I'm working in a project that produces several algorithms that should make part of a python library.
Some of these may be coded in python and some others in C++.
We use BOOST to bind our C++ functions into a python library, using:
BOOST_PYTHON_MODULE(MyPythonModule)
{
...
}
When we compile this we get a .so file containing the module.
On the other hand, we have .py files that contain functions that we would like to be found in the same module.
Is there a way to add the functions contained in the .py file into the module contained in the .so?
If this can be done after compiling it would be perfect, although that sounds too difficult (impossible?).
I also want to avoid calling the python function in C++ and then binding it as it would make a python-> C++ -> python chain which sounds at least "impractical".
Related
I am working on a project which requires me to create some wrappers in Python for the C library that I need to call from Python. For context, the C library I am using is a bunch of header files (.h) and statically linked library files (.a)
I have decided to use either CFFI or Cython to get my work done. I followed examples similar to this for CFFI - Interfacing C code with CFFI, and this for Cython - Making your C library callable from Python by wrapping it with Cython. Now small sample programs I've tried in both these modules more or less have the following steps
Create the interfacing code to call C APIs
In CFFI, it's a python file declaring the C functions and headers needed
In Cython, it's a .pyx file and modifications to setup.py
Build the interfacing code to generated the .so files for the interfacing glue code.
Call the wrapped functions from a different python script, by importing the interfacing library from the .so file.
Now, this works perfectly for me. But, I'll have to go through two execution steps in the process (generating the .so file, and then actually running the python script with the C API being called).
What I need is to know if there is a way to do all the above in a single execution step. Like, I want to run my final python script, and it should build the interfacing code and import it on the fly in a single execution.
For more context, I have tried SWIG, but wasn't able to find a way to wrapped .a statically linked libraries with it. Same goes for ctypes.
Can you not do this?
import os
os.system('command to build your .so here')
...
import what_ever_you_need
...
For CFFI you just need to execute at runtime the code that is now in the builder script. Move it all in a function, and then you have a function you can call when needed.
Is it possible to modify Ctypes src code to support static libraries for Python (eg. I can modify Ctypes to add some additional funcs to invoke static library)?
Since for special reasons, I have to compile everything into one giant Python blob (including Python interpreter, and user Python .py programs(zip section)). Therefore, I cannot use separate .so libraries during my Python blob running.
BTW: Python C extension is not considered here, since my clients' code uses Ctypes to bridge there C code for Python. I don't want to change too much in their side.
I have a main file(main.cpp) and a header file(nodes.hpp). The main file takes N(any positive integer) as input argument and by using the functions of header file it gives output say 'x & y' (both double).
Note:
Both main and header files are written in C++.
Both main and header files instead of using data structues as arrays,vectors, make use of Eigen Library.
I have to write a python wrapper for them, I have working knowledge of python but have never used any wrapper.
Can anybody please refer or give some notes about using python wrpper for such code?
Here are your options:
You can use ctypes, and I consider this the cleanest solution, because you convert your program to a shared library that can be called by any other software, not only Python. You, though, have to write a C-interface for your program yourself.
You can use Python C-Extension, and I consider this the worst solution, because it's very low level, and prone to memory leaks, and costs lots of time to implement one function, and is Python-version dependent. Basically this is good to start a Python interpreter inside your C++. You can create PyObjects (which is the main building block of any Python type) and deal with them insdie C/C++.
You can use SWIG, where it automatically creates the the interface that you have to create with ctypes through an interface file that you define. People say it's very good, but the documentation is not as good.
You can use Boost.Python, which is good, but it has a very ugly build system with bjam. If you can manage to bypass that, then it's even better than ctypes. I'm a big boost fan, but bjam is why I don't use this.
What I do typically is ctypes. I trust it because it emphasizes the single-reponsibility principle. The library has a job that's separate from the interface (the C-interface), which is also separate from your Python script that uses that interface and exposes "the easy functionality" to the user.
Use Boost.Python. Here is my tutorial, previously on SO Docs.
Using Boost.Python
Things are easy when you have to use a C++ library in a Python project. Just you can use Boost.
First of all here is a list of components you need:
A CMakeList.txt file, because you're going to use CMake.
The C++ files of the C++ project.
The python file - this is your python project.
Let's start with a small C++ file. Our C++ project has only one method which returns some string "This is the first try". Call it CppProject.cpp
char const *firstMethod() {
return "This is the first try.";
}
BOOST_PYTHON_MODULE(CppProject) {
boost::python::def("getTryString", firstMethod); // boost::python is the namespace
}
Have a CMakeLists.txt file a below:
cmake_minimum_required(VERSION 2.8.3)
FIND_PACKAGE(PythonInterp)
FIND_PACKAGE(PythonLibs)
FIND_PACKAGE(Boost COMPONENTS python)
INCLUDE_DIRECTORIES(${Boost_INCLUDE_DIRS} ${PYTHON_INCLUDE_DIRS})
PYTHON_ADD_MODULE(NativeLib CppProject)
FILE(COPY MyProject.py DESTINATION .) # See the whole tutorial to understand this line
By this part of the tutorial everything is so easy. you can import the library and call method in your python project. Call your python project MyProject.py.
import NativeLib
print (NativeLib.getTryString)
In order to run your project follow the instructions below:
Create a directory with the name build.
