python / python/cpython

Data race reading `_thread.RLock` recursion count in `repr()` under free-threading

Open
#154,928 1 comment 0 reactions 0 assignees View on GitHub

Nobody has claimed this yet.

extension-modules type-bug
Dominant language
Python
Stars
77.2k
Forks
35.9k
PR merge metrics
PR metrics pending

Description

Bug report

Bug description:

This is a follow-up to #153292 (data race in repr() of _thread.RLock), which was fixed by making rlock_repr read the lock's owner with an atomic load. The fix covered the owner (self->lock.thread) field, but rlock_repr still reads self->lock.level with a plain (non-atomic) load to compute the recursion count:

https://github.com/python/cpython/blob/22a6c51c94a4fde986b8964f1d36d5ec3ac20dcc/Modules/_threadmodule.c#L1287-L1305

self->lock.level is written by acquire / release / _acquire_restore, e.g.:

https://github.com/python/cpython/blob/22a6c51c94a4fde986b8964f1d36d5ec3ac20dcc/Modules/_threadmodule.c#L1198-L1210

So on a free-threaded build, repr(rlock) concurrent with acquire() or release() is still a data race, now on the level field rather than the owner field the earlier fix addressed.

Reproducer:

import _thread
from threading import Thread, Barrier

shared_rlock = _thread.RLock()
state = (5, _thread.get_ident())

def chain1_thread():
    for _ in range(20000):
        try:
            shared_rlock._acquire_restore(state)
        except Exception:
            pass

def chain2_thread():
    for _ in range(20000):
        try:
            repr(shared_rlock)
        except Exception:
            pass

N_C1 = 2
N_C2 = 4
barrier = Barrier(N_C1 + N_C2)

def _c1():
    barrier.wait()
    chain1_thread()

def _c2():
    barrier.wait()
    chain2_thread()

threads  = [Thread(target=_c1) for _ in range(N_C1)]
threads += [Thread(target=_c2) for _ in range(N_C2)]
for t in threads: t.start()
for t in threads: t.join()

TSAN Report :

==================
WARNING: ThreadSanitizer: data race (pid=655652)
  Read of size 8 at 0x7fffb6610540 by thread T6:
    #0 rlock_repr /cpython/./Modules/_threadmodule.c:1295:28 
    #1 PyObject_Repr /cpython/Objects/object.c:784:11 
    #2 builtin_repr /cpython/Python/bltinmodule.c:2677:12 
    #3 _PyEval_EvalFrameDefault /cpython/Python/generated_cases.c.h:2712:35  

  Previous write of size 8 at 0x7fffb6610540 by thread T1:
    #0 _thread_RLock__acquire_restore_impl /cpython/./Modules/_threadmodule.c:1210:22 
    #1 _thread_RLock__acquire_restore /cpython/./Modules/clinic/_threadmodule.c.h:537:20 
    #2 method_vectorcall_O /cpython/Objects/descrobject.c:476:24 
    #3 _PyObject_VectorcallTstate /cpython/./Include/internal/pycore_call.h:144:11 
    #4 PyObject_Vectorcall /cpython/Objects/call.c:327:12 
    #5 _Py_VectorCallInstrumentation_StackRefSteal /cpython/Python/ceval.c:768:11 
    #6 _PyEval_EvalFrameDefault /cpython/Python/generated_cases.c.h:1906:35

SUMMARY: ThreadSanitizer: data race /cpython/./Modules/_threadmodule.c:1295:28 in rlock_repr
==================
CPython versions tested on:

CPython main branch

Operating systems tested on:

Linux

Linked PRs
  • gh-155381

Contributor guide

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start in Modules/_threadmodule.c at rlock_repr and the acquire, release, and _acquire_restore implementations described in the report. Run the provided reproducer on a free-threaded build with ThreadSanitizer, then inspect the related tests and verify that concurrent repr() and lock updates no longer report a race.

Written by the indexing model from the issue text.

Assessment

Tech stack
c, python
Domain
operating-systems
Issue type
Bug
Difficulty
4/5
Estimated time
3-5 days
Activity status
Stale
Clarity
Clearly specified
Newbie friendliness
35/100

Get new issues in your inbox

A short digest of beginner-friendly GitHub issues.