我在 Ubuntu 18.04 上使用 Flask 1.0.2 和 Python 3.6。我的应用程序应该使用 asyncio 和 asyncio.create_subprocess_exec()
启动后台脚本,从中读取标准输出,然后在脚本完成后返回状态。
我基本上是想从这篇文章中实现一个答案:
Non-blocking read on a subprocess.PIPE in python
该脚本已成功启动,我从中获得了所有预期的输出,但问题是它永远不会返回(意味着永远不会到达 Killing subprocess now
行)。当我从 Linux 终端检查进程列表 ( ps
) 时,后台脚本已退出。
我做错了什么,如何成功突破async for line in process.stdout
环形?
在我导入后的文件顶部,我创建了我的事件循环:
# Create a loop to run all the tasks in.
global eventLoop ; asyncio.set_event_loop(None)
eventLoop = asyncio.new_event_loop()
asyncio.get_child_watcher().attach_loop(eventLoop)
我在我的路线上方定义了我的异步协程:
async def readAsyncFunctionAndKill(cmd):
# Use global event loop
global eventLoop
print("[%s] Starting async Training Script ..." % (os.path.basename(__file__)))
process = await asyncio.create_subprocess_exec(cmd,stdout=PIPE,loop=eventLoop)
print("[%s] Starting to read stdout ..." % (os.path.basename(__file__)))
async for line in process.stdout:
line = line.decode(locale.getpreferredencoding(False))
print("%s"%line, flush=True)
print("[%s] Killing subprocess now ..." % (os.path.basename(__file__)))
process.kill()
print("[%s] Training process return code was: %s" % (os.path.basename(__file__), process.returncode))
return await process.wait() # wait for the child process to exit
我的(缩写)路线在这里:
@app.route("/train_model", methods=["GET"])
def train_new_model():
# Use global event loop
global eventLoop
with closing(eventLoop):
eventLoop.run_until_complete(readAsyncFunctionAndKill("s.py"))
return jsonify("done"), 200
调用的“s.py”脚本被标记为可执行文件并且位于同一工作目录中。缩写脚本如下所示(它包含几个子进程并实例化 PyTorch 类):
def main():
# Ensure that swap is activated since we don't have enough RAM to train our model otherwise
print("[%s] Activating swap now ..." % (os.path.basename(__file__)))
subprocess.call("swapon -a", shell=True)
# Need to initialize GPU
print("[%s] Initializing GPU ..." % (os.path.basename(__file__)))
device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
defaults.device = torch.device("cuda")
with torch.cuda.device(0):
torch.tensor([1.]).cuda()
print("[%s] Cuda is Available: %s - with Name: %s ..." % (os.path.basename(__file__),torch.cuda.is_available(),torch.cuda.get_device_name(0)))
try:
print("[%s] Beginning to train new model and replace existing model ..." % (os.path.basename(__file__)))
# Batch size
bs = 16
#bs = 8
# Create ImageBunch
tfms = get_transforms(do_flip=True,
flip_vert=True,
max_rotate=180.,
max_zoom=1.1,
max_lighting=0.5,
max_warp=0.1,
p_affine=0.75,
p_lighting=0.75)
# Create databunch using folder names as class names
# This also applies the transforms and batch size to the data
os.chdir(TRAINING_DIR)
data = ImageDataBunch.from_folder("TrainingData", ds_tfms=tfms, train='.', valid_pct=0.2, bs=bs)
...
# Create a new learner with an early stop callback
learn = cnn_learner(data, models.resnet18, metrics=[accuracy], callback_fns=[
partial(EarlyStoppingCallback, monitor='accuracy', min_delta=0.01, patience=3)])
...
print("[%s] All done training ..." % (os.path.basename(__file__)))
# Success
sys.exit(0)
except Exception as err:
print("[%s] Error training model [ %s ] ..." % (os.path.basename(__file__),err))
sys.exit(255)
if __name__== "__main__":
main()
最佳答案
这里有几个问题:
asyncio.get_child_watcher().attach_loop(eventLoop)
主要是多余的,因为 eventLoop = asyncio.new_event_loop()
,如果在主线程上运行,已经做到了。这是您所看到的问题的主要候选者。
OSError
异常(和子类),因为不合格 s.py
仅当它被设为可执行时才有效,以 #!
开头shebang 线,可在 PATH
上找到.它不会仅仅因为它在同一个目录中而工作,你也不想依赖当前的工作目录。async for line in process.stdout:
循环也会永远等待。考虑向代码添加超时以避免被错误的子进程阻塞。在多线程应用程序中使用 asyncio 子进程时,您确实想阅读 Python asyncio 文档中的两个部分:
asyncio.run_coroutine_threadsafe()
function在特定线程中的循环上运行协程。asyncio
使用非阻塞 os.waitpid(-1, os.WNOHANG)
调用跟踪子状态并依赖于使用信号处理(只能在主线程上完成)。 Python 3.8 移除了这个限制(通过添加一个新的 child watcher implementation,它在单独的线程中使用阻塞的每个进程 os.waitpid()
调用,以额外的内存为代价。但是,您不必坚持默认的子观察者策略。您可以使用
EventLoopPolicy.set_child_watcher()
并传入 different process watcher instance .实际上,这意味着向后移植 3.8 ThreadedChildWatcher
implementation .对于您的用例,确实不需要为每个线程运行一个新的事件循环。根据需要在单独的线程中运行单个循环。如果您在单独的线程中使用循环,根据您的 Python 版本,您可能还需要在主线程上运行循环或使用不同的进程观察器。一般来说,在 WSGI 服务器的主线程上运行 asyncio 循环并不容易,甚至不可能。
因此,您需要在单独的线程中永久运行一个循环,并且您需要使用一个无需主线程循环即可工作的子进程观察器。这是一个实现,这应该适用于 Python 3.6 及更高版本:
import asyncio
import itertools
import logging
import time
import threading
try:
# Python 3.8 or newer has a suitable process watcher
asyncio.ThreadedChildWatcher
except AttributeError:
# backport the Python 3.8 threaded child watcher
import os
import warnings
# Python 3.7 preferred API
_get_running_loop = getattr(asyncio, "get_running_loop", asyncio.get_event_loop)
class _Py38ThreadedChildWatcher(asyncio.AbstractChildWatcher):
def __init__(self):
self._pid_counter = itertools.count(0)
self._threads = {}
def is_active(self):
return True
def close(self):
pass
def __enter__(self):
return self
def __exit__(self, exc_type, exc_val, exc_tb):
pass
def __del__(self, _warn=warnings.warn):
threads = [t for t in list(self._threads.values()) if t.is_alive()]
if threads:
_warn(
f"{self.__class__} has registered but not finished child processes",
ResourceWarning,
source=self,
)
def add_child_handler(self, pid, callback, *args):
loop = _get_running_loop()
thread = threading.Thread(
target=self._do_waitpid,
name=f"waitpid-{next(self._pid_counter)}",
args=(loop, pid, callback, args),
daemon=True,
)
self._threads[pid] = thread
thread.start()
def remove_child_handler(self, pid):
