Stories about CPython
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The Import Tax: A Longitudinal Measurement of Startup Cost in the Python Ecosystem
AI InsightPython import cost has long been masked by steady-state benchmarks, but this measurement reveals a heavily skewed distribution: half of packages are fast, while the tail reaches 354ms. PEP 810 is shifting from anecdote-driven to data-driven design, suggesting future Python performance optimization will focus on real bottlenecks in cold-start scenarios rather than average throughput.Key TakeawayPython 3.15's lazy import decision is shifting from anecdote-driven to data-driven.Why It MattersImport cost is a real bottleneck for CLI tools, tests, and serverless cold starts; this measurement could influence PEP 810's default behavior, affecting startup experience for millions of developers and cloud function billing.Who's Affected- Python Core TeamGains ecosystem-level data to refine PEP 810 design and defaults.
- CLI Tool DevelopersIf lazy imports become widespread, tool startup latency may drop significantly, improving UX.
- Serverless PlatformsLower cold-start cost can reduce function init time and potentially billing based on compute time.
- Package MaintainersPackages with high tail import cost may face optimization pressure to avoid ecosystem bottlenecks.
What's NextWatch the measured effect of PEP 810 after Python 3.15 release, especially whether p99 latency for tail packages drops and whether mainstream CLI/serverless frameworks adjust packaging due to lazy imports.Importance 62/100