Simon Willison Uses Python 3.15 Profiling to Identify web-edit’s Line-Ending Bottleneck

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Simon Willison demonstrated Python 3.15’s built-in sampling profiler on the unmodified web-edit app, finding that preserving mixed line endings dominated the editing workload. He had GPT-6 Astra Extra High in Codex run the profiler and produce a flame graph and source heatmap. In the profiled workload, `preserve_endings` appeared in 64.8% of 15,296 CPU stacks, while `SequenceMatcher.find_longest_match` accounted for 38.3% of leaf samples. AnyIO’s worker thread produced 95.1% of the stacks, making sampling across all threads essential to capturing the work.

Generated by AI from reports · Updated 3 days ago

Latest development10/13 00:58 (UTC+8)

Profiling web-edit with Python 3.15 Reveals Line-Ending Workload Hotspots Simon Willison

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10/13

00:58
Simon Willison
Profiling web-edit with Python 3.15 Reveals Line-Ending Workload Hotspots
Profiling the unmodified web-edit app with Python 3.15’s built-in `profiling.sampling` found that preserving mixed line endings dominated the editing workload. `preserve_endings` appeared in 64.8% of 15,296 CPU stacks, while `SequenceMatcher.find_longest_match` contributed 38.3% of leaf samples; 95.1% of stacks came from AnyIO’s worker thread, making all-thread sampling essential.

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