Python ctypes结构体深度复制指南

import ctypes as ct

class Group(ct.Structure):
    _fields_ = (('ChSize', ct.c_uint32 * 9),          # 9个通道的尺寸数组
                ('DataChannel', ct.POINTER(ct.c_float) * 9), # 9个指向浮点数数组的指针
                ('TriggerTimeLag', ct.c_uint32),      # 触发时间延迟
                ('StartIndexCell', ct.c_uint16))     # 起始索引单元

    def __repr__(self):
        """
        为Group对象提供一个可读的字符串表示，便于调试。
        它会显示所有字段的值，并特别地展示DataChannel指针所指向的数据内容。
        """
        s = f'Group(ChSize={self.ChSize[:]}, TriggerTimeLag={self.TriggerTimeLag}, StartIndexCell={self.StartIndexCell})\n'
        for i in range(9):
            # 仅显示ChSize指定长度的数据
            s += f'  DataChannel[{i}] = {self.DataChannel[i][:self.ChSize[i]]}\n'
        return s

    def deepcopy(self):
        """
        实现Group结构体的深度复制。
        """
        # 1. 创建结构体本身的浅拷贝
        # from_buffer_copy 会复制结构体所有直接包含的值类型字段和固定大小数组。
        # 此时，copy.DataChannel 中的指针仍然指向原始 group 的数据。
        copy = Group.from_buffer_copy(self)

        # 2. 遍历指针字段并进行深度复制
        for i, (size, channel) in enumerate(zip(self.ChSize, self.DataChannel)):
            if channel: # 确保指针不为空
                # 为当前通道的数据创建一个新的C数组缓冲区
                # (*channel[:size]) 将原始指针指向的数据解引用并复制到新数组中
                data = (ct.c_float * size)(*channel[:size])

                # 将新创建的缓冲区转换为POINTER类型，并存储到副本的DataChannel字段中
                # 这确保了副本的指针指向独立的新内存区域
                copy.DataChannel[i] = ct.cast(data, ct.POINTER(ct.c_float))
            else:
                copy.DataChannel[i] = None # 如果原始指针为空，副本也设置为空

        return copy

# 1. 创建、初始化并显示原始Group对象
group = Group()
group.ChSize[:] = [1, 2, 3, 4, 5, 6, 7, 8, 9] # 设置每个通道的数据长度

for i, size in enumerate(group.ChSize):
    # 为每个通道动态分配数据并填充
    data = (ct.c_float * size)(*[1.5 * n for n in range(size)])
    group.DataChannel[i] = ct.cast(data, ct.POINTER(ct.c_float))

group.TriggerTimeLag = 123
group.StartIndexCell = 456
print("--- 原始 Group 对象 ---")
print(group)

# 2. 进行深度复制
copy = group.deepcopy()

# 3. 修改原始Group对象的通道数据，将其全部清零
# 注意：这里不仅将ChSize设为0，还将DataChannel指针设为None，
# 模拟原始数据被释放或修改的情况。
group.ChSize[:] = [0] * 9
group.DataChannel[:] = [None] * 9

print("\n--- 修改后的原始 Group 对象 ---")
print(group)

# 4. 显示副本Group对象，验证其数据是否未受原始对象修改的影响
print("\n--- 深度复制的副本 Group 对象 ---")
print(copy)

--- 原始 Group 对象 ---
Group(ChSize=[1, 2, 3, 4, 5, 6, 7, 8, 9], TriggerTimeLag=123, StartIndexCell=456)
  DataChannel[0] = [0.0]
  DataChannel[1] = [0.0, 1.5]
  DataChannel[2] = [0.0, 1.5, 3.0]
  DataChannel[3] = [0.0, 1.5, 3.0, 4.5]
  DataChannel[4] = [0.0, 1.5, 3.0, 4.5, 6.0]
  DataChannel[5] = [0.0, 1.5, 3.0, 4.5, 6.0, 7.5]
  DataChannel[6] = [0.0, 1.5, 3.0, 4.5, 6.0, 7.5, 9.0]
  DataChannel[7] = [0.0, 1.5, 3.0, 4.5, 6.0, 7.5, 9.0, 10.5]
  DataChannel[8] = [0.0, 1.5, 3.0, 4.5, 6.0, 7.5, 9.0, 10.5, 12.0]

--- 修改后的原始 Group 对象 ---
Group(ChSize=[0, 0, 0, 0, 0, 0, 0, 0, 0], TriggerTimeLag=123, StartIndexCell=456)
  DataChannel[0] = []
  DataChannel[1] = []
  DataChannel[2] = []
  DataChannel[3] = []
  DataChannel[4] = []
  DataChannel[5] = []
  DataChannel[6] = []
  DataChannel[7] = []
  DataChannel[8] = []

--- 深度复制的副本 Group 对象 ---
Group(ChSize=[1, 2, 3, 4, 5, 6, 7, 8, 9], TriggerTimeLag=123, StartIndexCell=456)
  DataChannel[0] = [0.0]
  DataChannel[1] = [0.0, 1.5]
  DataChannel[2] = [0.0, 1.5, 3.0]
  DataChannel[3] = [0.0, 1.5, 3.0, 4.5]
  DataChannel[4] = [0.0, 1.5, 3.0, 4.5, 6.0]
  DataChannel[5] = [0.0, 1.5, 3.0, 4.5, 6.0, 7.5]
  DataChannel[6] = [0.0, 1.5, 3.0, 4.5, 6.0, 7.5, 9.0]
  DataChannel[7] = [0.0, 1.5, 3.0, 4.5, 6.0, 7.5, 9.0, 10.5]
  DataChannel[8] = [0.0, 1.5, 3.0, 4.5, 6.0, 7.5, 9.0, 10.5, 12.0]