fenics team mailing list archive

[Johan Hake <johan.hake@xxxxxxxxx>]

On Sunday July 25 2010 13:25:25 Kristian Ølgaard wrote:
> On 25 July 2010 20:29, Johan Hake <johan.hake@xxxxxxxxx> wrote:
> > On Saturday July 24 2010 09:48:44 Kristian Ølgaard wrote:
> >> On 22 July 2010 20:10, Johan Hake <johan.hake@xxxxxxxxx> wrote:
> >> > On Monday July 19 2010 12:54:44 Kristian Oelgaard wrote:
> >> >> On 23 June 2010 15:35, Kristian Oelgaard <k.b.oelgaard@xxxxxxxxx> 
wrote:
> >> >> > On 23 June 2010 10:55, Kristian Oelgaard <k.b.oelgaard@xxxxxxxxx>
> > 
> > wrote:
> >> >> >> On 22 June 2010 19:03, Johan Hake <johan.hake@xxxxxxxxx> wrote:
> >> >> >>> On Tuesday June 22 2010 08:28:37 Kristian Oelgaard wrote:
> >> >> >>>> I've started writing the programmer's reference for FEniCS.
> >> >> >>>> One of the features that we decided on was that doc-strings for
> >> >> >>>> PyDOLFIN should be written and maintained as part of the
> >> >> >>>> documentation project and then added to the dolfin module on
> >> >> >>>> import.
> >> >> >>>> 
> >> >> >>>> I thought about doing this in the following way:
> >> >> >>>> 
> >> >> >>>> 1) Create a pseudo module 'dolfin-doc' which is a copy of the
> >> >> >>>> classes and functions in the 'real' dolfin module only it
> >> >> >>>> contains no code at all, just doc-strings. (This approach will
> >> >> >>>> also make it easy to create a script to check if all functions
> >> >> >>>> are documented or if any docs are obsolete).
> >> >> >>> 
> >> >> >>> Sounds good. I first thought of a structure (other than a dummy
> >> >> >>> class) that just mimics the class hierarchy, but in some way that
> >> >> >>> is what you actually suggests and it is probably as easy as
> >> >> >>> anything else.
> >> >> >>> 
> >> >> >>>> 2) Use the autodoc functionality of Sphinx to create parts of
> >> >> >>>> the documentation for functions and classes
> >> >> >>>> 
> >> >> >>>> 3) Manually add additional information (in the reST file) and
> >> >> >>>> links to other parts of the documentation like demos etc. This
> >> >> >>>> will not be available using help() in the Python interpreter.
> >> >> >>>> 
> >> >> >>>> 4) In the dolfin.__init__.py function import the 'dolfin-doc'
> >> >> >>>> module and copy the doc-strings from all classes and functions
> >> >> >>>> to the classes and functions in the real dolfin module as was
> >> >> >>>> suggested by Johan Hake.
> >> >> >>>> 
> >> >> >>>> The problem with this approach is that assigning to __doc__ is
> >> >> >>>> not permitted for objects of 'type' type.
> >> >> >>>> 
> >> >> >>> :(
> >> >> >>> 
> >> >> >>> I did not anticipate this. Not sure why this is. I have got the
> >> >> >>> impression that numpy get around this. They use numpydoc to
> >> >> >>> dynamically add their documentation. It makes heavy use of
> >> >> >>> sphinx, but I couldn't figure how they get around that __doc__
> >> >> >>> is read-only.
> >> >> >> 
> >> >> >> To me it looks like numpydoc is a Sphinx extension that translates
> >> >> >> the Numpy docstrings into something that Sphinx can understand,
> >> >> >> not the other way around which is what we want.
> >> >> >> 
> >> >> >> http://projects.scipy.org/numpy/browser/trunk/doc/sphinxext/README
> >> >> >> .tx t
> >> >> >> 
> >> >> >> So I think our best bet is to proceed with your suggestions below.
> >> >> >> 
> >> >> >> Kristian
> >> >> >> 
> >> >> >>> While it might be cool to look into what NumPy have done, (they
> >> >> >>> also define a pseudo classes, which they populate with
> >> >> >>> docstrings, (look into phantom_import.py), and they also define
> >> >> >>> some nice format for the reST used in the docstrings), I suggest
> >> >> >>> two things we can do:
> >> >> >>> 
> >> >> >>> 1) SWIG can generate docstrings. We do that allready using parsed
> >> >> >>> doxygen documentation. All of this is gathered in docstrings.i. I
> >> >> >>> suggest generating such a file from our documentation. We need to
> >> >> >>> turn of %feature("autodoc","1") in dolfin.i to get rid of the
> >> >> >>> long and sometimes faulty generated signatures.
> >> >> > 
> >> >> > I turns out that it's only the __doc__ of the class I can't assign
> >> >> > to, not the __doc__ of member functions (and regular functions). A
> >> >> > simpler solution (at least for me) is to parse the cpp.py module
> >> >> > once generated and substitute all docstrings of classes with the
> >> >> > docstrings from the dolfindoc module rather than creating the
> >> >> > docstrings.i file.
> >> >> > 
