Thread.start() can hang indefinitely if the new thread fails (MemoryError) during its initialization
Ninguém assumiu esta issue ainda.
- Linguagem predominante
- Python
- Estrelas
- 77.2k
- Forks
- 35.9k
- Métricas de merge de PRs
- Métricas de PR pendentes
Descrição
Bug report
Bug description:
There is a race condition in the threading module where a parent thread calling Thread.start() can wait forever if the newly created thread crashes with a MemoryError during its internal bootstrap process.
Case Explanation
In case we have a "Serving Thread" that creates threads on demand (e.g., for each HTTP request):
- When this Serving Thread calls
Thread.start(), the OS-level thread (pthread_create()^1 - Linux) is successfully created. The parent thread then waits for the new thread to signal that it has started correctly by callingself._started.wait()^2. - The new thread starts, but before it can signal the parent thread (Serving Thread) that it is alive with
self._started.set()^3 it encounters aMemoryError. - This
MemoryErrorcan occur at the C level during thePyObject_Callto the_bootstrapmethod or inside the_bootstrap_innermethod before_started.set()is reached, often due to memory pressure from other threads (or a heap limit being reached). - This exception is caught by the C-level entry point
thread_run(), which calls_PyErr_WriteUnraisableMsg^4 and prints "Exception ignored in thread started by: ..."
The new thread then exits without ever signaling the _started event, and the parent thread waits indefinitely on the _started.wait().
This also leaves the threading module in an inconsistent state, as the "zombie" thread object may not be correctly cleaned up from the _limbo dict.
How to Reproduce
This has been observed in high-concurrency server applications under heavy, sustained load, where heap memory can be rapidly consumed and exhausted by concurrent threads ^5.
This is a race condition that is difficult to reproduce reliably, as it requires triggering a MemoryError at a specific moment.
I found a (deterministic?) way to reproduce the issue by restricting the heap memory until it reaches a threshold where we can start a new thread, but this new thread won't get enough memory for its initialization.
On some machines (and depending of Python versions), it is sometimes necessary to tweak HARD_LIMIT_START / LIMIT_REDUCTION (I reproduced it on Ubuntu based machine with Python 3.11/3.12/3.13/3.14)
import resource
import threading
import gc
def handler():
pass
def serving():
# These should be tweak (depending of Python version + system)
HARD_LIMIT_START = 30_000_000
LIMIT_REDUCTION = 5_000
for _ in range(500_000):
gc.collect(2) # Force getting back memory: seems to increase the determinism of the script
# Limit the heap size available for this process
resource.setrlimit(resource.RLIMIT_DATA, (HARD_LIMIT_START, HARD_LIMIT_START * 2))
try:
handler_thread = threading.Thread(target=handler)
print(f'Start Thread: {handler_thread} - Heap size limit : {HARD_LIMIT_START}')
handler_thread.start()
handler_thread.join()
HARD_LIMIT_START -= LIMIT_REDUCTION
except RuntimeError as r: # If Python refused to launch a new Thread
print(f'RuntimeError: {r} - Cannot start the thread at all => error not detected.')
return
serving_thread = threading.Thread(target=serving)
serving_thread.start()
serving_thread.join()
Expected Behavior
I am not sure if this is an "accepted" limitation of (CPython) Thread or not. IMO, Thread.start() shouldn't hang indefinitely if the low-level thread is dead.
I didn't take the time to try to fix it yet (if possible). I would prefer to get your opinions on this first.
CPython versions tested on:
3.12, 3.13, 3.14
Operating systems tested on:
Linux
Linked PRs
- gh-140799
- gh-144750
- gh-153776
Guia de contribuição
Primeiros passos
- Leia a issue inteira e depois o guia de contribuição do projeto.
- Comente na issue dizendo que vai assumir — evita que duas pessoas façam o mesmo trabalho.
- Faça um fork do repositório e trabalhe em uma branch.
- Abra um pull request que referencie o número da issue.
Direção de pesquisa
Comece em Lib/threading.py, em torno de Thread.start() e _bootstrap_inner, e depois inspecione o ponto de entrada referenciado em Modules/_threadmodule.c e a implementação de pthread em Python/thread_pthread.h. Execute o reprodutor fornecido de limite de recursos do Linux nas versões listadas do CPython. Considera-se concluído quando Thread.start() não espera indefinidamente quando a inicialização falha, com cobertura de regressão para o caminho de falha.
Escrita pelo modelo de indexação a partir do texto da issue.
Avaliação
- Stack de tecnologia
- python
- Domínio
- operating-systems
- Tipo de issue
- Bug
- Dificuldade
- 4/5
- Tempo estimado
- 3-5 dias
- Status de atividade
- Estagnada
- Clareza
- Razoavelmente clara
- Facilidade para iniciantes
- 25/100