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Statistical Profiling in Python

I would like to know that the Python interpreter is doing in my production environments.

Some time ago I wrote a simple tool called live-trace which runs a daemon thread which collects stacktraces every N milliseconds.

But signal handling in the interpreter itself has one disadvantage:

Although Python signal handlers are called asynchronously as far as the Python user is concerned, they can only occur between the “atomic” instructions of the Python interpreter. This means that signals arriving during long calculations implemented purely in C (such as regular expression matches on large bodies of text) may be delayed for an arbitrary amount of time.

Source: https://docs.python.org/2/library/signal.html

How could I work around above constraint and get a stacktrace, even if the interpreter is in some C code for several seconds?

Related: https://github.com/23andMe/djdt-flamegraph/issues/5

over 4 years ago · Santiago Trujillo
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I use py-spy with speedscope now. It is a very cool combination.

speedscope-view-of-py-spy-data

py-spy works on Windows/Linux/macOS, can output flame graphs by its own and is actively deployed, eg. subprocess profiling support was added in October 2019.

over 4 years ago · Santiago Trujillo Report

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Have you tried Pyflame? It's based on ptrace, so it shouldn't be affected by CPython's signal handling subtleties.

over 4 years ago · Santiago Trujillo Report

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Maybe the perf-tool from Brendan Gregg can help

over 4 years ago · Santiago Trujillo Report
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