缓冲协议
********

在 Python 中可使用一些对象来包装对底层内存数组或称 *缓冲* 的访问。此类
对象包括内置的 "bytes" 和 "bytearray" 以及一些如 "array.array" 这样的
扩展类型。第三方库也可能会为了特殊的目的而定义它们自己的类型，例如用于
图像处理和数值分析等。

虽然这些类型中的每一种都有自己的语义，但它们具有由可能较大的内存缓冲区
支持的共同特征。 在某些情况下，希望直接访问该缓冲区而无需中间复制。

Python 以 缓冲协议 的形式在 C 层级上提供这样的功能。 此协议包括两个方
面:

* 在生产者这一方面，该类型的协议可以导出一个“缓冲区接口”，允许公开它的
  底层缓冲区信息。该接口的描述信息在 Buffer Object Structures 一节中；

* 在消费者一侧，有几种方法可用于获得指向对象的原始底层数据的指针（例如
  一个方法的形参）。

一些简单的对象例如 "bytes" 和 "bytearray" 会以面向字节的形式公开它们的
底层缓冲区。 也可能会用其他形式；例如 "array.array" 所公开的元素可以是
多字节值。

缓冲区接口的消费者的一个例子是文件对象的 "write()" 方法：任何可以输出
为一系列字节流的对象可以被写入文件。然而 "write()" 方法只需要对于传入
对象的只读权限，其他的方法，如 "readinto()" 需要参数内容的写入权限。缓
冲区接口使得对象可以选择性地允许或拒绝读写或只读缓冲区的导出。

对于缓冲接口的消费者而言，有两种方式来获取一个目的对象的缓冲。

* 使用正确的参数来调用 "PyObject_GetBuffer()"  函数

* 调用 "PyArg_ParseTuple()" (或其同级对象之一) 并传入 "y*", "w*" or
  "s*" 格式代码 中的一个。

在这两种情况下，当不再需要缓冲区时必须调用 "PyBuffer_Release()" 。如果
此操作失败，可能会导致各种问题，例如资源泄漏。


缓冲区结构
==========

缓冲区结构(或者简单地称为“buffers”)对于将二进制数据从另一个对象公开给
Python程序员非常有用。它们还可以用作零拷贝切片机制。使用它们引用内存块
的能力，可以很容易地将任何数据公开给Python程序员。内存可以是C扩展中的
一个大的常量数组，也可以是在传递到操作系统库之前用于操作的原始内存块，
或者可以用来传递本机内存格式的结构化数据。

与 Python 解释器公开的大多部数据类型不同，缓冲区不是 "PyObject" 指针而
是简单的 C 结构。 这使得它们可以非常简单地创建和复制。 当需要为缓冲区
加上泛型包装器时，可以创建一个 内存视图 对象。

有关如何编写并导出对象的简短说明，请参阅 缓冲区对象结构。 要获取缓冲区
对象，请参阅 "PyObject_GetBuffer()"。

Py_buffer

   void *buf

      指向由缓冲区字段描述的逻辑结构开始的指针。 这可以是导出程序底层
      物理内存块中的任何位置。 例如，使用负的 "strides" 值可能指向内存
      块的末尾。

      对于 *contiguous* ，‘邻接’数组，值指向内存块的开头。

   void *obj

      A new reference to the exporting object. The reference is owned
      by the consumer and automatically decremented and set to *NULL*
      by "PyBuffer_Release()". The field is the equivalent of the
      return value of any standard C-API function.

      As a special case, for *temporary* buffers that are wrapped by
      "PyMemoryView_FromBuffer()" or "PyBuffer_FillInfo()" this field
      is *NULL*. In general, exporting objects MUST NOT use this
      scheme.

   Py_ssize_t len

      "product(shape) * itemsize"。对于连续数组，这是基础内存块的长度
      。对于非连续数组，如果逻辑结构复制到连续表示形式，则该长度将具有
      该长度。

      仅当缓冲区是通过保证连续性的请求获取时，才访问 "((char *)buf)[0]
      up to ((char *)buf)[len-1]" 时才有效。在大多数情况下，此类请求将
      为 "PyBUF_SIMPLE" 或 "PyBUF_WRITABLE"。

   int readonly

      缓冲区是否为只读的指示器。此字段由 "PyBUF_WRITABLE" 标志控制。

   Py_ssize_t itemsize

      Item size in bytes of a single element. Same as the value of
      "struct.calcsize()" called on non-NULL "format" values.

      Important exception: If a consumer requests a buffer without the
      "PyBUF_FORMAT" flag, "format" will be set to  *NULL*,  but
      "itemsize" still has the value for the original format.

