我的 Python 扩展模块遇到了不可预知的行为，该模块包装了一个 C++ 库，该库启动一个新的 pthread，并在完成一些工作后生成回调回调用者。我已将其大大简化为一个仍然演示此问题的简单示例。以下有时会生成一个Fatal Python error: PyEval_SaveThread: NULL tstate，通常相当快。有时它在 SIGSEGV 上tupledealoc。偶尔会出现这种死锁。我不知道为什么。有没有人有任何想法？
这是我的python测试代码
import mymod
from time import sleep
from random import randrange
def my_cb1(s):
print("Python cb %s" % (s));
for x in range(1,1000):
num_cb = randrange(5) + 1
print("Starting %d" % mymod.doit(my_cb1, "myid" + str(x), num_cb))
while True:
sleep(1)
扩展模块是：
#include <pthread.h>
#define PY_SSIZE_T_CLEAN
#include <Python.h>
#include <stddef.h>
#include <iostream>
#include <map>
#include <deque>
#include <mutex>
#include <functional>
#include <thread>
static std::map<std::string, PyObject *> cb_map;
static std::mutex map_mtx;
struct fake_cb_info
{
fake_cb_info() = delete;
fake_cb_info(const unsigned long &num_cb, const std::string &id) :
num_cb(num_cb), id(id)
{
}
const unsigned long num_cb;
const std::string id;
};
static std::deque<struct fake_cb_info> deq;
static std::mutex deq_mtx;
static bool is_worker_thread_running = false;
static std::thread worker_thread;
typedef std::function<void(const std::string &id, const std::string &s)> doit_cb_t;
static void internal_cb(const std::string &id, const std::string &s)
{
std::scoped_lock<std::mutex> lk(map_mtx);
if (0 != cb_map.count(id))
{
PyGILState_STATE gstate;
gstate = PyGILState_Ensure();
PyObject *arglist = Py_BuildValue("(s)", s.c_str());
PyObject *result = PyObject_CallObject(cb_map.at(id), arglist);
Py_DECREF(arglist);
if (NULL == result)
{
if (NULL == PyErr_Occurred())
{
std::cerr << "Unknown error occurred in C callback" << std::endl;
}
else
{
PyErr_Print();
}
}
else
{
Py_DECREF(result);
}
PyGILState_Release(gstate);
}
else
{
std::cerr << "Unknown callback id " << id << std::endl;
}
}
void static worker()
{
size_t x = 0;
while(true)
{
std::scoped_lock<std::mutex> lk(deq_mtx);
if (deq.size() == 0)
{
usleep(1000);
continue;
}
auto info = deq.front();
deq.pop_front();
for (unsigned long i=0; i<info.num_cb; i++)
{
internal_cb(info.id, std::to_string(x++));
}
}
}
PyObject * _wrap_doit(void *self, PyObject *args, PyObject *kwargs)
{
PyObject *py_retval;
PyThreadState *py_thread_state = NULL;
PyObject *cb;
const char *id = NULL;
Py_ssize_t id_len;
std::string id_std;
unsigned long num_callbacks;
const char *keywords[] = {"cb_func", "id", "num_cb", NULL};
if (!PyArg_ParseTupleAndKeywords(args, kwargs, (char *) "Os#k", (char **) keywords, &cb, &id, &id_len, &num_callbacks))
{
abort();
}
if (!PyCallable_Check(cb))
{
abort();
}
id_std = std::string(id, id_len);
{
std::scoped_lock<std::mutex> lk(map_mtx);
if (0 == cb_map.count(id_std))
{
Py_INCREF(cb);
cb_map.insert(std::make_pair(id_std, cb));
// N.B. The corresponding Py_DECREF for the callback function PyObject
// is intentionally not here. It is in another extension module method
// that is not listed here (just trying to keep this example as small
// and lean as possible)
}
else
{
std::cerr << "Only one callback for ID!" << std::endl;
abort();
}
}
if (PyEval_ThreadsInitialized ())
{
std::cout << "Saving thread" << std::endl;
py_thread_state = PyEval_SaveThread();
}
{
// Stash away the info so that we will know how many callbacks to
// generate and sleep a bit. This is to simulate a real external library
// doing work which will, in turn, generate callbacks
struct fake_cb_info info(num_callbacks, id_std);
std::scoped_lock<std::mutex> lk(deq_mtx);
deq.push_back(info);
if (!is_worker_thread_running)
{
std::cout << "@@@@ Creating a new thread\n";
worker_thread = std::thread(&worker);
pthread_setname_np(worker_thread.native_handle(), "worker_thread");
worker_thread.detach();
is_worker_thread_running = true;
}
usleep(10000);
}
if (py_thread_state)
{
std::cout << "Restoring thread" << std::endl;
PyEval_RestoreThread(py_thread_state);
}
py_retval = Py_BuildValue((char *) "k", num_callbacks);
return py_retval;
}
static PyMethodDef mymod_functions[] = {
{
(char *) "doit",
(PyCFunction) _wrap_doit,
METH_KEYWORDS | METH_VARARGS,
"Generate requested number of multi-threaded callbacks.\n doit(callback_fn, id, num_callbacks)"
},
{NULL, NULL, 0, NULL}
};
static struct PyModuleDef moduledef = {
PyModuleDef_HEAD_INIT,
"mymod",
"pthread test module",
-1,
mymod_functions,
};
#define MOD_ERROR NULL
#define MOD_INIT(name) PyObject* PyInit_##name(void)
#define MOD_RETURN(val) val
#if defined(__cplusplus)
extern "C"
#endif
#if defined(__GNUC__) && __GNUC__ >= 4
__attribute__ ((visibility("default")))
#endif
MOD_INIT(mymod)
{
PyObject *m = PyModule_Create(&moduledef);
if (m == NULL) {
return MOD_ERROR;
}
return MOD_RETURN(m);
}
如果您想跳过setup.py编译扩展模块的步骤，这是我用来构建它的 shell 脚本
#!/bin/bash -eux
obj='test_python_cmodule.o'
lib='mymod.cpython-36m-x86_64-linux-gnu.so'
if [ -f $obj ]; then
rm $obj
fi
if [ -f $lib ]; then
rm $lib
fi
g++ -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I. -I/usr/include/python3.6m -c test_python_cmodule.cpp -o $obj -std=c++17 -Wno-unused-variable -g -O0
x86_64-linux-gnu-gcc -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-Bsymbolic-functions -Wl,-z,relro -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 $obj -lpthread -o $lib -lstdc++