1. Introduction¶
- This document is written for people already familiar with the Python/C API Reference Manual.
- The macros provided by the Hurricane Python/C API are written using the standard Python C/API. That is, you may not use them and write directly your functions with the original API or any mix between. You only have to respect some naming convention.
- Coriolis is build against Python 2.7.
1.1 First, A Disclaimer¶
The Hurricane Python/C++ API has been written about ten years ago, at a time my mastering of template programming was less than complete. This is why this interface is build with old fashioned C macro instead of C++ template.
It is my hope that at some point in the future I will have time to completly
rewrite it, borrowing the interface from boost::python
.
1.2 About Technical Choices¶
Some would say, why not use off the shelf wrappers like swig
or boost::python
, here are some clues.
Partial exposure of the C++ class tree. We expose at Python level C++ base classes, only if they provides common methods that we want to see. Otherwise, we just show them as base classes under Python. For instance
Library
is derived fromDBo
, but we won’t see it under Python.Bi-directional communication. When a Python object is deleted, the wrapper obviously has a pointer toward the underlying C++ object and is able to delete it. But, the reverse case can occurs, meaning that you have a C++ object wrapped in Python and the database delete the underlying object. The wrapped Python object must be informed that it no longer refer a valid C++ one. Moreover, as we do not control when Python objects gets deleteds (that is, when their reference count reaches zero), we can have valid Python object with a dangling C++ pointer. So our Python objects can be warned by the C++ objects that they are no longer valid and any other operation than the deletion should result in a severe non-blocking error.
To be precise, this apply to persistent object in the C++ database, like
Cell
,Net
,Instance
orComponent
. Short lived objects likeBox
orPoint
retains the classic Python behavior.Another aspect is that, for all derived
DBo
objects, one and only one Python object is associated. For one givenInstance
object we will always return the samePyInstance
object, thanks to the bi-directional link. Obviously, the reference count of thePyInstance
is managed accordingly. This mechanism is implemented by thePyInstance_Link()
function.Linking accross modules. As far as I understand, the wrappers are for monolithic libraries. That is, you wrap the entire library in one go. But Hurricane has a modular design, the core database then various tools. We do not, and cannot, have one gigantic wrapper that would encompass all the libraries in one go. We do one Python module for one C++ library.
This brings another issue, at Python level this time. The Python modules for the libraries have to share some functions. Python provides a mechanism to pass C function pointers accross modules, but I did found it cumbersome. Instead, all our modules are split in two:
- The first part contains the classic Python module code.
- The second part is to be put in a separate dynamic library that will hold the shared functions. The Python module is dynamically linked against that library like any other. And any other Python module requiring the functions will link against the associated shared library.
Each module file will be compiled twice, once to build the Python module (
__PYTHON_MODULE
is defined) and once to build the supporting shared library (__PYTHON_MODULE__
not defined). This tricky double compilation is taken care of though theadd_python_module
cmake
macro.For the core Hurricane library we will have:
Hurricane.so
the Python module (use with:import Hurricane
).libisobar.so.1.0
the supporting shared library.
The
PyLibrary.cpp
file will have the following structure:#include "hurricane/isobar/PyLibrary.h" namespace Isobar { extern "C" { #if defined(__PYTHON_MODULE__) // +=================================================================+ // | "PyLibrary" Python Module Code Part | // +=================================================================+ // // The classic part of a Python module. Goes into Hurricane.so. #else // End of Python Module Code Part. // x=================================================================x // | "PyLibrary" Shared Library Code Part | // x=================================================================x // // Functions here will be part of the associated shared library and // made available to all other Python modules. Goes into libisobar.so.1.0 # endif // Shared Library Code Part. } // extern "C". } // Isobar namespace.
This way, we do not rely upon a pointer transmission through Python modules, but directly uses linker capabilities.
1.3 Botched Design¶
The mechanism to compute the signature of a call to a Python function,
the __cs
object, is much too complex and, in fact, not needed.
At some point I may root it out, but it is used in so many places...
What I should have used the "O!"
capablity of PyArg_ParseTuple()
,
like in the code below:
static PyObject* PyContact_create ( PyObject*, PyObject *args )
{
Contact* contact = NULL;
HTRY
PyNet* pyNet = NULL;
PyLayer* pyLayer = NULL;
PyComponent* pyComponent = NULL;
DbU::Unit x = 0;
DbU::Unit y = 0;
DbU::Unit width = 0;
DbU::Unit height = 0;
if (PyArg_ParseTuple( args, "O!O!ll|ll:Contact.create"
, &PyTypeNet , &pyNet
, &PyTypeLayer, &pyLayer
, &x, &y, &width, &height)) {
contact = Contact::create( PYNET_O(pyNet), PYLAYER_O(pyLayer)
, x, y, width, height );
} else {
PyErr_Clear();
if (PyArg_ParseTuple( args, "O!O!ll|ll:Contact.create"
, &PyTypeComponent, &pyComponent
, &PyTypeLayer , &pyLayer
, &x, &y, &width, &height)) {
contact = Contact::create( PYCOMPONENT_O(pyComponent), PYLAYER_O(pyLayer)
, x, y, width, height );
} else {
PyErr_SetString( ConstructorError
, "invalid number of parameters for Contact constructor." );
return NULL;
}
}
HCATCH
return PyContact_Link( contact );
}