      如果 "shape" 存在，则相等的 "product(shape) * itemsize == len"
      仍然存在，使用者可以使用 "itemsize" 来导航缓冲区。

      If "shape" is *NULL* as a result of a "PyBUF_SIMPLE" or a
      "PyBUF_WRITABLE" request, the consumer must disregard "itemsize"
      and assume "itemsize == 1".

   const char *format

      A *NUL* terminated string in "struct" module style syntax
      describing the contents of a single item. If this is *NULL*,
      ""B"" (unsigned bytes) is assumed.

      此字段由 "PyBUF_FORMAT" 标志控制。

   int ndim

      The number of dimensions the memory represents as an
      n-dimensional array. If it is "0", "buf" points to a single item
      representing a scalar. In this case, "shape", "strides" and
      "suboffsets" MUST be *NULL*.

      宏 "PyBUF_MAX_NDIM" 将最大维度数限制为 64。 导出程序必须遵守这个
      限制，多维缓冲区的使用者应该能够处理最多 "PyBUF_MAX_NDIM" 维度。

   Py_ssize_t *shape

      一个长度为 "Py_ssize_t" 的数组 "ndim" 表示作为 n 维数组的内存形
      状。 请注意，"shape[0] * ... * shape[ndim-1] * itemsize" 必须等
      于 "len"。

      Shape 形状数组中的值被限定在 "shape[n] >= 0" 。 "shape[n] == 0"
      这一情形需要特别注意。更多信息请参阅 complex arrays 。

      shape数组对于使用者来说是只读的。

   Py_ssize_t *strides

      一个长度为 "Py_ssize_t" 的数组 "ndim" 给出要跳过的字节数以获取每
      个尺寸中的新元素。

      Stride 步幅数组中的值可以为任何整数。对于常规数组，步幅通常为正
      数，但是使用者必须能够处理 "strides[n] <= 0" 的情况。更多信息请
      参阅 complex arrays 。

      strides数组对用户来说是只读的。

   Py_ssize_t *suboffsets

      An array of "Py_ssize_t" of length "ndim". If "suboffsets[n] >=
      0", the values stored along the nth dimension are pointers and
      the suboffset value dictates how many bytes to add to each
      pointer after de-referencing. A suboffset value that is negative
      indicates that no de-referencing should occur (striding in a
      contiguous memory block).

      If all suboffsets are negative (i.e. no de-referencing is
      needed), then this field must be NULL (the default value).

      Python Imaging Library (PIL) 中使用了这种数组的表达方式。请参阅
      complex arrays 来了解如何从这样一个数组中访问元素。

      suboffsets 数组对于使用者来说是只读的。

   void *internal

      This is for use internally by the exporting object. For example,
      this might be re-cast as an integer by the exporter and used to
      store flags about whether or not the shape, strides, and
      suboffsets arrays must be freed when the buffer is released. The
      consumer MUST NOT alter this value.


缓冲区请求的类型
================

Buffers are usually obtained by sending a buffer request to an
exporting object via "PyObject_GetBuffer()". Since the complexity of
the logical structure of the memory can vary drastically, the consumer
uses the *flags* argument to specify the exact buffer type it can
handle.

所有 "Py_buffer" 字段均由请求类型明确定义。


与请求无关的字段
----------------

以下字段不会被 *flags* 影响，并且必须总是用正确的值填充："obj", "buf"
，"len"，"itemsize"，"ndim"。


只读，格式
----------

   PyBUF_WRITABLE

      Controls the "readonly" field. If set, the exporter MUST provide
      a writable buffer or else report failure. Otherwise, the
      exporter MAY provide either a read-only or writable buffer, but
      the choice MUST be consistent for all consumers.

   PyBUF_FORMAT

      Controls the "format" field. If set, this field MUST be filled
      in correctly. Otherwise, this field MUST be *NULL*.

"PyBUF_WRITABLE" can be |'d to any of the flags in the next section.
Since "PyBUF_SIMPLE" is defined as 0, "PyBUF_WRITABLE" can be used as
a stand-alone flag to request a simple writable buffer.

"PyBUF_FORMAT" 可以被设为除了 "PyBUF_SIMPLE" 之外的任何标志。 后者已经
按暗示了``B``(无符号字节串)格式。


形状，步幅，子偏移量
--------------------

控制内存逻辑结构的标志按照复杂度的递减顺序列出。注意，每个标志包含它下
面的所有标志。

+-------------------------------+---------+-----------+--------------+
| 请求                          | 形状    | 步幅      | 子偏移量     |
|===============================|=========|===========|==============|
| PyBUF_INDIRECT                | 是      | 是        | 如果需要的话 |
+-------------------------------+---------+-----------+--------------+
| PyBUF_STRIDES                 | 是      | 是        | NULL         |
+-------------------------------+---------+-----------+--------------+
| PyBUF_ND                      | 是      | NULL      | NULL         |
+-------------------------------+---------+-----------+--------------+
| PyBUF_SIMPLE                  | NULL    | NULL      | NULL         |
+-------------------------------+---------+-----------+--------------+


