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- const README: rewrite the space-saving claim per issue #5 follow-ups (constant-expression const vs #define immediates; which const qualify as constant expressions) - const README: fix the class-section diagnosis per issue #338 (overload resolution picks the const overload; the restriction only surfaces once that overload is removed) - sizeof README: virtual-inheritance result is compiler-dependent (GCC merges vbptr+vfptr -> 16, MSVC keeps them separate -> 32) #246 - static README: new section on internal linkage / access restriction with anonymous-namespace comparison #142 - 10-day practice: full problem list table + fixed day links #136 - new design_pattern/singleton/singleton_default.hpp: reusable thread-safe CRTP singleton template, compile+concurrency tested #303
148 lines
3.7 KiB
Markdown
148 lines
3.7 KiB
Markdown
> 来自 [C++那些事网站](https://light-city.github.io/stories_things/cpp-guides/cpython-extension-notes/) 的文章，由站点同步脚本导出。
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# CPython 扩展开发笔记
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本篇文章将会围绕最近给Apache提的一个feature为背景，展开讲讲CPython遇到的问题，以及尝试自己从0写一个库出来，代码也已经放星球了，感兴趣的同学可以去下载学习。
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## 0.背景
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最近在给apache arrow提的一个feature因为C++接口的变动引发其他语言的接口变动，一些测试也跟着需要修复。
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像PyArrow熟悉的人应该一点也不陌生，这次接口变动也需要修改这个库，因为是在一个仓库里的，不然ci过不了。而PyArrow的实现是通过CPython实现的，之前也没特别学习CPython，改出了一堆问题，其中遇到两个问题比较重要，这里记录一下。
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**问题1：初始化函数里面不支持其他类的默认构造。**
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示例：
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```
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def __init__(self, mode="only_valid", filter=Expression._scalar(True)):
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pass
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```
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报错：
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```
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TypeError: descriptor '_scalar' for 'pyarrow._compute.Expression' objects doesn't apply to a 'bool' object
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```
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可以看到没识别出来，实际情况是Expression._scalar(True)合法的，我们看里面的实现：
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```python
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@staticmethod
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def _scalar(value):
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cdef:
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Scalar scalar
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if isinstance(value, Scalar):
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scalar = value
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else:
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scalar = lib.scalar(value)
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return Expression.wrap(CMakeScalarExpression(scalar.unwrap()))
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```
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可以看到，里面支持正常的bool类型，我怀疑这是cpython的限制，于是改为下面这种方式就可以了：
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```python
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def __init__(self, mode="only_valid", filter=None):
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if filter is None:
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filter = Expression._scalar(True)
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```
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**问题2：定义顺序**
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当我使用后面创建的`_true`，每次传递进去的默认值是空，这个比较好理解，因为最后编译好了会翻译为一个`xxx.cpp`文件，根据C++规则前面读到的自然就是空了。
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```python
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def __init__(self, mode="only_valid", filter=_true):
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pass
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cdef CExpression _true = CMakeScalarExpression(
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<shared_ptr[CScalar]> make_shared[CBooleanScalar](True)
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)
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```
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好了，基于以上背景，我自己也想写一个例子出来，例如：使用C++写一个类，封装sort和sum，然后使用Python调用。
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## 1.CPython完整例子
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1. 创建一个.h文件
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```cpp
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void sort(std::vector<int>& nums) {
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std::sort(nums.begin(), nums.end());
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}
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int sum(std::vector<int>& nums) {
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int sum = 0;
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for (int num : nums) {
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sum += num;
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}
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return sum;
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}
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```
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2) 创建foo.pyx
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重要点：上面vector需要：
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```
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from libcpp.vector cimport vector
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```
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然后去定义一个class，调用C++的接口。
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```
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cdef class PyFoo:
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cdef Foo* f
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def __cinit__(self):
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self.f = new Foo()
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def __dealloc__(self):
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del self.f
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def sort(self, nums):
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cdef vector[int] c_nums = nums
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self.f.sort(c_nums)
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def sum(self, nums):
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cdef vector[int] c_nums = nums
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return self.f.sum(c_nums)
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```
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3. 创建setup.py文件
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```python
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ext = Extension('Foo', sources=["foo.pyx"], language="c++", include_dirs=[numpy.get_include()])
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setup(name="Foo", ext_modules = cythonize([ext]))
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```
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4. 运行
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```
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python3 setup.py build_ext --inplace
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```
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最后，可以写一个测试脚本去使用自己写的python接口。
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```python
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import Foo
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f = Foo.PyFoo()
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nums = [3, 1, 4, 1, 5, 9, 2, 6, 5, 3, 5]
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f.sort(nums)
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print("Sorted nums:", nums)
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print("Sum of nums:", f.sum(nums))
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```
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CPython在一些项目中使用挺多的，学习起来吧~
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运行：
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```
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➜ cpython_examples python3 test.py
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Sorted nums: [3, 1, 4, 1, 5, 9, 2, 6, 5, 3, 5]
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Sum of nums: 44
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``` |