Embedding Python in C/C++ is also relatively simple. First, you need to add Python’s include file directory and lib file directory in VC:
Under VC6.0, open
tools->options->directories->show directories
for, add the inlude directory in the Python installation directory to the include files item, and add the libs directory to library
files item.
Under VC2005, open the tools->options->Projects and Solutions->VC++ directory, and then do the same work.
The code is as follows:
//在debug下执行出错,“无法找到python31_d.lib文件”,后查到原因是:在debug下生成必须要有python31_d.lib文件,否则只能在release下生成 #include <python.h> int main() { Py_Initialize(); PyRun_SimpleString("Print 'hi, python!'"); Py_Finalize(); return 0; }
Py_Initialize function prototype is: void
Py_Initialize(), this function must be used when embedding Python scripts. It initializes the Python interpreter and is used when using other Python/C
This function must be called before the API. You can use the Py_IsInitialized function to determine whether the initialization is successful and return True if successful.
PyRun_SimpleString function prototype is int
PyRun_SimpleString(const char
*command), used to execute a piece of Python code. Note: Do you need to maintain indentation between statements?
Py_Finalize function prototype is void
Py_Finalize(), used to close the Python interpreter and release the resources occupied by the interpreter.
PyRun_SimpleFile function can be used to run ".py" script files. The function prototype is as follows:
int
PyRun_SimpleFile(FILE *fp, const char *filename);
its
where fp is the open file pointer, and filename is the name of the python script file to be run. However, since this function is officially released by visual studio
Compiled with 2003.NET, if other versions of the compiler are used, the FILE definition may cause a crash due to version reasons. At the same time, for simplicity, you can use the following method to replace this function:
PyRun_SimpleString("execfile('file.py')");
//Use execfile to run python files
Py_BuildValue() is used to convert numbers and strings into corresponding data types in Python (in C language, all Python types are declared as PyObject types), function The prototype is as follows:
PyObject
*Py_BuildValue(const char *format,
…..);
PyString_String() is used to convert PyObject* type variables into char* type that can be processed by C language. The specific prototype is as follows:
char*
PyString_String(PyObject *p);
List operation function:
PyObject
* PyList_New(Py_ssize_t len);
int PyList_SetItem(PyObject *list, Py_ssize_t
index, PyObject *item);
PyObject * PyList_GetItem(PyObject *list, Py_ssize_t
index);
int PyList_Append(PyObject *list, PyObject *item);
int
PyList_Sort(PyObject *list);
int PyList_Reverse(PyObject
*list);
Py_ssize_t PyList_Size(PyObject *list);
Tuple operation function:
int
PyTuple_New(Py_ssize_t len);
int PyTuple_SetItem(PyObject *p, Py_ssize_t pos,
PyObject *o);
PyObject * PyTuple_GetItem(PyObject *p, Py_ssize_t pos);
int
_PyTuple_Resize(PyObject **p, Py_ssize_t newsize);
//Note that it is a ** pointer
Dictionary operation function:
PyObject * PyDict_New();
int PyDict_SetItem(PyObject
*p, PyObject *key, PyObject *val);
int PyDict_SetItemString(PyObject *p,
const char *key, PyObject *val);
PyObject* PyDict_GetItem(PyObject *p,
PyObject *key);
PyObject* PyDict_GetItemString(PyObject *p, const char
*key);
//corresponds to PyDict_SetItemString
int PyDict_DelItem(PyObject *p, PyObject
*key);
int PyDict_DelItemString(PyObject *p, char
*key);
//corresponds to PyDict_SetItemString
int PyDict_Next(PyObject *p, Py_ssize_t
*ppos, PyObject **pkey, PyObject **pvalue);
PyObject* PyDict_Items(PyObject
*p);
PyObject* PyDict_keys(PyObject *p);
PyObject* PyDict_Values(PyObject
*p);
Using Python objects in C/C++ should handle reference counting issues correctly, otherwise it can easily lead to memory leaks. When using Python/C
After functions in the API create lists, tuples, dictionaries, etc., you should use macros such as Py_CLEAR() and Py_DECREF() to destroy these objects after completing operations on them. The prototype is as follows:
void
Py_CLEAR(PyObject *o);
void Py_DECREF(PyObject
*o);
Among them, for the Py_CLEAR function, the parameter can be a NULL pointer, which means no operation is performed, but the Py_DECREF function cannot be a NULL pointer, otherwise an error will occur.
Use the PyImport_Import() function to import a Python module in C and return a module object. The function prototype is:
PyObject*
PyImport_Import(PyObject
*name);
The PyModule_GetDict() function can obtain the function list in the Python module and return a dictionary. The key in the dictionary is the function name and the value is the calling address of the function. The prototype is as follows:
PyObject*
PyModule_GetDict(PyObject
*module);
Use the PyObject_CallObject() function and PyObject_CallFunction() function to call functions in Python from C. The prototype is as follows:
PyObject*
PyObject_CallObject(PyObject *callable_object, PyObject
*args);
//args is in tuple form
PyObject* PyObject_CallFunction(PyObject *callable,
char *format,
...);
//format is a parameter type similar to "iss", followed by the specified parameters
You can use PyCallable_Check(func) to determine whether the function can be called, and return True if it can.
The above is the content of embedding Python in C/C++. For more related articles, please pay attention to the PHP Chinese website (www.php.cn)!

Python and C each have their own advantages, and the choice should be based on project requirements. 1) Python is suitable for rapid development and data processing due to its concise syntax and dynamic typing. 2)C is suitable for high performance and system programming due to its static typing and manual memory management.

Choosing Python or C depends on project requirements: 1) If you need rapid development, data processing and prototype design, choose Python; 2) If you need high performance, low latency and close hardware control, choose C.

By investing 2 hours of Python learning every day, you can effectively improve your programming skills. 1. Learn new knowledge: read documents or watch tutorials. 2. Practice: Write code and complete exercises. 3. Review: Consolidate the content you have learned. 4. Project practice: Apply what you have learned in actual projects. Such a structured learning plan can help you systematically master Python and achieve career goals.

Methods to learn Python efficiently within two hours include: 1. Review the basic knowledge and ensure that you are familiar with Python installation and basic syntax; 2. Understand the core concepts of Python, such as variables, lists, functions, etc.; 3. Master basic and advanced usage by using examples; 4. Learn common errors and debugging techniques; 5. Apply performance optimization and best practices, such as using list comprehensions and following the PEP8 style guide.

Python is suitable for beginners and data science, and C is suitable for system programming and game development. 1. Python is simple and easy to use, suitable for data science and web development. 2.C provides high performance and control, suitable for game development and system programming. The choice should be based on project needs and personal interests.

Python is more suitable for data science and rapid development, while C is more suitable for high performance and system programming. 1. Python syntax is concise and easy to learn, suitable for data processing and scientific computing. 2.C has complex syntax but excellent performance and is often used in game development and system programming.

It is feasible to invest two hours a day to learn Python. 1. Learn new knowledge: Learn new concepts in one hour, such as lists and dictionaries. 2. Practice and exercises: Use one hour to perform programming exercises, such as writing small programs. Through reasonable planning and perseverance, you can master the core concepts of Python in a short time.

Python is easier to learn and use, while C is more powerful but complex. 1. Python syntax is concise and suitable for beginners. Dynamic typing and automatic memory management make it easy to use, but may cause runtime errors. 2.C provides low-level control and advanced features, suitable for high-performance applications, but has a high learning threshold and requires manual memory and type safety management.


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