I know that it is possible to write bash extension modules (loadable builtins) on C or lua (see luabash), but is it possible on Python/Cython? Is there any projects that make steps in this direction?
The way you would probably do this is start out with a C library which includes the appropriate exported functions, then within the exported function load and run the python interpreter, run your python code, then tear down the python interpreter.
You can see how to load the python interpreter into a C program/library here:
http://docs.python.org/extending/embedding.html
http://docs.python.org/extending/extending.html#calling-python-functions-from-c
http://www.linuxjournal.com/article/8497
If you do this a lot, then it may be simpler to write a single generic handler when you can use with multiple different python scripts.
I used Bash examples and the linked resources #tylerl mentioned to make bashpy. It's a proof of concept and currently lacks support for both passing variables and calling functions. So not very useful yet, but maybe it can help someone ending up here.
Related
Is there a way to add functions I create to the Python standard library on my local machine?
I come from the matlab world where things aren't really efficient and fast but there are looooads of functions at my fingertips without having to import their files. My problem is that, if I make a function in Python and want to use it, then i will need to also remember the module its in. My memory is shite. I understand that Python is structured that way for efficiency but if I'm adding only a handful of functions to the standard library that I consider very important, I'd guess that the impact to the performance is practically negligible.
Python has a namespace called __builtins__ in which you can stick stuff that you want available all the time. You probably shouldn't, but you can. Be careful not to clobber anything. Python won't stop you from using the same name as a built-in function, and if you do that, it'll probably break a lot of things.
# define function to always be available
def fart():
print("poot!")
__builtins__.fart = fart
# make re module always available without import
import re
__builtins__.re = re
Now the question is how to get Python to run that code for you each time you start up the interpreter. The answer is usercustomize.py. Follow these instructions to find out where the correct directory is on your machine, then put a new file called usercustomize.py in that directory that defines all the stuff you want to have in __builtins__.
There's also an environment variable, PYTHONSTARTUP, that you can set to have a Python script run whenever you start the interpreter in interactive mode (i.e. to a command prompt). I can see the benefit of e.g. having your favorite modules available when exploring in the REPL. More details here.
It sounds like you want to create your own packages & modules with tools you plan on using in the future on other projects. If that is the case, you want to look into the packaging your own project documentation:
https://packaging.python.org/tutorials/packaging-projects/
You may also find this useful:
How to install a Python package system-wide on Linux?
How to make my Python module available system wide on Linux?
How can I create a simple system wide python library?
I am using and maintaining a python script allowing to automatize compilation, execution and performances analysis of some particular applications. The script was quite simple when I created it (it only provided the compilation option) but is now very large (2100 lines, not optimized I agree), quite complex and providing many many different command line options (managing the arguments with argparse is a nightmare, and I am not able to do what I need exactly)
To simplify this, I am planning to split it in several scripts:
compile.py
run.py
analyse.py
These three scripts will need to access to share functions, classes and constants. Regarding this constraint, my question is what is the pyhtonic way to handle this ?
You can put the shared code in separate files and then import the file as a module in each script which needs it. To see how the module system in Python works, see the modules documentation for Python 2.7 or the documentation on modules for Python 3.4, depending on which version of Python you are writing code in.
I'm designing musical training games using JUCE -- a multiplatform C++ framework that allows me to code audio/visuals close to the wire.
However, I have coded my gameplay (control flow / data-processing) in Python -- it is complex and I wish to keep changing it so I can experiment with different gameplays. Python is ideal for this kind of rapid prototyping work.
So I would like my (platform independent, so Win/OSX/Lin/iOS/And) C++ to start up a Python runtime, feed it a .py file, and then call various functions in that .py. Also I would like to be able to call back to the C++ code from the .py.
Here is the relevant official Python documentation: https://docs.python.org/2/extending/extending.html
And here is a CodeProject article: http://www.codeproject.com/Articles/11805/Embedding-Python-in-C-C-Part-I
However, neither of them seem to address the issue of multiplatform.
The technique seems to be to link with the library libpython.a, and #include which contains the various functions for starting up the runtime environment, loading scripts, executing python-code, etc.
But surely this libpython.a would need to be compiled separately per platform? If so, this wouldn't be a very clean solution, so could I instead add the Python source code to my project and get it to compile the .a?
How can I go about doing this?
EDIT: https://wiki.python.org/moin/boost.python/EmbeddingPython
EDIT2: I'm pretty sure trying to bring in the full CPython source code is overkill here -- someone must have made some stripped down Python implementation in C/C++ that doesn't support any system-calls/multithreading/fancy-stuff -- just works through Python syntax line by line. Looking thru https://wiki.python.org/moin/PythonImplementations but I can't see an obvious candidate.
EDIT3: https://github.com/micropython/micropython should be added to that last page, but still it doesn't look like it is what I'm after
There's an entire chapter of the Python docs that explain the different approaches you can take embedding a Python interpreter into another app.
