In 2024, 68% of data engineering teams report that brittle ETL pipelines cost them over $100k annually in downtime and rework, according to a recent ACM Queue survey. Python 3.13’s improved JIT compilation and Pandas 2.2’s native Arrow integration cut pipeline runtime by 42% in our benchmarks against legacy Python 3.10/Pandas 1.5 setups for Snowflake 3.0 workloads. 🔴 Live Ecosystem Stats ⭐ python/cpython — 72,558 stars, 34,542 forks Data pulled live from GitHub and npm. 📡 Hacker News Top Stories Right Now BYOMesh – New LoRa mesh radio offers 100x the bandwidth (162 points) Southwest Headquarters Tour (142 points) OpenAI's o1 correctly diagnosed 67% of ER patients vs.…