligent context loading:
  - Technology-first loading rules for automatic context provision
  - Troubleshooting keyword triggers for emergency scenarios
  - Documentation maintenance protocols with automated reminders
  - Context window management for optimal documentation updates

• Preserved valuable content from .claude/tmp/:
  - SSH security improvements and server inventory
  - Tdarr CIFS troubleshooting and Docker iptables solutions
  - Operational scripts with proper technology classification

• Benefits achieved:
  - Self-contained technology directories with complete context
  - Automatic loading of relevant documentation based on keywords
  - Emergency-ready troubleshooting with comprehensive guides
  - Scalable structure for future technology additions
  - Eliminated context bloat through targeted loading

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-08-12 23:20:15 -05:00

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Python Patterns

Project Structure

  • Use virtual environments (venv)
  • Implement proper package structure with __init__.py
  • Separate configuration from code
  • Use requirements.txt for dependencies

Code Organization

  • MVC/MVT patterns for web applications
  • Factory pattern for object creation
  • Context managers for resource handling
  • Async/await for I/O-bound operations

Error Handling

  • Use specific exception types
  • Implement proper logging with levels
  • Graceful degradation for external dependencies
  • Validation at API boundaries

Performance Considerations

  • Use generators for large datasets
  • Profile before optimizing
  • Leverage caching appropriately
  • Consider async for concurrent operations

Related Documentation

  • Examples: /examples/python/web-frameworks.md
  • Examples: /examples/python/api-clients.md
  • Examples: /examples/python/async-patterns.md
  • Reference: /reference/python/debugging.md
  • Reference: /reference/python/performance.md