python sharedctypes 多进程性能测试

经过测试，没有比numpy快。

      # !/usr/bin/env python
      # -*- coding: utf-8 -*-
      import ctypes
      import multiprocessing
      import random
      import time
      import os
      from multiprocessing import sharedctypes
      import numpy as np
      import cv2
      def make_array(shape=(1,), dtype=np.uint8, shared=False, fill_val=None):
       start = time.time()
       np_type_to_ctype = {np.float32: ctypes.c_float,
       np.float64: ctypes.c_double,
       np.bool: ctypes.c_bool,
       np.dtype('uint8'): ctypes.c_ubyte,
       np.uint8: ctypes.c_ubyte,
       np.uint64: ctypes.c_ulonglong}
      if not shared:
       np_arr = np.empty(shape, dtype=dtype)
      else:
       numel = int(np.prod(shape))
       arr_ctypes = sharedctypes.RawArray(np_type_to_ctype[dtype], numel)
       np_arr = np.frombuffer(arr_ctypes, dtype=dtype, count=num
  
 

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原文链接：blog.csdn.net/jacke121/article/details/88930459