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mblanke
9b98ab9614
- NetworkMap: hunt-scoped force-directed graph with click-to-inspect popover - NetworkMap: zoom/pan (wheel, drag, buttons), viewport transform - NetworkMap: clickable IP/Host/Domain/URL legend chips to filter node types - NetworkMap: brighter colors, 20% smaller nodes - DatasetViewer: IOC columns highlighted with colored headers + cell tinting - AUPScanner: hunt dropdown replacing dataset checkboxes, auto-select all - Rename 'Social Media (Personal)' theme to 'Social Media' with DB migration - Fix /api/hunts timeout: Dataset.rows lazy='noload' (was selectin cascade) - Add OS column mapping to normalizer - Full backend services, DB models, alembic migrations, new routes - New components: Dashboard, HuntManager, FileUpload, NetworkMap, etc. - Docker Compose deployment with nginx reverse proxy
32 lines
1.2 KiB
Markdown
32 lines
1.2 KiB
Markdown
# Performance Profiling (Bun/Node)
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Use this skill when:
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- a hot path feels slow
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- CPU usage is high
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- you suspect accidental O(n²) or repeated work
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- you need evidence before optimizing
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## Bun CPU profiling
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Bun supports CPU profiling via `--cpu-prof` (generates a `.cpuprofile` you can open in Chrome DevTools).
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Upcoming: `bun --cpu-prof-md <script>` outputs a CPU profile as **Markdown** so LLMs can read/grep it easily.
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### Workflow (Bun)
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1) Run the workload with profiling enabled
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- Today: `bun --cpu-prof ./path/to/script.ts`
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- Upcoming: `bun --cpu-prof-md ./path/to/script.ts`
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2) Save the output (or `.cpuprofile`) into `./profiles/` with a timestamp.
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3) Ask the Reviewer agent to:
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- identify the top 5 hottest functions
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- propose the smallest fix
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- add a regression test or benchmark
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## Node CPU profiling (fallback)
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- `node --cpu-prof ./script.js` writes a `.cpuprofile` file.
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- Open in Chrome DevTools → Performance → Load profile.
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## Rules
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- Optimize based on measured hotspots, not vibes.
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- Prefer algorithmic wins (remove repeated work) over micro-optimizations.
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- Keep profiling artifacts out of git unless explicitly needed (use `.gitignore`).
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