Enter into that directory.
Give the command cmake -DCMAKE_BUILD_TYPE=Release ..
make
python MyProject.py. Now, you have to see the string which the method in your C++ project returns.
Another tool for C++ wrapper generation is CLIF. Released in 2017, Google uses this for most everything these days. We no longer allow new SWIG wrappers to be written for Python internally.
It is built on top of Clang for the C++ parsing and requires relatively idiomatic modern C++ API use (unsurprisingly following Google's Style Guide) rather than any attempt to allow you to shoot yourself in the foot via SWIG's "support everything poorly" approach.
Try with official documentation:
https://docs.python.org/2/extending/extending.html
this link will provide you simple example of how to include a cpp module and use it from the python interpreter, or if this is possible try with Cython: http://cython.org/
Cython will allow you to write C-like, Python-like code which will be translated to CPP compiled and then will be easily accessible from the Python.
You can use Boost.Python
or go with the Python native interface
I would recommend Boost.Python if you already have Boost set up.
I'm writing some sort of Python C extension. It uses my own *.so library and headers from another project (let's say they're in /usr/local/lib/otherproject.so and /usr/local/include/otherproject.h).
I don't know which strategy to follow. I came up with two:
As a pure Python extension
Write a Python C extension just as described in the official docs. The problem here is that I don't know how to link with my own library and headers; to compile, I write a setup.py file and run python3.4 setup.py build. I don't know if I can include some option to the former command, or if I can write something in setup.py to include my headers and binaries (if so, I will also have to worry about making this distributable?).
With ctypes
Write a C library (with my other project's build system). Include Python by passing '/usr/include/python2.7' to find headers and the python2.7 binary. Then use ctypes to wrap around that library and get the functions, types, objects, etc. The inconvenience here is that I need to manually wrap around every single function/type/variable from ctypes; I don't think I can use PyModule_AddObject since I'm not creating the module in C but in the Python wrapper (with ctypes).
Also, I tried the second approach, but I could not successfully get my custom PyTypeObject from ctypes. If the second approach sounds good to any more expert brain here on SO, I would post the code to get any help =).
The second approach also yields problems with distribution. And if you create a Python object in C you should do it in the context of a module. For scenarios where distribution is problematic, you could link this module statically instead.
For your issue with linking you'll find more information about Library options in the documentation. Since your library resides in a directory which should be in the standard library search path, you'd only need to define your library with the libraries option of the Extension class:
mymodule_ext = Extension('mymodule', ['mymodule.c'], libraries=['otherproject'])
If you're not using the standard lib* prefix you'd need to use libraries=[':otherproject.so'] instead.
Well, I have a Python package. I need to compile it as dll before distribute it in a way easily importable. How? You may suggest that *.pyc. But I read somewhere any *.pyc can be easily decompiled!
Update:
Follow these:
1) I wrote a python package
2) want to distribute it
3) do NOT want distribute the source
4) *.pyc is decompilable >> source can be extracted!
5) dll is standard
Write everything you want to hide in Cython, and compile it to pyd. That's as close as you can get to making compiled python code.
Also, dll is not a standard, not in Python world. They're not portable, either.
Nowadays a simple solutino exists: use Nuitka compiler as described in Nuitka User Manual
Use Case 2 - Extension Module compilation
If you want to compile a single extension module, all you have to do is this:
python -m nuitka --module some_module.py
The resulting file some_module.so can then be used instead of some_module.py.
You need to compile for each platform you want to support and write some initialization code to import so/pyd file ~~appropriate for given platform/python version etc.~~
[EDIT 2021-12]: Actually in python 3 the proper so/dll is determined automatically based on the file name (if it includes python version and platform - can't find PEP for this feature at the moment but Nuitka creates proper names for compiled modules). So for python 2.7 the library name would be something.pyd or something.so whereas for python 3 this would change to something.cp36-win32.pyd or something.cpython-36m-x86_64-linux-gnu.so (for 32bit python 3.6 on x86).
The result is not DLL as requested but Python-native compiled binary format (it is not bytecode like in pyc files; the so/pyd format cannot be easily decompiled - Nuitka compiles to machine code through C++ translation)
EDIT [2020-01]: The compiled module is prone to evaluation methods using python standard mechanisms - e.g. it can be imported as any other module and get its methods listed etc. To secure implementation from being exposed that way there is more work to be done than just compiling to a binary module.
You can use py2exe.org to convert python scripts into windows executables. Granted this will only work on windows, but it's better then nothing.
You can embed python inside C. The real trick is converting between C values and Python values. Once you've done that, though, making a DLL is pretty straightforward.
