Is your Python code a 'messy' monolith of tightly coupled logic? This guide explores the modern relevance of SOLID principles, demonstrating how to refactor rigid scripts into modular, testable systems using protocols and dependency inversion. We compare a strict class-based approach with a lean functional alternative to find the perfect balance for 2025.
Python projects often collapse under the weight of tight coupling and messy imports. Arjan reveals how to transform fragile spaghetti code into a robust, extensible system using ABCs, Protocols, and functional closures. By centralizing messy logic into a single 'dirty corner' and using abstractions elsewhere, you'll create code that is actually easy to test.
DataFrames are flexible but often clunky for complex queries, while SQL is powerful but usually requires a heavy external server. DuckDB solves this by letting you run full SQL analytics directly on your local Python variables. This deep dive explores how to integrate this 'SQLite for Analytics' into your workflow for faster, cleaner data processing.