I'm writing a python program that includes a c++ module (.so
, using boost.python
).
I'm starting several python threads that run a c++ function.
This is how the C++ code looks like:
#include <boost/python.hpp>
using namespace boost;
void f(){
// long calculation
// call python function
// long calculation
}
BOOST_PYTHON_MODULE(test)
{
python::def("f", &f);
}
And the python code:
from test import f
t1 = threading.Thread(target=f)
t1.setDaemon(True)
t1.start()
print "Still running!"
I encounter a problem: the "Still running!" message isn't shown, and I found out that the c++ thread is holding the GIL.
What is the best method of handling the GIL in my case of running c++ code from python code?
Thanks! Gal
I often find that using RAII-style classes to manage the Global Interpreter Lock (GIL) provides an elegant exception-safe solution.
For example, with the following with_gil
class, when a with_gil
object is created, the calling thread acquires the GIL. When the with_gil
object is destructed, it restores the GIL state.
/// @brief Guard that will acquire the GIL upon construction, and
/// restore its state upon destruction.
class with_gil
{
public:
with_gil() { state_ = PyGILState_Ensure(); }
~with_gil() { PyGILState_Release(state_); }
with_gil(const with_gil&) = delete;
with_gil& operator=(const with_gil&) = delete;
private:
PyGILState_STATE state_;
};
And the complementary without_gil
class does the opposite:
/// @brief Guard that will unlock the GIL upon construction, and
/// restore its staet upon destruction.
class without_gil
{
public:
without_gil() { state_ = PyEval_SaveThread(); }
~without_gil() { PyEval_RestoreThread(state_); }
without_gil(const without_gil&) = delete;
without_gil& operator=(const without_gil&) = delete;
private:
PyThreadState* state_;
};
Their usage within a function could be as follows:
void f()
{
without_gil no_gil; // release gil
// long calculation
...
{
with_gil gil; // acquire gil
// call python function
...
} // restore gil (release)
// long calculation
...
} // restore gil (acquire)
One can also use a higher level convenient class to provide a std::lock_guard
like experience. The GIL acquisition and release, save and restore semantics are slightly different than a normal mutex. Hence, the gil_guard
interface is different:
gil_guard.acquire()
will acquire the GILgil_guard.release()
will release the GILgil_guard_restore()
will restore the previous state/// @brief Guard that provides higher-level GIL controls.
class gil_guard
{
public:
struct no_acquire_t {} // tag type used for gil acquire strategy
static no_acquire;
gil_guard() { acquire(); }
gil_guard(no_acquire_t) { release(); }
~gil_guard() { while (!stack_.empty()) { restore(); } }
void acquire() { stack_.emplace(new with_gil); }
void release() { stack_.emplace(new without_gil); }
void restore() { stack_.pop(); }
static bool owns_gil()
{
// For Python 3.4+, one can use `PyGILState_Check()`.
return _PyThreadState_Current == PyGILState_GetThisThreadState();
}
gil_guard(const gil_guard&) = delete;
gil_guard& operator=(const gil_guard&) = delete;
private:
// Use std::shared_ptr<void> for type erasure.
std::stack<std::shared_ptr<void>> stack_;
};
And its usage would be:
void f()
{
gil_guard gil(gil_guard::no_acquire); // release gil
// long calculation
...
gil.acquire(); // acquire gil
// call python function
...
gil.restore(); // restore gil (release)
// long calculation
...
} // restore gil (acquire)
Here is a complete example demonstrating GIL management with these auxiliary classes:
#include <cassert>
#include <iostream> // std::cout, std::endl
#include <memory> // std::shared_ptr
#include <thread> // std::this_thread
#include <stack> // std::stack
#include <boost/python.hpp>
/// @brief Guard that will acquire the GIL upon construction, and
/// restore its state upon destruction.
class with_gil
{
public:
with_gil() { state_ = PyGILState_Ensure(); }
~with_gil() { PyGILState_Release(state_); }
with_gil(const with_gil&) = delete;
with_gil& operator=(const with_gil&) = delete;
private:
PyGILState_STATE state_;
};
/// @brief Guard that will unlock the GIL upon construction, and
/// restore its staet upon destruction.
class without_gil
{
public:
without_gil() { state_ = PyEval_SaveThread(); }
~without_gil() { PyEval_RestoreThread(state_); }
without_gil(const without_gil&) = delete;
without_gil& operator=(const without_gil&) = delete;
private:
PyThreadState* state_;
};
/// @brief Guard that provides higher-level GIL controls.
class gil_guard
{
public:
struct no_acquire_t {} // tag type used for gil acquire strategy
static no_acquire;
gil_guard() { acquire(); }
gil_guard(no_acquire_t) { release(); }
~gil_guard() { while (!stack_.empty()) { restore(); } }
void acquire() { stack_.emplace(new with_gil); }
void release() { stack_.emplace(new without_gil); }
void restore() { stack_.pop(); }
static bool owns_gil()
{
// For Python 3.4+, one can use `PyGILState_Check()`.
return _PyThreadState_Current == PyGILState_GetThisThreadState();
}
gil_guard(const gil_guard&) = delete;
gil_guard& operator=(const gil_guard&) = delete;
private:
// Use std::shared_ptr<void> for type erasure.
std::stack<std::shared_ptr<void>> stack_;
};
void f()
{
std::cout << "in f()" << std::endl;
// long calculation
gil_guard gil(gil_guard::no_acquire);
assert(!gil.owns_gil());
std::this_thread::sleep_for(std::chrono::milliseconds(500));
std::cout << "calculating without gil..." << std::endl;
// call python function
gil.acquire();
assert(gil.owns_gil());
namespace python = boost::python;
python::object print =
python::import("__main__").attr("__builtins__").attr("print");
print(python::str("calling a python function"));
gil.restore();
// long calculation
assert(!gil.owns_gil());
std::cout << "calculating without gil..." << std::endl;
}
BOOST_PYTHON_MODULE(example)
{
// Force the GIL to be created and initialized. The current caller will
// own the GIL.
PyEval_InitThreads();
namespace python = boost::python;
python::def("f", +[] {
// For exposition, assert caller owns GIL before and after
// invoking function `f()`.
assert(gil_guard::owns_gil());
f();
assert(gil_guard::owns_gil());
});
}
Interactive usage:
>>> import threading
>>> import example
>>> t1 = threading.Thread(target=example.f)
>>> t1.start(); print "Still running"
in f()
Still running
calculating without gil...
calling a python function
calculating without gil...
>>> t1.join()
If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
Donate Us With