Scaling Concerns, NoDB, Elizabeth, Python 3.7 & Testing

Architectural Realism

In this episode, Michael and Brian discuss the importance of architectural context. They explore the common pitfall of over-engineering applications based on patterns from tech giants like Google or Amazon when your actual needs are smaller.

Key Principles

• Understand your problem fully before searching for solutions.
• Evaluate whether your current team size and application complexity justify the shift to microservices.

"Does it make sense to push programming complexity into infrastructure DevOps complexity?"

Tools and Technologies

NoDB

• A, Pythonic object store that utilizes Amazon S3 as a backend.
• Ideal for prototyping and scenarios where you want to avoid managing heavy database servers.

Elizabeth

• A high-performance alternative to the popular Faker library for generating dummy test data.
• Includes a useful PyTest integration for managing test fixtures.

Future Trends and Testing

Python 3.7 Outlook

• Significant performance optimizations are incoming, specifically regarding function calls which could become 20% faster.
• Integration of async context managers.

Hypothesis Testing

• The hosts discuss Hypothesis, a powerful library for automated property-based testing.
• It forces developers to better define function specifications and uncover difficult edge cases that manual examples might miss.