# asyncio never calls remove_child_handler() !!!
# The method is no-op but is implemented because
# abstract base class requires it
return True
def attach_loop(self, loop):
pass
def _do_waitpid(self, loop, expected_pid, callback, args):
assert expected_pid > 0
try:
pid, status = os.waitpid(expected_pid, 0)
except ChildProcessError:
# The child process is already reaped
# (may happen if waitpid() is called elsewhere).
pid = expected_pid
returncode = 255
logger.warning(
"Unknown child process pid %d, will report returncode 255", pid
)
else:
if os.WIFSIGNALED(status):
returncode = -os.WTERMSIG(status)
elif os.WIFEXITED(status):
returncode = os.WEXITSTATUS(status)
else:
returncode = status
if loop.get_debug():
logger.debug(
"process %s exited with returncode %s", expected_pid, returncode
)
if loop.is_closed():
logger.warning("Loop %r that handles pid %r is closed", loop, pid)
else:
loop.call_soon_threadsafe(callback, pid, returncode, *args)
self._threads.pop(expected_pid)
# add the watcher to the loop policy
asyncio.get_event_loop_policy().set_child_watcher(_Py38ThreadedChildWatcher())
__all__ = ["EventLoopThread", "get_event_loop", "stop_event_loop", "run_coroutine"]
logger = logging.getLogger(__name__)
class EventLoopThread(threading.Thread):
loop = None
_count = itertools.count(0)
def __init__(self):
name = f"{type(self).__name__}-{next(self._count)}"
super().__init__(name=name, daemon=True)
def __repr__(self):
loop, r, c, d = self.loop, False, True, False
if loop is not None:
r, c, d = loop.is_running(), loop.is_closed(), loop.get_debug()
return (
f"<{type(self).__name__} {self.name} id={self.ident} "
f"running={r} closed={c} debug={d}>"
)
def run(self):
self.loop = loop = asyncio.new_event_loop()
asyncio.set_event_loop(loop)
try:
loop.run_forever()
finally:
try:
shutdown_asyncgens = loop.shutdown_asyncgens()
except AttributeError:
pass
else:
loop.run_until_complete(shutdown_asyncgens)
loop.close()
asyncio.set_event_loop(None)
def stop(self):
loop, self.loop = self.loop, None
if loop is None:
return
loop.call_soon_threadsafe(loop.stop)
self.join()
_lock = threading.Lock()
_loop_thread = None
def get_event_loop():
global _loop_thread
if _loop_thread is None:
with _lock:
if _loop_thread is None:
_loop_thread = EventLoopThread()
_loop_thread.start()
# give the thread up to a second to produce a loop
deadline = time.time() + 1
while not _loop_thread.loop and time.time() < deadline:
time.sleep(0.001)
return _loop_thread.loop
def stop_event_loop():
global _loop_thread
with _lock:
if _loop_thread is not None:
_loop_thread.stop()
_loop_thread = None
def run_coroutine(coro):
return asyncio.run_coroutine_threadsafe(coro, get_event_loop())
以上是我为 Make a Python asyncio call from a Flask route 发布的相同的通用“使用 Flask 运行异步”解决方案,但添加了 ThreadedChildWatcher
向后移植。然后您可以使用从
get_event_loop()
返回的循环。运行子进程,通过调用 run_coroutine_threadsafe()
:import asyncio
import locale
import logging
logger = logging.getLogger(__name__)
def get_command_output(cmd, timeout=None):
encoding = locale.getpreferredencoding(False)
async def run_async():
try:
process = await asyncio.create_subprocess_exec(
cmd, stdout=asyncio.subprocess.PIPE)
except OSError:
logging.exception("Process %s could not be started", cmd)
return
async for line in process.stdout:
line = line.decode(encoding)
# TODO: actually do something with the data.
print(line, flush=True)
process.kill()
logging.debug("Process for %s exiting with %i", cmd, process.returncode)
return await process.wait()
future = run_coroutine(run_async())
result = None
try:
result = future.result(timeout)
except asyncio.TimeoutError:
logger.warn('The child process took too long, cancelling the task...')
future.cancel()
except Exception as exc:
logger.exception(f'The child process raised an exception')
return result
请注意,上述函数可能需要超时(以秒为单位),这是您等待子进程完成的最长时间。
关于路由中的 Python3 Flask asyncio 子进程挂起,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/58547753/