I often edit Glom’s .glade files by hand instead of using Glade (though that should get better now that we have a GtkSourceView catalog for Glade, and that Openismus is paying Tristan to do a little cleanup in Glade). But I often make mistakes, so I added some tests. These run when doing “make check”, for instance during “make distcheck”, thanks to the autotools’ lovely built-in features.

Here are links to the two tests, in case it’s useful to anybody else. Maybe other people have other useful tests?

• Check the glade files for validity (a Glade DTD would make this even better if someone can finish it)
• Check instantiation: Check that all top-level windows and dialogs can be instantiated and check that none have visible=true.?
  This is C++, with libxml++ and gtkmm, but it’s simple.
  It would need slightly cleverer code to get secondary top-level objects such as GtkAdjustments and GtkTreeBuffers, because gtk_builder_add_objects_from_file() fails unless you specify secondary objects explicitly. But we avoid using these in Glom, because it’s easy to break the code at runtime when one is added to the .glade file, and it’s less of a problem now that Glade doesn’t create them when the default values would be acceptable. Another workaround is to put all windows in their own .glade file, but that makes it hard to work with them all together in Glade.

Finally Figured Out boost::python

After lots of experimentation and two previous failed attempts, Glom now uses boost::python, with very little use of the nasty Python C API remaining. This should make it easier to add Python API to easily access and set field/record/table/database details from the Python that’s used in calculated fields or button scripts.

Useful Things I Now Know about boost::python

boost::python is no fun to get started with, but it’s now far easier for me to use than the Python C API.

I’ve mentioned the awful boost::python documentation before. Here are some essential things that I figured out, which are not really documented. This is thanks to helpful people on the boost::python mailing list. Corrections welcome – there’s so much here that some of it must be wrong.

None of this is very obvious or pleasant. If anyone had their first real C++ experience with boost::python then I’d forgive them for being put off C++ for good. I love C++ so that would be unfortunate.

“Converting” between C and C++ object types

C++ to C: To get the underlying PyObject* from a boost::python::object (awful docs), when you need to use a C function:

PyObject* cobject = theobject.ptr();

To test for a boost::python::object with a null underlying PyObject*, do:

if(cppobject.ptr())

Do not do if(cppobject). That tests if the python object is actually a boolean that is PyTrue.

C to C++: To get a boost::python::object for a PyObject*, when you received one from a C function, but you then need to use the result in a C++ function, or just want the improved memory management:

• If the C function gave you a reference that you should later unreference:

  boost::python::object cppobject( (boost::python::handle<>(cobject)) );

  (You need those extra brackets, for “interesting” compiler reasons.)

• Or, if you need to take a reference.

  boost::python::object cppobject(boost::python::borrowed(cobject));

  (Yes. that’s horrible too. I see no reason to expose boost::python::handle in the API.)

• However, you’ll need to use allow_null too to avoid exceptions if the PyObject* might be null. Well, any pointer could be null, so say hello to:

  boost::python::object cppobject(  (boost::python::handle<>(boost::python::allow_null(cobject))) );

  or

  boost::python::object(boost::python::borrowed(boost::python::allow_null(cobject)));

  (Shoot me now. No, reducing it to b::p::whatever is not a significant improvement.)
  I understand that a null PyObject* may sometimes be an exceptional unexpected event, but forcing the use of a try/catch by default just for a null pointer check is annoying. Explicit functions such as wrap() and wrap_not_null() would be so much easier.
  See the equivalent for gtkmm (plus calling reference() when necessary with non-widgets).

Using boost::python with your own wrapped C++ classes.

• To get a boost::python::object for an instance of your C++ class that you’ve wrapped for Python with boost::python::class, just do:

  boost::python::object obj(new YourWrappedClass);

• To get a C++ instance of your wrapped class from a boost::python::object, use boost::python::extract (as also mentioned generically below):

  boost::python::extract<MyClass*> extractor(cppobject);
  if(extractor.check()) myobject = extractor;

Others

• To get a C++ value out of a boost::python::object do, for instance:

  boost::python::extract<std::string> extractor(cppobject);
  if(extractor.check()) mystring = extractor;

  You can do

  mystring = boost::python::extract<std::string>(cppobject)

  without the check() but that will throw an exception if the underlying type is not really what you expect.

• boost::python likes to throw exceptions. I think it only ever throws boost::python::error_already_set, though the (Python) error is often not already set when it’s thrown. When the error is set, you’ll need to use Python C API to discover what it is.
• To provide [] syntax in python for your wrapped class, you’ll need to know how the C API works. Add this voodoo to your boot::python::class declaration:

  .def("__getitem__", &MyClass::getitem)
  .def("__len__", &MyClass::len)

  Those methods can then have signatures like this:

  boost::python::object getitem(const boost::python::object& cppitem);
  long len() const;

• To use Python date or time values, you will need to use C Python functions. For instance:

  PyObject* cobject = cppobject.ptr();
  int day = PyDateTime_GET_DAY(cobject);
  int month = PyDateTime_GET_MONTH(cobject);
  int year = PyDateTime_GET_YEAR(cobject) );

Boost has no .pc files

boost is a complete pain as a dependency. I understand that they don’t want to freeze API or ABI, because it’s a place for gradually improving API, though I think they should just have regular stable/devel phases with parallel installs. But I can’t forgive how difficult it is to get the header and linker options to use boost libraries. There are some m4 macros out there but they are hacky and fragile, and don’t actually work for boost::python. It shouldn’t be hard to provide pkg-config .pc files, so you wouldn’t need to do any compilation or linker checks in configure at all. I hacked some m4 code together based on some existing stuff, but I couldn’t recommend it.

So distro packagers won’t enjoy this new dependency. Sorry.

We (Openismus) recently got our GtkToolPalette widget into GTK+’s git master, to be seen in recent GTK+ 2.19 (unstable) tarballs. We haven’t had much extra time for this kind of thing, so I’m glad it’s finally done after being worked on now and then by Mathias Hasselmann, Jan Arne Petersen and Johannes Schmid. Thanks to Matthias Clasen for valuable reviewing and cleanup.

We hope that this can replace the hand-coded tool palette widgets in Glade and Gimp, as well as making this easier for new applications. It replaces EggToolPalette in libegg, where we started the work. Please take a look and report any problems. I’m already using it in a Glom branch.

Here’s the GTK+ API reference for GtkToolPalette. There’s a GtkToolPalette example in gtk-demo.

And here’s a little introductory Gtk::ToolPalette chapter I wrote for the gtkmm (C++) book. Note that gtkmm’s API reference for this is mostly empty, but fixed already in git.