Python Memory Tricks to Boost Performance

Python memory optimization techniques can drastically improve performance for data-heavy applications. The article outlines eight practical strategies including using generators for processing one item at a time, adding __slots__ to classes to reduce object memory footprint, implementing weak references for caches, and utilizing appropriate data structures like arrays instead of lists. These methods can reduce RAM usage by 40-60% in large programs, with Python 3.13's new mimalloc feature providing automatic memory optimization benefits.