分布式进程BaseManager(multiprocessing.managers)

分布式进程BaseManager(multiprocessing.managers)
原创howlowl 最后发布于2017-11-10 18:27:53 阅读数 3158 收藏
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命令行运行：

#task_master.py

import random,time,queue
from multiprocessing.managers import BaseManager

task_queue = queue.Queue()
result_queue = queue.Queue()

class QueueManager(BaseManager):
pass

def task_q():
return task_queue
def result_q():
return result_queue


print('master start.')
QueueManager.register('get_task_queue',callable=task_q)
QueueManager.register('get_result_queue',callable=result_q)
manager = QueueManager(address=('127.0.0.1',5000),authkey=b'abc')
manager.start()
task = manager.get_task_queue()
result = manager.get_result_queue()
for i in range(10):
n = random.randint(0,10000)
print('put task %d...' % n)
task.put(n)
print('try get results...')
for i in range(10):
r = result.get(timeout=100)
print('Result: %s' % r)
manager.shutdown()
print('master exit.')

得到：
master start.
master start.
Traceback (most recent call last):
File "<string>", line 1, in <module>
File "C:\Users\lenovo\AppData\Local\Programs\Python\Python35-32\lib\multiprocessing\spawn.py", line 106, in spawn_main
exitcode = _main(fd)
File "C:\Users\lenovo\AppData\Local\Programs\Python\Python35-32\lib\multiprocessing\spawn.py", line 115, in _main
prepare(preparation_data)
File "C:\Users\lenovo\AppData\Local\Programs\Python\Python35-32\lib\multiprocessing\spawn.py", line 226, in prepare
_fixup_main_from_path(data['init_main_from_path'])
File "C:\Users\lenovo\AppData\Local\Programs\Python\Python35-32\lib\multiprocessing\spawn.py", line 278, in _fixup_main_from_path
run_name="__mp_main__")
File "C:\Users\lenovo\AppData\Local\Programs\Python\Python35-32\lib\runpy.py", line 254, in run_path
pkg_name=pkg_name, script_name=fname)
File "C:\Users\lenovo\AppData\Local\Programs\Python\Python35-32\lib\runpy.py", line 96, in _run_module_code
mod_name, mod_spec, pkg_name, script_name)
File "C:\Users\lenovo\AppData\Local\Programs\Python\Python35-32\lib\runpy.py", line 85, in _run_code
exec(code, run_globals)
File "D:\4视频教程\PythonExercise Files\task_master.py", line 22, in <module>
manager.start()
File "C:\Users\lenovo\AppData\Local\Programs\Python\Python35-32\lib\multiprocessing\managers.py", line 479, in start
self._process.start()
File "C:\Users\lenovo\AppData\Local\Programs\Python\Python35-32\lib\multiprocessing\process.py", line 105, in start
self._popen = self._Popen(self)
File "C:\Users\lenovo\AppData\Local\Programs\Python\Python35-32\lib\multiprocessing\context.py", line 313, in _Popen
return Popen(process_obj)
File "C:\Users\lenovo\AppData\Local\Programs\Python\Python35-32\lib\multiprocessing\popen_spawn_win32.py", line 34, in __init__
prep_data = spawn.get_preparation_data(process_obj._name)
File "C:\Users\lenovo\AppData\Local\Programs\Python\Python35-32\lib\multiprocessing\spawn.py", line 144, in get_preparation_data
_check_not_importing_main()
File "C:\Users\lenovo\AppData\Local\Programs\Python\Python35-32\lib\multiprocessing\spawn.py", line 137, in _check_not_importing_main
is not going to be frozen to produce an executable.''')
RuntimeError:
An attempt has been made to start a new process before the
current process has finished its bootstrapping phase.
This probably means that you are not using fork to start your
child processes and you have forgotten to use the proper idiom
in the main module:
if __name__ == '__main__':
freeze_support()
...
The "freeze_support()" line can be omitted if the program
is not going to be frozen to produce an executable.
在命令行运行：
#task_master.py

import random,time,queue
from multiprocessing.managers import BaseManager

task_queue = queue.Queue()
result_queue = queue.Queue()

