Scaling before profiling is like trying to fix slow internet by buying a bigger monitor. Sure, it looks cool, but nothing changes. In data engineering and Python-heavy pipelines, we often rush to scale clusters, spin up bigger machines, or move to distributed frameworks without ever asking: what’s actually slow? That’s where profiling steps in. Profiling... Continue Reading →
Lazy Evaluation vs Eager Evaluation: Compute Now or Compute When Needed
Have you ever noticed that some Python operations don’t execute immediately? Or why creating huge lists can crash your program? That’s where lazy evaluation vs eager evaluation comes into play — two contrasting approaches for handling computation. Understanding them is critical if you work with Python, Spark, or any data-intensive pipeline. 1. Eager Evaluation: Compute... Continue Reading →
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