连续性的请求
------------

可以显式地请求C 或 Fortran *连续* ，不管有没有步幅信息。若没有步幅信息
，则缓冲区必须是 C-连续的。

+-------------------------------------+---------+-----------+--------------+----------+
| 请求                                | 形状    | 步幅      | 子偏移量     | 邻接     |
|=====================================|=========|===========|==============|==========|
| PyBUF_C_CONTIGUOUS                  | 是      | 是        | NULL         | C        |
+-------------------------------------+---------+-----------+--------------+----------+
| PyBUF_F_CONTIGUOUS                  | 是      | 是        | NULL         | F        |
+-------------------------------------+---------+-----------+--------------+----------+
| PyBUF_ANY_CONTIGUOUS                | 是      | 是        | NULL         | C 或 F   |
+-------------------------------------+---------+-----------+--------------+----------+
| PyBUF_ND                            | 是      | NULL      | NULL         | C        |
+-------------------------------------+---------+-----------+--------------+----------+


复合请求
--------

所有可能的请求都由上一节中某些标志的组合完全定义。为方便起见，缓冲区协
议提供常用的组合作为单个标志。

In the following table *U* stands for undefined contiguity. The
consumer would have to call "PyBuffer_IsContiguous()" to determine
contiguity.

+---------------------------------+---------+-----------+--------------+----------+------------+----------+
| 请求                            | 形状    | 步幅      | 子偏移量     | 邻接     | 只读       | 格式     |
|=================================|=========|===========|==============|==========|============|==========|
| PyBUF_FULL                      | 是      | 是        | 如果需要的话 | U        | 0          | 是       |
+---------------------------------+---------+-----------+--------------+----------+------------+----------+
| PyBUF_FULL_RO                   | 是      | 是        | 如果需要的话 | U        | 1 或 0     | 是       |
+---------------------------------+---------+-----------+--------------+----------+------------+----------+
| PyBUF_RECORDS                   | 是      | 是        | NULL         | U        | 0          | 是       |
+---------------------------------+---------+-----------+--------------+----------+------------+----------+
| PyBUF_RECORDS_RO                | 是      | 是        | NULL         | U        | 1 或 0     | 是       |
+---------------------------------+---------+-----------+--------------+----------+------------+----------+
| PyBUF_STRIDED                   | 是      | 是        | NULL         | U        | 0          | NULL     |
+---------------------------------+---------+-----------+--------------+----------+------------+----------+
| PyBUF_STRIDED_RO                | 是      | 是        | NULL         | U        | 1 或 0     | NULL     |
+---------------------------------+---------+-----------+--------------+----------+------------+----------+
| PyBUF_CONTIG                    | 是      | NULL      | NULL         | C        | 0          | NULL     |
+---------------------------------+---------+-----------+--------------+----------+------------+----------+
| PyBUF_CONTIG_RO                 | 是      | NULL      | NULL         | C        | 1 或 0     | NULL     |
+---------------------------------+---------+-----------+--------------+----------+------------+----------+


复杂数组
========


NumPy-风格：形状和步幅
----------------------

The logical structure of NumPy-style arrays is defined by "itemsize",
"ndim", "shape" and "strides".

If "ndim == 0", the memory location pointed to by "buf" is interpreted
as a scalar of size "itemsize". In that case, both "shape" and
"strides" are *NULL*.

If "strides" is *NULL*, the array is interpreted as a standard
n-dimensional C-array. Otherwise, the consumer must access an
n-dimensional array as follows:

   "ptr = (char *)buf + indices[0] * strides[0] + ... + indices[n-1] *
   strides[n-1]" "item = *((typeof(item) *)ptr);"

As noted above, "buf" can point to any location within the actual
memory block. An exporter can check the validity of a buffer with this
function:

   def verify_structure(memlen, itemsize, ndim, shape, strides, offset):
       """Verify that the parameters represent a valid array within
          the bounds of the allocated memory:
              char *mem: start of the physical memory block
              memlen: length of the physical memory block
              offset: (char *)buf - mem
       """
       if offset % itemsize:
           return False
       if offset < 0 or offset+itemsize > memlen:
           return False
       if any(v % itemsize for v in strides):
           return False

       if ndim <= 0:
           return ndim == 0 and not shape and not strides
       if 0 in shape:
           return True

       imin = sum(strides[j]*(shape[j]-1) for j in range(ndim)
                  if strides[j] <= 0)
       imax = sum(strides[j]*(shape[j]-1) for j in range(ndim)
                  if strides[j] > 0)

       return 0 <= offset+imin and offset+imax+itemsize <= memlen


PIL-风格：形状，步幅和子偏移量
------------------------------

除了常规项之外， PIL 风格的数组还可以包含指针，必须跟随这些指针才能到
达维度的下一个元素。例如，常规的三维 C 语言数组 "char v[2][2][3]" 可以
看作是一个指向 2 个二维数组的 2 个指针："char (*v[2])[2][3]"。在子偏移
表示中，这两个指针可以嵌入在 "buf" 的开头，指向两个可以位于内存任何位
置的 "char x[2][3]" 数组。

