Beyond Pandas: Architecting High-Performance Python Pipelines

Large datasets crash pandas because they load entirely into RAM. Instead of buying more memory, optimize your pipeline. Use Polars for lazy execution, Dask for chunked processing, and stream data instead of loading it all at once. Replace slow Python loops with vectorized operations and monitor memory usage with profiling tools. Smarter architecture turns batch jobs into real-time systems.