Comments (2)
I can't run this because you haven't attached the contents of the directory. Please do so.
All this said, Scalene doesn't claim to be faster than memray. In any event, these numbers aren't helpful given that they are for such old versions of Python and Scalene. I'd be interested to see that data for current versions.
It's also important to note that Scalene time includes the time to generate its profile, so you need to add the post-processing for memray as well in order for the comparison to be more fair. All this said, Python 3.12 and later have some improvements that, once we incorporate them, we expect will substantially lower Scalene's overhead.
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Closing for lack of response.
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Related Issues (20)
- Per-process GPU accounting isn't working under CUDA 12
- Scalene can't open browser on MacOS HOT 4
- Is there a way to measure time spent in GC? HOT 3
- GPU and memory columns not present HOT 8
- Python 3.11 support HOT 1
- defaults to cli HOT 2
- Segmentation fault profiling project
- Getting SIGSEGV with empty program HOT 5
- Probable bug with scalene when profiling async code HOT 2
- Wheel missing for Python 3.12 HOT 3
- Scalene does not seem to work with multiprocessing HOT 2
- Unicode decode error after executing cupy code in ipython
- Scalene crashes on sklearn / statsmodel etc. imports HOT 10
- Include flags from environment variables set externally HOT 1
- GUI Filter: Display only functions / methods with profiled lines
- Discrepency between online GUI and the generated HTML HOT 1
- Ollama server is not detected HOT 3
- Environment variables from .env file are not loaded HOT 1
- Add ability to control whether `profile.html` is generated HOT 1
- ImportError: dlopen with crdp.abi3.so, 0x0002: bad bind opcode 0x00 HOT 6
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