Here is a function that returns a pointer to the element in an N-D
array pointed to by an N-dimensional index when there are both non-
NULL strides and suboffsets:

   void *get_item_pointer(int ndim, void *buf, Py_ssize_t *strides,
                          Py_ssize_t *suboffsets, Py_ssize_t *indices) {
       char *pointer = (char*)buf;
       int i;
       for (i = 0; i < ndim; i++) {
           pointer += strides[i] * indices[i];
           if (suboffsets[i] >=0 ) {
               pointer = *((char**)pointer) + suboffsets[i];
           }
       }
       return (void*)pointer;
   }


缓冲区相关函数
==============

int PyObject_CheckBuffer(PyObject *obj)

   Return "1" if *obj* supports the buffer interface otherwise "0".
   When "1" is returned, it doesn't guarantee that
   "PyObject_GetBuffer()" will succeed.  This function always
   succeeds.

int PyObject_GetBuffer(PyObject *exporter, Py_buffer *view, int flags)

   Send a request to *exporter* to fill in *view* as specified by
   *flags*. If the exporter cannot provide a buffer of the exact type,
   it MUST raise "PyExc_BufferError", set "view->obj" to *NULL* and
   return "-1".

   On success, fill in *view*, set "view->obj" to a new reference to
   *exporter* and return 0. In the case of chained buffer providers
   that redirect requests to a single object, "view->obj" MAY refer to
   this object instead of *exporter* (See Buffer Object Structures).

   Successful calls to "PyObject_GetBuffer()" must be paired with
   calls to "PyBuffer_Release()", similar to "malloc()" and "free()".
   Thus, after the consumer is done with the buffer,
   "PyBuffer_Release()" must be called exactly once.

void PyBuffer_Release(Py_buffer *view)

   Release the buffer *view* and decrement the reference count for
   "view->obj". This function MUST be called when the buffer is no
   longer being used, otherwise reference leaks may occur.

   It is an error to call this function on a buffer that was not
   obtained via "PyObject_GetBuffer()".

Py_ssize_t PyBuffer_SizeFromFormat(const char *)

   Return the implied "itemsize" from "format". This function is not
   yet implemented.

int PyBuffer_IsContiguous(Py_buffer *view, char order)

   Return "1" if the memory defined by the *view* is C-style (*order*
   is "'C'") or Fortran-style (*order* is "'F'") *contiguous* or
   either one (*order* is "'A'").  Return "0" otherwise.  This
   function always succeeds.

int PyBuffer_ToContiguous(void *buf, Py_buffer *src, Py_ssize_t len, char order)

   Copy *len* bytes from *src* to its contiguous representation in
   *buf*. *order* can be "'C'" or "'F'" (for C-style or Fortran-style
   ordering). "0" is returned on success, "-1" on error.

   如果 *len* != *src->len* 则此函数将报错。

void PyBuffer_FillContiguousStrides(int ndims, Py_ssize_t *shape, Py_ssize_t *strides, int itemsize, char order)

   Fill the *strides* array with byte-strides of a *contiguous*
   (C-style if *order* is "'C'" or Fortran-style if *order* is "'F'")
   array of the given shape with the given number of bytes per
   element.

int PyBuffer_FillInfo(Py_buffer *view, PyObject *exporter, void *buf, Py_ssize_t len, int readonly, int flags)

   处理导出程序的缓冲区请求，该导出程序要暴露大小为 *len* 的 *buf* ，
   并根据 *readonly* 设置可写性。*bug* 被解释为一个无符号字节序列。

   The *flags* argument indicates the request type. This function
   always fills in *view* as specified by flags, unless *buf* has been
   designated as read-only and "PyBUF_WRITABLE" is set in *flags*.

   On success, set "view->obj" to a new reference to *exporter* and
   return 0. Otherwise, raise "PyExc_BufferError", set "view->obj" to
   *NULL* and return "-1";

   If this function is used as part of a getbufferproc, *exporter*
   MUST be set to the exporting object and *flags* must be passed
   unmodified. Otherwise, *exporter* MUST be NULL.
