#python

用 Python 处理了一个 5 亿行的数据集。Pandas 直接崩了，换了 Polars 秒处理。大数据时代工具选型太重要了。

Pandas tip: If your DataFrame operations are slow, try .itertuples() instead of .iterrows(). 100x faster, same result.

Started using Polars instead of Pandas. 10x speed improvement on a 50M row dataset. My data pipelines are flying.

Pythonの仮想環境管理、uvが速すぎて衝撃。pipより10倍速い。Rust製ツールは本当に速い。

Jupyter notebooks are great for exploration. Terrible for production. Know when to switch.