class QueueManager(BaseManager):
pass

##def task_q():
## return task_queue
##def result_q():
## return result_queue

if __name__ == '__main__':
print('master start.')
QueueManager.register('get_task_queue',callable= lambda: task_queue)
QueueManager.register('get_result_queue',callable= lambda: result_queue)
manager = QueueManager(address=('127.0.0.1',5000),authkey=b'abc')
manager.start()
task = manager.get_task_queue()
result = manager.get_result_queue()
for i in range(10):
n = random.randint(0,10000)
print('put task %d...' % n)
task.put(n)
print('try get results...')
for i in range(10):
r = result.get(timeout=100)
print('Result: %s' % r)
manager.shutdown()
print('master exit.')

得到：
master start.
Traceback (most recent call last):
File "task_master.py", line 22, in <module>
manager.start()
File "C:\Users\lenovo\AppData\Local\Programs\Python\Python35
-32\lib\multiprocessing\managers.py", line 479, in start
self._process.start()
File "C:\Users\lenovo\AppData\Local\Programs\Python\Python35
-32\lib\multiprocessing\process.py", line 105, in start
self._popen = self._Popen(self)
File "C:\Users\lenovo\AppData\Local\Programs\Python\Python35
-32\lib\multiprocessing\context.py", line 313, in _Popen
return Popen(process_obj)
File "C:\Users\lenovo\AppData\Local\Programs\Python\Python35
-32\lib\multiprocessing\popen_spawn_win32.py", line 66, in

__init__
reduction.dump(process_obj, to_child)
File "C:\Users\lenovo\AppData\Local\Programs\Python\Python35
-32\lib\multiprocessing\reduction.py", line 59, in dump
ForkingPickler(file, protocol).dump(obj)
_pickle.PicklingError: Can't pickle <function <lambda> at
0x005656F0>: attribute lookup <lambda> on __main__ failed
Traceback (most recent call last):
File "<string>", line 1, in <module>
File "C:\Users\lenovo\AppData\Local\Programs\Python\Python35
-32\lib\multiprocessing\spawn.py", line 100, in spawn_main
new_handle = steal_handle(parent_pid, pipe_handle)
File "C:\Users\lenovo\AppData\Local\Programs\Python\Python35
-32\lib\multiprocessing\reduction.py", line 81, in steal_handle
_winapi.PROCESS_DUP_HANDLE, False, source_pid)
OSError: [WinError 87] 参数错误。

但是，以下代码可以正常运行：
#task_master.py

import random,time,queue
from multiprocessing.managers import BaseManager

task_queue = queue.Queue()
result_queue = queue.Queue()

class QueueManager(BaseManager):
pass

def task_q():
return task_queue
def result_q():
return result_queue

if __name__ == '__main__':
print('master start.')
QueueManager.register('get_task_queue',callable= task_q)
QueueManager.register('get_result_queue',callable= result_q)
manager = QueueManager(address=('127.0.0.1',5000),authkey=b'abc')
manager.start()
task = manager.get_task_queue()
result = manager.get_result_queue()
for i in range(10):
n = random.randint(0,10000)
print('put task %d...' % n)
task.put(n)
print('try get results...')
for i in range(10):
r = result.get(timeout=100)
print('Result: %s' % r)
manager.shutdown()
print('master exit.')

#task_worker.py

import sys, time, queue
from multiprocessing.managers import BaseManager

class QueueManager(BaseManager):
pass

QueueManager.register('get_task_queue')
QueueManager.register('get_result_queue')

server_addr = '127.0.0.1'
print('Connect to server %s...' % server_addr)

m = QueueManager(address=(server_addr, 5000), authkey=b'abc')
m.connect()

task = m.get_task_queue()
result = m.get_result_queue()

for i in range(10):
try:
n = task.get(timeout = 1)
print('run task %d * %d' % (n, n))
r = '%d * %d = %d' % (n, n, n*n)
time.sleep(1)
result.put(r)
except Queue.Empty:
print('task queque is empty')

print('worker exit')

 

 

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版权声明：本文为CSDN博主「howlowl」的原创文章，遵循 CC 4.0 BY-SA 版权协议，转载请附上原文出处链接及本声明。
原文链接：https://blog.csdn.net/qq_33471057/article/details/78502256