Overview
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Writing code can be easy, but maintaining a product is always a challenge. In this course, learn how to efficiently manage your Python projects and make them production ready.
Syllabus
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Introduction
- Creating efficient Python projects
- What you should know
- Using the exercise files
- Working together as a team
- Avoid mistakes
- Feedback loop
- The problem
- Package managers
- Production vs. development
- Internal PyPI vendoring
- Docker
- Challenge: Gunicorn
- Solution: Gunicorn
- What to test
- CI/CD
- Development vs. CI environment
- Feedback to developers
- Eyes to production
- Python loggers
- Log configuration
- Dynamic configuration
- Structured logging
- Log aggregators
- Challenge: Configure logging
- Solution: Configure logging
- What are metrics?
- Types of metrics
- Designing metrics
- Metrics decorators
- Metrics systems
- Altering
- Challenge: report_errors metrics decorator
- Solution: report_errors metris decorator
- __main__.py
- Deployment problems
- Deployment strategies
- Reverting deployment
- Use Fabric to automate deployment
- Continuous delivery
- Next steps
