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Home/ Questions/Q 9235259
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Editorial Team
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Editorial Team
Asked: June 18, 20262026-06-18T06:59:07+00:00 2026-06-18T06:59:07+00:00

I’d like to share several numpy arrays between different child processes with python’s multiprocessing

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I’d like to share several numpy arrays between different child processes with python’s multiprocessing module. I’d like the arrays to be separately lockable, and I’d like the number of arrays to be dynamically determined at runtime. Is this possible?

In this answer, J.F. Sebastian lays out a nice way to use python’s numpy arrays in shared memory while multiprocessing. The array is lockable, which is what I want. I would like to do something very similar, except with a variable number of shared arrays. The number of arrays would be determined at runtime. His example code is very clear and does almost exactly what I want, but I’m unclear how to declare a variable number of such arrays without giving each one of them a hard-coded name like shared_arr_1, shared_arr_2, et cetera. What’s the right way to do this?

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1 Answer

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  1. Editorial Team
    Editorial Team
    2026-06-18T06:59:09+00:00Added an answer on June 18, 2026 at 6:59 am

    Turns out this was easier than I thought! Following J.F. Sebastian’s encouragement, here’s my crack at an answer:

    import time
    import ctypes
    import logging
    import Queue
    import multiprocessing as mp
    import numpy as np
    
    info = mp.get_logger().info
    
    def main():
        logger = mp.log_to_stderr()
        logger.setLevel(logging.INFO)
    
        data_pipeline = Image_Data_Pipeline(
            num_data_buffers=5,
            buffer_shape=(60, 256, 512))
        start = time.clock()
        data_pipeline.load_buffers(data_pipeline.num_data_buffers)
        end = time.clock()
        data_pipeline.close()
        print "Elapsed time:", end-start
    
    
    class Image_Data_Pipeline:
        def __init__(self, num_data_buffers, buffer_shape):
            """
            Allocate a bunch of 16-bit buffers for image data
            """
            self.num_data_buffers = num_data_buffers
            self.buffer_shape = buffer_shape
            pix_per_buf = np.prod(buffer_shape)
            self.data_buffers = [mp.Array(ctypes.c_uint16, pix_per_buf)
                                 for b in range(num_data_buffers)]
            self.idle_data_buffers = range(num_data_buffers)
    
            """
            Launch the child processes that make up the pipeline
            """
            self.camera = Data_Pipeline_Process(
                target=child_process, name='Camera',
                data_buffers=self.data_buffers, buffer_shape=buffer_shape)
            self.display_prep = Data_Pipeline_Process(
                target=child_process, name='Display Prep',
                data_buffers=self.data_buffers, buffer_shape=buffer_shape,
                input_queue=self.camera.output_queue)
            self.file_saving = Data_Pipeline_Process(
                target=child_process, name='File Saving',
                data_buffers=self.data_buffers, buffer_shape=buffer_shape,
                input_queue=self.display_prep.output_queue)
            return None
    
        def load_buffers(self, N, timeout=0):
            """
            Feed the pipe!
            """
            for i in range(N):
                self.camera.input_queue.put(self.idle_data_buffers.pop())
    
            """
            Wait for the buffers to idle. Here would be a fine place to
            feed them back to the pipeline, too.
            """
            while True:
                try:
                    self.idle_data_buffers.append(
                        self.file_saving.output_queue.get_nowait())
                    info("Buffer %i idle"%(self.idle_data_buffers[-1]))
                except Queue.Empty:
                    time.sleep(0.01)
                if len(self.idle_data_buffers) >= self.num_data_buffers:
                    break
            return None
    
        def close(self):
            self.camera.input_queue.put(None)
            self.display_prep.input_queue.put(None)
            self.file_saving.input_queue.put(None)
            self.camera.child.join()
            self.display_prep.child.join()
            self.file_saving.child.join()
    
    
    class Data_Pipeline_Process:
        def __init__(
            self,
            target,
            name,
            data_buffers,
            buffer_shape,
            input_queue=None,
            output_queue=None,
            ):
            if input_queue is None:
                self.input_queue = mp.Queue()
            else:
                self.input_queue = input_queue
    
            if output_queue is None:
                self.output_queue = mp.Queue()
            else:
                self.output_queue = output_queue
    
            self.command_pipe = mp.Pipe() #For later, we'll send instrument commands
    
            self.child = mp.Process(
                target=target,
                args=(name, data_buffers, buffer_shape,
                      self.input_queue, self.output_queue, self.command_pipe),
                name=name)
            self.child.start()
            return None
    
