If your executable reads parameters from a file, then your script either needs to create that file, or somehow needs to change parameters in some template file, which again requires regular expression parsing.Īlternatively, you can share values between Python and the executable using binary files, since those can store any data type. This might not be very efficient and definitely does not make for very easy code. Finally, universal_newlines = True makes sure line breaks in the terminal output are processed correctly.īoth the input and output for n() assumes strings, so you will need to convert all input arguments to strings before passing them on, and you will need to parse the output if you want to extract values from it. stdout = subprocess.PIPE will capture the output to the terminal instead of simply writing it to the terminal window. These will be joined together with spaces to create the command that will be executed. The arguments to n are quite straightforward: the first argument is a list containing all parts of the command to run (usually an executable followed by additional arguments). This assumes the test executable is located in the same directory where you are running Python. To run an executable called test with additional arguments a.in and 0.001, and collect its output to the terminal for example, you can use: Running commands from Python can be done in many ways, e.g. If you have a C++ executable that can be easily controlled through command line arguments or an input parameter file, and this executable generates the output you want for those parameters without much overhead, then arguably the easiest solution to achieve this is to simply run the executable from Python. The easy way: running software from Pythonīefore we embark on the difficult journey to actually couple C++ to Python, it is worth pointing out that there are lazy solutions. In this post, I will list a few ways to achieve this. For this reason, it can be quite useful to write the crucial parts of an algorithm in a low-level language like C++, and then somehow expose this code to Python. Writing efficient Python is however not as easy, especially if the algorithm you want to write is complex and cannot exploit the power of NumPy or SciPy. Python is a very popular tool among many scientists, mainly because it is very easy to use and because there exists a large number of powerful libraries that can be used from Python.

Exe file convert to cpp