However, why do you need to make a dll? Do you need to use this from a non-python program?
Python embedding is supported in CFFI version 1.5, you can create a .dll file which can be used by a Windows C application.
I would also using Cython to generate pyd files, like Dikei wrote.
But if you really want to secure your code, you should better write the important stuff in C++. The best would be to combine both C++ and Python. The idea: you would leave the python code open for adjustments, so that you don't have to compile everything over and over again. That means, you would write the "core" in C++ (which is the most secure solution these days) and use those dll files in your python code. It really depends what kind of tool or program you are building and how you want to execute it. I create mostly an execution file (exe,app) once I finish a tool or a program, but this is more for the end user. This could be done with py2exe and py2app (both 64 bit compatible). If you implement the interpreter, the end user's machine doesn't have to have python installed on the system.
A pyd file is the same like a dll and fully supported inside python. So you can normally import your module. You can find more information about it here.
Using and generating pyd files is the fastest and easiest way to create safe and portable python code.
You could also write real dll files in C++ and import them with ctypes to use them (here a good post and here the python description of how it works)
To expand on the answer by Nick ODell
You must be on Windows for DLLs to work, they are not portable.
However the code below is cross platform and all platforms support run-times so this can be re-compiled for each platform you need it to work on.
Python does not (yet) provide an easy tool to create a dll, however you can do it in C/C++
First you will need a compiler (Windows does not have one by default) notably Cygwin, MinGW or Visual Studio.
A basic knowledge of C is also necessary (since we will be coding mainly in C).
You will also need to include the necessary headers, I will skip this so it does not become horribly long, and will assume everything is set up correctly.
For this demonstration I will print a traditional hello world:
Python code we will be converting to a DLL:
def foo(): print("hello world")
C code:
#include "Python.h" // Includes everything to use the Python-C API
int foo(void); // Declare foo
int foo(void) { // Name of our function in our DLL
Py_Initialize(); // Initialise Python
PyRun_SimpleString("print('hello world')"); // Run the Python commands
return 0; // Finish execution
}
Here is the tutorial for embedding Python. There are a few extra things that should be added here, but for brevity I have left those out.
Compile it and you should have a DLL. :)
That is not all. You will need to distribute whatever dependencies are needed, that will mean the python36.dll run-time and some other components to run the Python script.
My C coding is not perfect, so if anyone can spot any improvements please comment and I will do my best to fix the it.
It might also be possible in C# from this answer How do I call a specific Method from a Python Script in C#?, since C# can create DLLs, and you can call Python functions from C#.
You can use pyinstaller for converting the .py files into executable with all required packages into .dll format.
Step 1. pip install pyinstaller,
step 2. new python file let's name it code.py .
step 3. Write some lines of code i.e print("Hello World")
step 4. Open Command Prompt in the same location and write pyinstaller code.py hit enter. Last Step see in the same location two folders name build, dist will be created. inside dist folder there is folder code and inside that folder there is an exe file code.exe along with required .dll files.
If your only goal is to hide your source code, it is much simpler to just compile your code to an executable(use PyInstaller, for example), and use an module with readable source for communication.
NOTE: You might need more converter functions as shown in this example.
Example:
Module:
import subprocess
import codecs
def _encode_str(str):
encoded=str.encode("utf-32","surrogatepass")
return codecs.encode(encoded,"base64").replace(b"\n",b"")
def _decode_str(b64):
return codecs.decode(b64,"base64").decode("utf-32","surrogatepass")
def strlen(s:str):#return length of str;int
proc=subprocess.Popen(["path_to_your_exe.exe","strlen",_encode_str(str).decode("ascii")],stdout=subprocess.PIPE)
return int(proc.stdout.read())
def random_char_from_string(str):
proc=subprocess.Popen(["path_to_your_exe.exe","randchr",_encode_str(str).decode("ascii")],stdout=subprocess.PIPE)
return _decode_str(proc.stdout.read())
Executable:
import sys
import codecs
import random
def _encode_str(str):
encoded=str.encode("utf-32","surrogatepass")
return codecs.encode(encoded,"base64").replace(b"\n",b"")
def _decode_str(b64):
return codecs.decode(b64,"base64").decode("utf-32","surrogatepass")
command=sys.argv[1]
if command=="strlen":
s=_decode_str(sys.argv[2].encode("ascii"))
print(len(str))
if command=="randchr":
s_decode_str(sys.argv[2].encode("ascii"))
print(_encode_str(random.choice(s)).decode("ascii"))
You might also want to think about compiling different executables for different platforms, if your package isn't a windows-only package anyways.
This is my idea, it might work. I don't know, if that work or not.
1.Create your *.py files.
2.Rename them into *.pyx
3.Convert them into *.c files using Cython
4.Compile *.c into *.dll files.
But I don't recommend you because it won't work on any other platforms, except Windows.
Grab Visual Studio Express and IronPython and do it that way? You'll be in Python 2.7.6 world though.