docs: address community issue feedback (#5 #338 #142 #246 #136 #303)

- 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
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> 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。
# CPython 扩展开发笔记
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。
## 0.背景
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。
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。
**问题1:初始化函数里面不支持其他类的默认构造。**
示例:
```
def __init__(self, mode="only_valid", filter=Expression._scalar(True)):
pass
```
报错:
```
TypeError: descriptor '_scalar' for 'pyarrow._compute.Expression' objects doesn't apply to a 'bool' object
```
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:
```python
@staticmethod
def _scalar(value):
cdef:
Scalar scalar
if isinstance(value, Scalar):
scalar = value
else:
scalar = lib.scalar(value)
return Expression.wrap(CMakeScalarExpression(scalar.unwrap()))
```
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:
```python
def __init__(self, mode="only_valid", filter=None):
if filter is None:
filter = Expression._scalar(True)
```
**问题2:定义顺序**
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。
```python
def __init__(self, mode="only_valid", filter=_true):
pass
cdef CExpression _true = CMakeScalarExpression(
<shared_ptr[CScalar]> make_shared[CBooleanScalar](True)
)
```
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。
## 1.CPython完整例子
1. 创建一个.h文件
```cpp
void sort(std::vector<int>& nums) {
std::sort(nums.begin(), nums.end());
}
int sum(std::vector<int>& nums) {
int sum = 0;
for (int num : nums) {
sum += num;
}
return sum;
}
```
2) 创建foo.pyx
重要点:上面vector需要:
```
from libcpp.vector cimport vector
```
然后去定义一个class,调用C++的接口。
```
cdef class PyFoo:
cdef Foo* f
def __cinit__(self):
self.f = new Foo()
def __dealloc__(self):
del self.f
def sort(self, nums):
cdef vector[int] c_nums = nums
self.f.sort(c_nums)
def sum(self, nums):
cdef vector[int] c_nums = nums
return self.f.sum(c_nums)
```
3. 创建setup.py文件
```python
ext = Extension('Foo', sources=["foo.pyx"], language="c++", include_dirs=[numpy.get_include()])
setup(name="Foo", ext_modules = cythonize([ext]))
```
4. 运行
```
python3 setup.py build_ext --inplace
```
最后,可以写一个测试脚本去使用自己写的python接口。
```python
import Foo
f = Foo.PyFoo()
nums = [3, 1, 4, 1, 5, 9, 2, 6, 5, 3, 5]
f.sort(nums)
print("Sorted nums:", nums)
print("Sum of nums:", f.sum(nums))
```
CPython在一些项目中使用挺多的,学习起来吧~
运行:
```
➜ cpython_examples python3 test.py
Sorted nums: [3, 1, 4, 1, 5, 9, 2, 6, 5, 3, 5]
Sum of nums: 44
```