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Phase 3: Performance & Internals

Phase 3: Performance & Internals

In this phase, we learn how to make Python run at “C-speed” by avoiding slow loops and profiling our code.

🗺️ Learning Path

  1. Vectorization: Using NumPy and Polars to avoid slow Python loops.
  2. Memory Profiling: Identifying and fixing memory leaks in long-running data pipelines.

🥅 Goals

  • Replace standard loops with vectorized operations.
  • Profile CPU and Memory usage.
  • Understand how to handle datasets larger than memory.