python进程间共享数据_使用多处理的Python进程之间共享数据的问题

比眉伴天荒 2022-11-19 09:49 182阅读 0赞

以下是一个建议的解决方案，假设您希望：控制工人寿命的集中管理者/主要过程

工作进程独立完成某项工作，然后将结果报告给经理和其他进程

在我展示之前，我想说的是，一般情况下，除非您是CPU专用的，否则\{\}实际上并不适合，主要是因为增加了复杂性，而且您最好使用不同的高级异步框架。另外，你应该使用python3，它好得多！在

也就是说，^\{\}，使用multiprocessing可以很容易地实现这一点。我已经在Python3中完成了这项工作，但我不认为任何东西在Python2中不应该“只工作”，但我还没有检查过。在from ctypes import c\_bool

from multiprocessing import Manager, Process, Array, Value

from pprint import pprint

from time import sleep, time

class Agent(Process):

def \_\_init\_\_(self, name, shared\_dictionary, delay=0.5):

"""My take on your Agent.

Key difference is that I've commonized the run-loop and used

a shared value to signal when to stop, to demonstrate it.

"""

super(Agent, self).\_\_init\_\_()

self.name = name

\# This is going to be how we communicate between processes.

self.shared\_dictionary = shared\_dictionary

\# Create a silo for us to use.

shared\_dictionary\[name\] = \[\]

self.should\_stop = Value(c\_bool, False)

\# Primarily for testing purposes, and for simulating

\# slower agents.

self.delay = delay

def get\_next\_results(self):

\# In the real world I'd use abc.ABCMeta as the metaclass to do

\# this properly.

raise RuntimeError('Subclasses must implement this')

def run(self):

ii = 0

while not self.should\_stop.value:

ii += 1

\# debugging / monitoring

print('%s %s run loop execution %d' % (

type(self).\_\_name\_\_, self.name, ii))

next\_results = self.get\_next\_results()

\# Add the results, along with a timestamp.

self.shared\_dictionary\[self.name\] += \[(time(), next\_results)\]

sleep(self.delay)

def stop(self):

self.should\_stop.value = True

print('%s %s stopped' % (type(self).\_\_name\_\_, self.name))

class HVACAgent(Agent):

def get\_next\_results(self):

\# This is where you do your work, but for the sake of

\# the example just return a constant dictionary.

return \{'temperature': 5, 'pressure': 7, 'humidity': 9\}

class DumbReadingAgent(Agent):

"""A dumb agent to demonstrate workers reading other worker values."""

def get\_next\_results(self):

\# get hvac 1 results:

hvac1\_results = self.shared\_dictionary.get('hvac 1')

if hvac1\_results is None:

return None

return hvac1\_results\[-1\]\[1\]\['temperature'\]

\# Script starts.

results = \{\}

\# The "with" ensures we terminate the manager at the end.

with Manager() as manager:

\# the manager is a subprocess in its own right. We can ask

\# it to manage a dictionary (or other python types) for us

\# to be shared among the other children.

shared\_info = manager.dict()

hvac\_agent1 = HVACAgent('hvac 1', shared\_info)

hvac\_agent2 = HVACAgent('hvac 2', shared\_info, delay=0.1)

dumb\_agent = DumbReadingAgent('dumb hvac1 reader', shared\_info)

agents = (hvac\_agent1, hvac\_agent2, dumb\_agent)

list(map(lambda a: a.start(), agents))

sleep(1)

list(map(lambda a: a.stop(), agents))

list(map(lambda a: a.join(), agents))

\# Not quite sure what happens to the shared dictionary after

\# the manager dies, so for safety make a local copy.

results = dict(shared\_info)

pprint(results)

python进程间共享数据_使用多处理的Python进程之间共享数据的问题

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