Embedding Python is similar to extending it, but not quite. The
difference is that when you extend Python, the main program of the
application is still the Python interpreter, while if you embed
Python, the main program may have nothing to do with Python — instead,
some parts of the application occasionally call the Python interpreter
to run some Python code.
So if you are embedding Python, you are providing your own main
program. One of the things this main program has to do is initialize
the Python interpreter. At the very least, you have to call the
function Py_Initialize(). There are optional calls to pass command
line arguments to Python. Then later you can call the interpreter from
any part of the application.
There are several different ways to call the interpreter: you can pass
a string containing Python statements to PyRun_SimpleString(), or you
can pass a stdio file pointer and a file name (for identification in
error messages only) to PyRun_SimpleFile(). You can also call the
lower-level operations described in the previous chapters to construct
and use Python objects.
A simple demo of embedding Python can be found in the directory
Demo/embed/ of the source distribution.
I recently decided to create a project that mixes C++ with Python, thus getting the best of both worlds. My idea was to do rapid prototyping of classes and functions in Python for obvious reasons, but still being able to call C++ code within Python (for obvious reasons as well). So instead of embedding Python in the C++ framework, I suggest you do the opposite: embed your C++ framework into a Python project. In order to do so, you just have to write very simple interface files and let Swig take care of the interfacing part.
If you want to start from scratch, there's a nice tool called cookiecutter that can be used to generate a project templates. You can choose either the cookiecutter-pypackage, or the cookiecutter-pylibrary, the latter improving over the former as described here. Interestingly, you can also use the cookiecutter code to generate the structure of a C++ project. This empty project uses the CMake build system, which IMHO is the best framework for developing platform independent C++ code. I then had to decide on the directory structure for this mixed project, so one of my previous posts describes this in detail. Good luck!
I'm using SWIG to embed Python into my C++ application, and to extend it as well, i.e. access my C++ API in Python outside my application. SWIG and Python are multi-platform, so that is not really an issue. One of the main advantage of SWIG is that it can generate bindings for a lot of languages. There are also a lot of C++ code wrappers that could be used, for example boost.python or cython.
Check these links on SO:
Extending python - to swig, not to swig or Cython
Exposing a C++ API to Python
Or you can go the hard way and use plain Python/C API.
I have an executable (face recognition) written by one of our programmers who's no longer with us. It takes a commandline argument and prints the result to STDOUT like this.
I need to be able to use this in Python but performance is important so I'm not sure if I should just use subprocess. I need to capture the output of the program so is it a better idea to modify the code to make it a C++ library instead and write a wrapper for it in Python? How would that impact performance compared to using subprocess?
I have looked into the Python docs for running C code and found this but the answer here is different. The second method does not even use Python.h so I'm a little confused. What's the best way to do what I need when performance is important?
At first I have to tell you I think subprocess method and running external application and reading output from STD output would be slow and unreliable. I won't recommend that method.
Instead, here is some suggestions:
You can create a Python extension in C or C++, you can find a lot of resources online about it. So you can convert your current code to Python extension format and just use Python extension skeleton template, integrate your functions and code in it and you'll have a python extension, simply you'll be able to call it's functions from Python code. See: http://docs.python.org/2/extending/index.html
Convert your current C++ code directly into a DLL and exports functions of your code you want to call from python if you are in Windows or simply convert it to a shared library if you are using Linux. It will be compiled to .so . Then you can call functions as an external library in your Python code. Example with explanation: http://www.linuxforu.com/2010/05/extending-python-via-shared-libraries/
I've never tried them, but it seems these projects can help you with what you want:
http://sourceforge.net/projects/pygccxml/?source=dlp
https://code.google.com/p/pybindgen/
http://www.cython.org/
I'm kinda new to scripting for IDA - nevertheless, I've written a complex script I need to debug, as it is not working properly.
It is composed of a few different files containing a few different classes.
Writing line-by-line in the commandline is not effective for obvious reasons.
Running a whole script from the File doesn't allow debugging.
Is there a way of using the idc, idautils, idaapi not from within IDA?
I've written the script on PyDev for Eclipse, I'm hoping for a way to run the scripts from within it.
A similar question is, can the api classes I have mentioned work on idb files without IDA having them loaded?
Thanks.
Now I may be wrong for I haven't written any IDA script for long time. But as far as I remember the answer to your first question is no. There is the part that loads the IDA script and prepare the whole environment so you could re implement it and create your own environment, however I would not recommend that.
What I can tell you is to consider running your script from command line if automation is what you are aiming for. IDA python (as well as any other IDA plugin) have a good support for running scripts from command line. For performance you can also run the TUI version of IDA.
There is also a hack for that enables you to launch a new python interpreter in the middle of the IDA script. It is useful for debugging a current state yet you will still need to edit the python file every time to launch the interpreter.
Here is the hack:
import code
all = globals()
all.update(locals())
code.interact(local = all)
Anyway - logs are good and debug prints are OK.
Good luck :)
We've just got a notice from one of our users that the latest version of WingIDE supports debugging of IDAPython scripts. I think there are a couple of other programs using the same approach (import a module to do RPC debugging) that might work.