    def child_process(
        name,
        data_buffers,
        buffer_shape,
        input_queue,
        output_queue,
        command_pipe):
        if name == 'Display Prep':
            display_buffer = np.empty(buffer_shape, dtype=np.uint16)
        while True:
            try:
                process_me = input_queue.get_nowait()
            except Queue.Empty:
                time.sleep(0.01)
                continue
            if process_me is None:
                break #We're done
            else:
                info("start buffer %i"%(process_me))
                with data_buffers[process_me].get_lock():
                    a = np.frombuffer(data_buffers[process_me].get_obj(),
                                      dtype=np.uint16)
                    if name == 'Camera':
                        """
                        Fill the buffer with data (eventually, from the
                        camera, dummy data for now)
                        """
                        a.fill(1)
                    elif name == 'Display Prep':
                        """
                        Process the 16-bit image into a display-ready
                        8-bit image. Fow now, just copy the data to a
                        similar buffer.
                        """
                        display_buffer[:] = a.reshape(buffer_shape)
                    elif name == 'File Saving':
                        """
                        Save the data to disk.
                        """
                        a.tofile('out.raw')
                info("end buffer %i"%(process_me))
                output_queue.put(process_me)
        return None
    
    if __name__ == '__main__':
        main()
    

    Background: This is the skeleton of a data-acquisition pipeline. I want to acquire data at a very high rate, process it for on-screen display, and save it to disk. I don’t ever want display rate or disk rate to limit acquisition, which is why I think using separate child processes in individual processing loops is appropriate.

    Here’s typical output of the dummy program:

    C:\code\instrument_control>c:\Python27\python.exe test.py
    [INFO/MainProcess] allocating a new mmap of length 15728640
    [INFO/MainProcess] allocating a new mmap of length 15728640
    [INFO/MainProcess] allocating a new mmap of length 15728640
    [INFO/MainProcess] allocating a new mmap of length 15728640
    [INFO/MainProcess] allocating a new mmap of length 15728640
    [[INFO/Camera] child process calling self.run()
    INFO/Display Prep] child process calling self.run()
    [INFO/Camera] start buffer 4
    [INFO/File Saving] child process calling self.run()
    [INFO/Camera] end buffer 4
    [INFO/Camera] start buffer 3
    [INFO/Camera] end buffer 3
    [INFO/Camera] start buffer 2
    [INFO/Display Prep] start buffer 4
    [INFO/Camera] end buffer 2
    [INFO/Camera] start buffer 1
    [INFO/Camera] end buffer 1
    [INFO/Camera] start buffer 0
    [INFO/Camera] end buffer 0
    [INFO/Display Prep] end buffer 4
    [INFO/Display Prep] start buffer 3
    [INFO/File Saving] start buffer 4
    [INFO/Display Prep] end buffer 3
    [INFO/Display Prep] start buffer 2
    [INFO/File Saving] end buffer 4
    [INFO/File Saving] start buffer 3
    [INFO/MainProcess] Buffer 4 idle
    [INFO/Display Prep] end buffer 2
    [INFO/Display Prep] start buffer 1
    [INFO/File Saving] end buffer 3
    [INFO/File Saving] start buffer 2
    [INFO/MainProcess] Buffer 3 idle
    [INFO/Display Prep] end buffer 1
    [INFO/Display Prep] start buffer 0
    [INFO/File Saving] end buffer 2
    [INFO/File Saving] start buffer 1
    [[INFO/MainProcess] Buffer 2 idle
    INFO/Display Prep] end buffer 0
    [INFO/File Saving] end buffer 1
    [INFO/File Saving] start buffer 0
    [INFO/MainProcess] Buffer 1 idle
    [INFO/File Saving] end buffer 0
    [INFO/MainProcess] Buffer 0 idle
    [INFO/Camera] process shutting down
    [INFO/Camera] process exiting with exitcode 0
    [INFO/Display Prep] process shutting down
    [INFO/File Saving] process shutting down
    [INFO/Display Prep] process exiting with exitcode 0
    [INFO/File Saving] process exiting with exitcode 0
    Elapsed time: 0.263240348548
    [INFO/MainProcess] process shutting down
    
    C:\code\instrument_control>
    

    It seems to do what I want: the data gets processed for display and saved to disk without interfering with the acquisition rate.

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