tools / python-profiler
Python Profiler
Summarize Python profiler output, hot frames, blocking calls, asyncio stalls, import cost, and CPython stack snapshots.
P2PerformanceMedium severity
55
debug signal score
2 signals
2 signals detected. Start with profiler table.
Detected signals
Profiler table
Python profiler output is present.
Sort by cumulative time for callers and total time for hot leaf functions.
Asyncio stall
Async runtime behavior may be involved.
Check blocking calls inside async handlers and thread/process offloading.
Highlighted lines
line 1
ncalls tottime percall cumtime function
Profiler table
line 3
asyncio slow callback took 0.8 seconds
Asyncio stall
Fix checklist
Sort by cumulative time for callers and total time for hot leaf functions.
Check blocking calls inside async handlers and thread/process offloading.
Sort profiler output by cumulative and self time.
Separate CPU-bound work from I/O wait.
Create a small benchmark before changing code.
DebugTools product
Python Profiler
Python Profiler is a focused DebugTools mini-product for developers. Summarize Python profiler output, hot frames, blocking calls, asyncio stalls, import cost, and CPython stack snapshots.
Use cases
- Identify slow paths, hot operations, large bundles, and runtime bottlenecks.
- Compare before/after evidence while tuning performance.
- Summarize profiler output into follow-up actions.
How it works
- Paste or load the snippet you want to inspect in Python Profiler.
- Run the tool in the browser and review the highlighted output.
- Copy, export, or turn the result into the next debugging step.
Privacy
- Python Profiler is local-first. The core workflow runs in your browser and does not require sending pasted content to DebugTools servers.
This tool history
Recent Python Profiler sessions
Only visits for this tool are shown. Pasted content, tokens, request bodies, and logs are not stored here.
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