How Complex is my Code?

A deep exploration of what code complexity really means, moving beyond Big O notation to cover Cyclomatic Complexity, Halstead Complexity, and — most originally — insights from psycholinguistics. The post draws parallels between natural language readability metrics (Mean Dependency Distance, Dependency Locality Theory, entropy/perplexity) and software complexity, arguing that cognitive load for the human reader is the most meaningful measure. It also covers practical use of complexity metrics combined with coupling and churn data to prioritize refactoring, illustrated with analysis of the Django codebase.