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[3.15] Docs: Acknowledge prior art for Tachyon (GH-161445)
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‎Doc/library/profiling.sampling.rst‎

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@@ -29,6 +29,13 @@ code changes or restarts. Because sampling occurs externally to the target
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process, overhead is virtually zero, making Tachyon suitable for both
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development and production environments.
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Tachyon follows earlier work on external sampling profilers such as
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`Austin <https://github.com/P403n1x87/austin>`__,
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`py-spy <https://github.com/benfred/py-spy>`__,
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`Pyflame <https://github.com/uber-archive/pyflame>`__, and
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`rbspy <https://github.com/rbspy/rbspy>`__. We thank their authors and the wider
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profiling community for their work and ideas.
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What is statistical profiling?
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==============================

‎Doc/whatsnew/3.15.rst‎

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@@ -356,6 +356,13 @@ A new statistical sampling profiler (Tachyon) has been added as
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:mod:`profiling.sampling`. This profiler enables low-overhead performance analysis of
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running Python processes without requiring code modification or process restart.
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Tachyon follows earlier work on external sampling profilers such as
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`Austin <https://github.com/P403n1x87/austin>`__,
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`py-spy <https://github.com/benfred/py-spy>`__,
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`Pyflame <https://github.com/uber-archive/pyflame>`__, and
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`rbspy <https://github.com/rbspy/rbspy>`__. We thank their authors and the wider
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profiling community for their work and ideas.
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Unlike deterministic profilers (such as :mod:`profiling.tracing`) that instrument
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every function call, the sampling profiler periodically captures stack traces from
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running processes. This approach provides virtually zero overhead while achieving

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