是的，你可以在 C 中建立包含函式、變數、例外甚至新型別的內建模組，擴充和嵌入 Python 直譯器 文件中有相關說明。
大多數中級或進階 Python 書籍也會涵蓋這個主題。
是的，可使用 C++ 中的 C 相容性功能。將 extern "C" { ... } 放在 Python 引入檔案周圍，並將 extern "C" 放在每個將由 Python 直譯器呼叫的函式之前。但具有構造函式的全域或靜態 C++ 物件可能不是一個好主意。
There are a number of alternatives to writing your own C extensions, depending on what you're trying to do. Recommended third party tools offer both simpler and more sophisticated approaches to creating C and C++ extensions for Python.
The highest-level function to do this is PyRun_SimpleString() which takes
a single string argument to be executed in the context of the module
__main__ and returns 0 for success and -1 when an exception occurred
(including SyntaxError). If you want more control, use
PyRun_String(); see the source for PyRun_SimpleString() in
Python/pythonrun.c.
Call the function PyRun_String() from the previous question with the
start symbol Py_eval_input; it parses an expression, evaluates it and
returns its value.
That depends on the object's type. If it's a tuple, PyTuple_Size()
returns its length and PyTuple_GetItem() returns the item at a specified
index. Lists have similar functions, PyList_Size() and
PyList_GetItem().
For bytes, PyBytes_Size() returns its length and
PyBytes_AsStringAndSize() provides a pointer to its value and its
length. Note that Python bytes objects may contain null bytes so C's
strlen() should not be used.
要測試物件的型別，首先確保它不是 NULL，然後再使用 PyBytes_Check()、PyTuple_Check()、PyList_Check() 等函式。
There is also a high-level API to Python objects which is provided by the
so-called 'abstract' interface -- read Include/abstract.h for further
details. It allows interfacing with any kind of Python sequence using calls
like PySequence_Length(), PySequence_GetItem(), etc. as well
as many other useful protocols such as numbers (PyNumber_Index() et
al.) and mappings in the PyMapping APIs.
這無法做到。請改用 PyTuple_Pack()。
The PyObject_CallMethod() function can be used to call an arbitrary
method of an object. The parameters are the object, the name of the method to
call, a format string like that used with Py_BuildValue(), and the
argument values:
PyObject *
PyObject_CallMethod(PyObject *object, const char *method_name,
const char *arg_format, ...);
這適用於任何具有方法的物件 —— 無論是內建的還是使用者定義的。你負責最終為回傳值來 Py_DECREF()。
例如，使用引數 10、0 呼叫檔案物件的 "seek" 方法（假設檔案物件指標為 "f"）：
res = PyObject_CallMethod(f, "seek", "(ii)", 10, 0);
if (res == NULL) {
... 發生一個例外 ...
}
else {
Py_DECREF(res);
}
請注意，由於 PyObject_CallObject() 總是需要一個元組作為引數列表，若要呼叫一個不帶引數的函式，要傳遞 "()" 作為格式，並呼叫一個帶有一個引數的函式，將引數括起來在括號中，例如 "(i)"。
In Python code, define an object that supports the write() method. Assign
this object to sys.stdout and sys.stderr. Call print_error, or
just allow the standard traceback mechanism to work. Then, the output will go
wherever your write() method sends it.
最簡單的方法是使用 io.StringIO 類別：
>>> import io, sys
>>> sys.stdout = io.StringIO()
>>> print('foo')
>>> print('hello world!')
>>> sys.stderr.write(sys.stdout.getvalue())
foo
hello world!
執行相同操作的自定義物件如下所示：
>>> import io, sys
>>> class StdoutCatcher(io.TextIOBase):
... def __init__(self):
... self.data = []
... def write(self, stuff):
... self.data.append(stuff)
...
>>> import sys
>>> sys.stdout = StdoutCatcher()
>>> print('foo')
>>> print('hello world!')
>>> sys.stderr.write(''.join(sys.stdout.data))
foo
hello world!
你可以取得指向模組物件的指標，如下所示：
module = PyImport_ImportModule("<modulename>");
If the module hasn't been imported yet (i.e. it is not yet present in
sys.modules), this initializes the module; otherwise it simply returns
the value of sys.modules["<modulename>"]. Note that it doesn't enter the
module into any namespace -- it only ensures it has been initialized and is
stored in sys.modules.
You can then access the module's attributes (i.e. any name defined in the module) as follows:
attr = PyObject_GetAttrString(module, "<attrname>");
Calling PyObject_SetAttrString() to assign to variables in the module
also works.
根據你的要求不同而有多種不同方法。要手動執行此操作，請先閱讀「擴充和嵌入」說明文件。對於 Python run-time 系統，C 和 C++ 之間並沒有太多區別 —— 因此圍繞 C 結構（指標）型別來構建新 Python 型別的策略也適用於 C++ 物件。
對於 C++ 函式庫，請參閱 寫 C 很難；還有其他選擇嗎？。
Setup must end in a newline, if there is no newline there, the build process fails. (Fixing this requires some ugly shell script hackery, and this bug is so minor that it doesn't seem worth the effort.)
When using GDB with dynamically loaded extensions, you can't set a breakpoint in your extension until your extension is loaded.
在你的 .gdbinit 檔案中（或交互地），新增命令：
br _PyImport_LoadDynamicModule
然後，當你運行 GDB 時：
$ gdb /local/bin/python
gdb) run myscript.py
gdb) continue # repeat until your extension is loaded
gdb) finish # so that your extension is loaded
gdb) br myfunction.c:50
gdb) continue
Most packaged versions of Python omit some files required for compiling Python extensions.
在 Red Hat 上，請安裝 python3-devel RPM 來取得必要的檔案。
對於 Debian，運行 apt-get install python3-dev。
Sometimes you want to emulate the Python interactive interpreter's behavior, where it gives you a continuation prompt when the input is incomplete (e.g. you typed the start of an "if" statement or you didn't close your parentheses or triple string quotes), but it gives you a syntax error message immediately when the input is invalid.
在 Python 中，你可以使用 codeop 模組，它充分模擬了剖析器 (parser) 的行為。像是 IDLE 就有使用它。
The easiest way to do it in C is to call PyRun_InteractiveLoop() (perhaps
in a separate thread) and let the Python interpreter handle the input for
you. You can also set the PyOS_ReadlineFunctionPointer() to point at your
custom input function. See Modules/readline.c and Parser/myreadline.c
for more hints.
To dynamically load g++ extension modules, you must recompile Python, relink it
using g++ (change LINKCC in the Python Modules Makefile), and link your
extension module using g++ (e.g., g++ -shared -o mymodule.so mymodule.o).
是的，你可以繼承內建類別，例如 int、list、dict 等。
Boost Python 函式庫（BPL，https://www.boost.org/libs/python/doc/index.html）提供了一種從 C++ 執行此操作的方法（即你可以使用 BPL 來繼承用 C++ 編寫的擴充類別）。