Embedding Python in C/C++. In order to use the source code. Python examples (example source code) Organized by topic. Home; Python; 2D; Application; Buildin Function; Class; Data Structure. Python; GUI Tk / Alarm 1: Animation 3: Back Fore. The official home of the Python Programming Language. While Javascript is not essential for this website, your interaction with the content will be limited. Please turn Javascript on for the full experience. Embedding Python program in a C/C++ code. How to Embed Python interpreter in your C/C++ code and dynamically change the code path of compiled native code. Introduction. In this Article, we will discuss the following topics: Getting the Python C/C++ API for working. Initialize and Destroy a Python environment. Running a Simple inline Python code from C/C++. Running a Simple Python program from file from C/C++ program. Call a Python method from C/C++. Call a C/C++ function from Python code. Why are we doing this???? And have basics programming knowledge in Python. The Line Numbering Program with Line Numbers Added Chapter10/listing10-8.py. A Sample Plain-Text Document (testBefore we begin : What we need??? Create a Console Application. Assuming that Python 3 is installed on the system, completely, at a location . If it builds correctly, we are ready to begin our work!!! Initialize and Clean the Python Environment. The simplest program to embed is: #include< stdio. Python. h> int main(). The linker library file is Python. Python. XX. lib, XX=3. Initialize Python environment by calling Py. This code is: print('Hello World from Embedded Python!!!'). This code in Python will print the line . This program is executed by our code using Py. Run. But the caller must ensure that, this function is called after Python interpreter is initialized and before it is destroyed. Thus, we now know how to execute a simple Python code from String in C. Next we will examine how to execute a Python code from an external text file. Execute a Python Program program from file. Consider the Simple Python program to execute, which is stored in the file . This function is similar to the fopen function of standard C/C++. Here we have opened the pyemb. Check the FILE* object returned. If it is NULL, the file cannot be opened, so we cannot proceed further. Report an error and abort. Now we have the file opened. We have to execute it using Py. Run. Next we will discuss a code, to call a specific Python function from a Python file. C++ Helper for Python. Content of C++ Header file pyhelper. Python Source Code and Scripts Downloads Free. Search; Python Articles Python sample free download. OSI-Approved Open Source (34) GNU General Public License version 2.0 (11). Python Software Foundation License (1) Creative Commons Attribution License (4). PYHELPER? When this object goes out of scope, the Python environment is destroyed. Now we can write the first program above as: #include< stdio. Advantage of the CPy. Instance class is that, the Python is deinitialized automatically and programmer is free to focus on rest of the code. In the next section we will discuss the use of Python object Py. Object and the corresponding helper CPy. Object class. Py. Object and the CPy. Object helper. Py. Object is a Python object used to access the Python objects used or returned by Python interpreter. Python uses references to track the objects returned. When an object is no more needed, it must be deferenced, using DECREF and XDECREF. Consider the code sample below: Py. Object* p. Obj = ... Once the object is no more required, we have called DECREF macro and passed the p. Obj pointer to it, and we are done. After this, the p. Obj code will become useless, and caller should never use it further. What about XDECREF macro? Calling DECREF requires that the passed Py. Object pointer should never be null. XDECREF checks for NULL pointer and then internally call DECREF if the Py. Object pointer passed is NOTNULL. If we want to re- reference the Py. Object further, or pass it to another function, then we must increase its reference. Hence use INCREF or XINCREF, and pass the Py. Object pointer to it. XINCREF is safe, and you can pass a NULL pointer too. But INCREF cannot process NULL pointer. To be safe, we will use the C++ class CPy. Object. Consider the code sample: CPy. Object p. Obj = ... This helper class encapsulate the Py. Object* within CPy. Object class. Once the class goes out of scope, the object is automatically dereferenced. Also, the NULL object is automatically taken care of, and can also be automatically type casted to Py. Object*. But to increase the reference pointer, call the Add. Reff(), method of the CPy. Object class.