多处理功能不写入文件或打印

Question

我正在使用 Raspberry Pi (3 B+) 制作数据收集设备，我正在尝试生成一个进程来记录传入的数据并将其写入文件。我有一个写作函数，当我直接调用它时可以正常工作。然而，当我使用多进程方法调用它时，似乎什么也没发生。我可以在 Linux 的任务监视器中看到该进程确实被生成但没有文件被写入，并且当我尝试将标志传递给它以关闭它时它不起作用，这意味着我最终终止了该进程而什么也没有似乎已经发生了。我已经从各个方面解决了这个问题，但看不出我做错了什么；还有其他人吗？如果相关，这些是父类中的函数，其中一个函数旨在生成另一个作为线程的函数。我正在使用的代码：from datetime import datetime, timedeltaimport csvfrom drivers.IMU_SEN0 import IMU_SEN0import multiprocessing, osclass IMU_data_logger:    _output_filename = ''    _csv_headers = []    _accelerometer_headers = ['Accelerometer X','Accelerometer    Y','Accelerometer Z']    _gyroscope_headers = ['Gyroscope X','Gyroscope Y','Gyroscope Z']    _magnetometer_headers = ['Bearing']    _log_accelerometer = False    _log_gyroscope= False    _log_magnetometer = False    IMU = None    _writer=[]    _run_underway = False    _process=[]    _stop_value = 0def __init__(self,output_filename='/home/pi/blah.csv',log_accelerometer = True,log_gyroscope= True,log_magnetometer = True):    """data logging device    NOTE! Multiple instances of this class should not use the same IMU devices simultaneously!"""            self._output_filename = output_filename    self._log_accelerometer = log_accelerometer    self._log_gyroscope = log_gyroscope    self._log_magnetometer = log_magnetometerdef __del__(self):    # TODO Update this    if self._run_underway: # If there's still a run underway, end it first        self.end_recording()def _set_up(self):            self.IMU = IMU_SEN0(self._log_accelerometer,self._log_gyroscope,self._log_magnetometer)    self._set_up_headers()答案：对于在这里跟进的任何人，事实证明问题在于我使用了 VS Code 调试器，该调试器显然不适用于多处理，并且以某种方式阻止了生成的进程的成功。

Answer 1

我可以在您的代码中看到一些错误：

首先 stop_value == 0 不会像 multiprocess.Value('i', 0) != 0 那样工作，将该行更改为

while stop_value.value == 0

其次，你永远不会更新 previous_read_time 所以它会尽可能快地写入读数，你会很快用完磁盘

第三，尝试使用 time.sleep() 你正在做的事情被称为忙循环，它很糟糕，它不必要地浪费了 CPU 周期。

四，以 self._stop_value = 1 终止可能不会起作用，必须有其他方法来设置该值，也许 self._stop_value.value = 1。

好吧，这是基于您提供的代码的示例代码，该代码工作正常：

import csv

import multiprocessing

import time

from datetime import datetime, timedelta

from random import randint

class IMU(object):

    @staticmethod

    def read_accelerometer_values():

        return dict(x=randint(0, 100), y=randint(0, 100), z=randint(0, 10))

class Foo(object):

    def __init__(self, output_filename):

        self._output_filename = output_filename

        self._csv_headers = ['xxxx','y','z']

        self._log_accelerometer = True

        self.IMU = IMU()

    def _record_data(self, frequency, stop_value):

        #self._set_up()  # Run setup functions for the data collection device and store it in the self.IMU variable

        """Record data function, which takes a recording frequency, in herz, as an input"""

        previous_read_time = datetime.now() - timedelta(1, 0, 0)

        self._run_underway = True  # Note that a run is now going

        Period = 1 / frequency  # Period, in seconds, of a recording based on the input frequency

        print("Writing output data to", self._output_filename)

        with open(self._output_filename, 'w', newline='') as outcsv:

            self._writer = csv.writer(outcsv)

            self._writer.writerow(self._csv_headers)  # Write headers to file

            while stop_value.value == 0:  # While a run continues

                if datetime.now() - previous_read_time >= timedelta(0, 1,

                                                                    0):  # If we've waited a period, collect the data; otherwise keep looping

                    print("run underway value", self._run_underway)

                if datetime.now() - previous_read_time >= timedelta(0, Period,

                                                                    0):  # If we've waited a period, collect the data; otherwise keep looping

                    next_row = []

                    if self._log_accelerometer:

                        # Get values in m/s^2

                        axes = self.IMU.read_accelerometer_values()

                        next_row += [axes['x'], axes['y'], axes['z']]

                    previous_read_time = datetime.now()

                    self._writer.writerow(next_row)

            # Close the csv when done

            outcsv.close()

    def start_recording(self, frequency_in_hz):

        # Create recording process

        self._stop_value = multiprocessing.Value('i', 0)

        self._process = multiprocessing.Process(target=self._record_data, args=(frequency_in_hz, self._stop_value))

        # Start recording process

        self._process.start()

        print(datetime.now().strftime("%H:%M:%S.%f"), "Data logging process spawned")

        print("ID of data logging process: {}".format(self._process.pid))

    def end_recording(self, terminate_wait=2):

        """Function to end the recording multithread that's been spawned.

        Args: terminate_wait: This is the time, in seconds, to wait after attempting to shut down the process before terminating it."""

        # Get process id

        id = self._process.pid

        # Set stop event for process

        self._stop_value.value = 1

        self._process.join(terminate_wait)  # Wait two seconds for the process to terminate

        if self._process.is_alive():  # If it's still alive after waiting

            self._process.terminate()

            print(datetime.now().strftime("%H:%M:%S.%f"), "Process", id, "needed to be terminated.")

        else:

            print(datetime.now().strftime("%H:%M:%S.%f"), "Process", id, "successfully ended itself.")

if __name__ == '__main__':

    foo = Foo('/tmp/foometer.csv')

    foo.start_recording(20)

    time.sleep(5)

    print('Ending recording')

    foo.end_recording()