[3.15] Docs: Acknowledge prior art for Tachyon (GH-161445) (#161446)

Author: pablogsal

Doc/library/profiling.sampling.rst

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

Doc/whatsnew/3.15.rst

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