#include< pyhelper. This function has the signature Py. Object* Py. Long. The function takes in a long value and returns a Py. Object. Next we want to convert Py. Object* to long value. We know that the p object represents a long value. The function signature is long Py. Long. This function takes in a Py. Object* and returns a long value. In the above program, we have printed this Python object's value. After we are done, we just forget about the object, it will automatically be dereferenced. Next, we will call a Python function from C++. Call a Python function (method) from C++Consider the following Python program, stored in pyemb. Integer(). print('Python function get. Integer() called'). Now we want to call the function get. Integer() from the following C++ code and print the value returned this function. This is the client C++ code: #include< stdio. Python. h> #include< pyhelper. Our module name is pyemb. Python object using from the function Py. Object *Py. Unicode. This function returns Py. Object* in CPy. Object as CPy. Object p. Name = Py. Unicode. We use this function as CPy. Object p. Module = Py. Import. Here, no null check is done, programmers may check for it, if they want. Next, we get the function attribute object using the function Py. Object* Py. Object. So, we use this as CPy. Object p. Func = Py. Object. The first is the handle to the module being used, then the second argument is the name of the function being called. Next, we check if the returned function object is. NULL. If it is not NULL, then check if we can call the function. For this we use int Py. Callable. We pass the function object pointer to this function. If we get a 1 in return, then we can call the function. Only if we can call the function, we can proceed further. Next, we call the Python function using Py. Object* Py. Object. The first argument here is the function object, we obtained previously. The second is the arguments that will be passed to the Python method. But we do not pass any argument, so we pass NULL to this. The function after execution, will return an object that is returned by the Python method. The result of the Python function. Since we know, that the function returns a long value, so we print the value using the program line printf. The familiar part of the code are, initializing Python environment, then load a Python program and run the program. But now we will conventrate on how to add a new module to Python environment. First of all, the imported module must be added before the Python instance is initialized. Now how we do it: The C function must have the format- . Py. Object* self as first object, representing the function itself. Py. Object* args as the second object, representing the arguments that is passed by the Python program. Py. Object* returned by the function itself. This represents the data to be returned to the Python program calling this function. The function name following the format module. Namespace. Its signature is int Py. Arg. First argument is the reference to the args pointer. The parameter name is not used, it refers to access mode possibly. The min represents minimum number of arguments (tuples) to be passed by Python code, and max must be maximum number of arguments that can be passed. We need only 1 argument to our function, so we set min = max =1. Next, we declare a method table. Py. Method. Def methods. It's fields are. First field represents the name of the method, that the Python code will use to call our native code. The C/C++ function pointer, that will be invoked when Python calls in. Method can pass in variable numbers of arguments. This is must. Last field, represents a help string. Specify what our function will do. Can be thought of as a Help for our function, in Python environment. A newly introduced way to develop import module in Python 3, is to declare Py. Module. Def. staticstruct Py. Module. Def mod. Def = . In our case, it is arnav. Third argument - We are not using it. Specify NULL. Fourth argument - Specify - 1. Fifth argument - We pass the pointer to our method declaration structure Py. Method. Def. In our case we pass our static variable method. Last 4 parameters, we do not use. So we specify NULL for these. NOTE: We are using a minimal declaration, which will solve most of our problems. So, in future article, we will use more fields of this structure and describe in details about each field and their effect. Next, we declare the following code. Py. Object* Py. Init. Here we declare a function of format Py. Init. In our case for namespace arnav, we use function name Py. Init. This function does not take anything, but returns a Py. Object*. Note the use of Py. Object* Py. Module. Here, we pass our Py. Module. Def structure. This function will create a new module. In our case we pass the address of our mod. Def variable. The function returns a Py. Object* when the module is loaded, the function Py. Init. This is done through the use of function Py. Import. This function has the signature int Py. Import. We pass our initialization function Py. Init. And, if successful (function will not return - 1), the new module will be added to the Python environment. Finally, the module will become callable from the Python module. Now we will examine how the Python source utilizes this new namespace arnav: First, import the new namespace. Now we can call the methods within arnav module, using format module. Name. function. Name(..) - . The output of the program is: in python. Also, the Python API is elaborate yet easy to use. Further, embedding an interpreter within a Native language will enable us to change the course of the program after it had been designed, makes dynamic programming approach to the programming. In future, we would investigate more into the embedded Python and examine the above discussed structures in details. Download the attached ZIP file. It has the Python. SDK bundled along with some demo applications, discussed in this article. You can directly use it. If you are installing Python. Boost and other API alternatives are available for the same work, but since I have never used one; I am sticking to the Python official SDK. Always distribute Python. C/C++ application.
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