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[subinterpreters] Don't share Python objects between interpreters #84713
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To get one GIL per interpreter (bpo-40512), either PyObject.ob_refcnt member must become an atomic variable, or subinterpreters must not share any object. Right now, subinterpreters share Python objects. For example, PyModule_Type is declared statically and so shared by all interpreters and so PyModule_Type.tp_mro tuple is accessed in parallel by multiple interpreters. If PyObject.ob_refcnt is not atomic, Py_INCREF() and Py_DECREF() are unsafe and tp_mro tuple can be destroyed whereas it is still used. I propose to make PyObject.ob_refcnt atomic for now, when Python is built with EXPERIMENTAL_ISOLATED_SUBINTERPRETERS macro defined. It's a temporary workaround until subinterpreters stop sharing objects. |
Yep, before per-interpreter GIL is official we must get to the point where *no* PyObject objects are shared. Making PyObject.ob_refcnt atomic until then (only as part of the experiment) should be fine. |
I would like to add: "no PyObject objects are shared in the stdlib" ;-) |
Another example of this issue are parallel Py_INCREF/Py_DECREF calls on the tp_bases member of a type. |
The current plan is to not share any object between two interpreters, so this PR is not needed. I close my PR 19958 which marked PyObject.ob_refcnt as atomic. |
Until all Python stdlib C extensions and all third-party C extensions will be modified to no longer use and define static types and will stop shared Python objects between two interpreters, we can no longer micro-optimize the comparison of two interned strings by only comparing their memory addresse. See bpo-46006. |
Sharing objects between multiple interpreters can cause complex bugs leading to crashes: https://bugs.python.org/issue46070#msg410493 For this specific bug, I wrote a workaround (GH-30577). |
I don't have the bandwidth to work on this issue, so I just close it. |
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