Hi I'm trying to write a module that lets me read and send data via pyserial
. I have to be able to read the data in parallel to my main script. With the help of a stackoverflow user, I have a basic and working skeleton of the program, but when I tried adding a class I created that uses pyserial (handles finding port, speed, etc) found here I get the following error:
File "<ipython-input-1-830fa23bc600>", line 1, in <module>
runfile('C:.../pythonInterface1/Main.py', wdir='C:/Users/Daniel.000/Desktop/Daniel/Python/pythonInterface1')
File "C:...\Anaconda3\lib\site-packages\spyder_kernels\customize\spydercustomize.py", line 827, in runfile
execfile(filename, namespace)
File "C:...\Anaconda3\lib\site-packages\spyder_kernels\customize\spydercustomize.py", line 110, in execfile
exec(compile(f.read(), filename, 'exec'), namespace)
File "C:/Users/Daniel.000/Desktop/Daniel/Python/pythonInterface1/Main.py", line 39, in <module>
p.start()
File "C:...\Anaconda3\lib\multiprocessing\process.py", line 112, in start
self._popen = self._Popen(self)
File "C:...\Anaconda3\lib\multiprocessing\context.py", line 223, in _Popen
return _default_context.get_context().Process._Popen(process_obj)
File "C:...\Anaconda3\lib\multiprocessing\context.py", line 322, in _Popen
return Popen(process_obj)
File "C:...\Anaconda3\lib\multiprocessing\popen_spawn_win32.py", line 89, in __init__
reduction.dump(process_obj, to_child)
File "C:...\Anaconda3\lib\multiprocessing\reduction.py", line 60, in dump
ForkingPickler(file, protocol).dump(obj)
ValueError: ctypes objects containing pointers cannot be pickled
This is the code I am using to call the class in SerialConnection.py
import multiprocessing
from time import sleep
from operator import methodcaller
from SerialConnection import SerialConnection as SC
class Spawn:
def __init__(self, _number, _max):
self._number = _number
self._max = _max
# Don't call update here
def request(self, x):
print("{} was requested.".format(x))
def update(self):
while True:
print("Spawned {} of {}".format(self._number, self._max))
sleep(2)
if __name__ == '__main__':
'''
spawn = Spawn(1, 1) # Create the object as normal
p = multiprocessing.Process(target=methodcaller("update"), args=(spawn,)) # Run the loop in the process
p.start()
while True:
sleep(1.5)
spawn.request(2) # Now you can reference the "spawn"
'''
device = SC()
print(device.Port)
print(device.Baud)
print(device.ID)
print(device.Error)
print(device.EMsg)
p = multiprocessing.Process(target=methodcaller("ReadData"), args=(device,)) # Run the loop in the process
p.start()
while True:
sleep(1.5)
device.SendData('0003')
What am I doing wrong for this class to be giving me problems? Is there some form of restriction to use pyserial
and multiprocessing together? I know it can be done but I don't understand how...
here is the traceback i get from python
Traceback (most recent call last): File "C:...\Python\pythonInterface1\Main.py", line 45, in <module>
p.start()
File "C:...\AppData\Local\Programs\Python\Python36-32\lib\multiprocessing\process.py", line 105, in start
self._popen = self._Popen(self)
File "C:...\AppData\Local\Programs\Python\Python36-32\lib\multiprocessing\context.py", line 223, in _Popen
return _default_context.get_context().Process._Popen(process_obj)
File "C:...\AppData\Local\Programs\Python\Python36-32\lib\multiprocessing\context.py", line 322, in _Popen
return Popen(process_obj)
File "C:...\AppData\Local\Programs\Python\Python36-32\lib\multiprocessing\popen_spawn_win32.py", line 65, in __init__
reduction.dump(process_obj, to_child)
File "C:...\AppData\Local\Programs\Python\Python36-32\lib\multiprocessing\reduction.py", line 60, in dump
ForkingPickler(file, protocol).dump(obj) ValueError: ctypes objects containing pointers cannot be pickled
You are trying to pass a SerialConnection
instance to another process as an argument. For that python has first to serialize (pickle) the object, and it is not possible for SerialConnection
objects.
As said in Rob Streeting's answer, a possible solution would be to allow the SerialConnection
object to be copied to the other process' memory using the fork that occurs when multiprocessing.Process.start
is invoked, but this will not work on Windows as it does not use fork.
A simpler, cross-platform and more efficient way to achieve parallelism in your code would be to use a thread instead of a process. The changes to your code are minimal:
import threading
p = threading.Thread(target=methodcaller("ReadData"), args=(device,))
I think the problem is due to something inside device
being unpicklable (i.e., not serializable by python). Take a look at this page to see if you can see any rules that may be broken by something in your device object.
So why does device
need to be picklable at all?
When a multiprocessing.Process is started, it uses fork() at the operating system level (unless otherwise specified) to create the new process. What this means is that the whole context of the parent process is "copied" over to the child. This does not require pickling, as it's done at the operating system level.
(Note: On unix at least, this "copy" is actually a pretty cheap operation because it used a feature called "copy-on-write". This means that both parent and child processes actually read from the same memory until one or the other modifies it, at which point the original state is copied over to the child process.)
However, the arguments of the function that you want the process to take care of do have to be pickled, because they are not part of the main process's context. So, that includes your device
variable.
I think you might be able to resolve your issue by allowing device
to be copied as part of the fork operation rather than passing it in as a variable. To do this though, you'll need a wrapper function around the operation you want your process to do, in this case methodcaller("ReadData")
. Something like this:
if __name__ == "__main__":
device = SC()
def call_read_data():
device.ReadData()
...
p = multiprocessing.Process(target=call_read_data) # Run the loop in the process
p.start()
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