> >> >> > Then for the classes that we manually add we use the method you
> >> >> > described below, but only for class.__doc__ .
> >> >> > 
> >> >> > class Foo(object):
> >> >> >    __doc__ = dolfindoc.Foo.__doc__
> >> >> >    def bar(self):
> >> >> >        "this doc string will be substituted with the
> >> >> > dolfindoc.Foo.__dict__["bar"].__doc__."
> >> >> >        pass
> >> >> 
> >> >> Unfortunately it turned out I was too quick to make this conclusion.
> >> >> For instance,
> >> >> for the Swig generated class Mesh in the module cpp I can't assign to
> >> >> 
> >> >> Mesh.__doc__
> >> >> 
> >> >> because it is a 'type' object as pointed our earlier, I can assign
> >> >> to:
> >> >> 
> >> >> Mesh.__dict__["__init__"].__doc__
> >> >> 
> >> >> but not
> >> >> 
> >> >> Mesh.__dict__["size"].__doc__
> >> >> 
> >> >> along with practically all other member functions.
> >> >> 
> >> >> The reason is that Swig, after the class definitions does this:
> >> >> 
> >> >> Mesh.size = new_instancemethod(_cpp.Mesh_size,None,Mesh)
> >> >> 
> >> >> to which no assignment is possible.
> >> >> 'AttributeError: attribute '__doc__' of 'instancemethod' objects is
> >> >> not writable'
> >> >> The code in Mesh.size is already
> >> >> 
> >> >>     def size(self, *args):
> >> >>         return _cpp.Mesh_size(self, *args)
> >> >> 
> >> >> so why Swig overrides the method I don't know. If it didn't I could
> >> >> assign to the docstring.
> >> >> 
> >> >> Recall that my initial plan was to simply parse the cpp.py file and
> >> >> substitute the docstrings of all classes with what the pseudo module
> >> >> dolfindoc would define. However, that doesn't seem so practical
> >> >> anymore since I would need to also comment out all lines where
> >> >> instancemethods are being assigned to class members such that on
> >> >> import (in dolfin/__init__.py) I can loop classes and assign to
> >> >> function docstrings. This is of course possible but seems a bit
> >> >> awkward and I don't know what implications the commenting out of
> >> >> instancemethod assignment will have.
> >> >> As I see it, two solutions remain.
> >> >> 
> >> >> 1) Take the pseudo module dolfindoc from the FEniCS documentation and
> >> >> create a docstring.i generator. The script
> >> >> dolfin/dolfin/swig/generator.py should then try to import the
> >> >> dolfindoc module, if successful use that to create docstring.i,
> >> >> otherwise use the Doxy2SWIG generator.
> >> > 
> >> > I thought that you landed on this alternative. The point is to
> >> > generate a dosctrings.i file from the FEniCS documentation. Then for
> >> > the extended Python layer we can use a generated Python module to
> >> > assign the docstrings:
> >> > 
> >> >  class VariationalProblem(...):
> >> >     ...
> >> >     __doc__ generated_docstring_module.VariationalProblem.__doc__
> >> 
> >> This approach is getting more and more complicated; it turns out we
> >> also need to generate all the
> >> _post.i files to get the docstrings correct.
> > 
> > Do yo meen the extended python functions that resides in these files?
> 
> Yes, they will need a docstring too. But since Swig doesn't mess with
> these particular (member-) functions, it is actually possible to
> assign to __doc__ dynamically (on import) so maybe that would be an
> easier option.

How would you do that? I tried 

%extend dolfin::GenericVector
{
  %pythoncode
  %{
    def data(self):
        generated_docstring_module.GenericVector.data.__doc__
        return self._data()
  %}
}

But it was only possible to have a "real" string, not a variable that was a 
str. Not sure why...

> >> At this point it seems a
> >> lot easier to me to simply extend the Python layer with everything we
> >> want to have detailed documentation for and distribute the
> >> dolfindocstrings module with DOLFIN so we can do:
> >> 
> >> class VariationalProblem(...):
> >>      ...
> >>    __doc__ generated_docstring_module.VariationalProblem.__doc__
> >> 
> >> this way we handle the docstrings in a uniform way, else we need to
> >> generate docstrings.i for some functions, *_post.i files for other
> >> functions and STILL do the assign to __doc__ trick.
> >> 
> >> For functions that we don't extend in the Python layer we still have
> >> the oneliner docs from the header files extended with some random
> >> output from Swig.
> > 
> > How do we handle the documentation of the pure cpp classes, for example
> > cpp.Mesh?
> 
> For all functions/classes we put a docstring in the docstringsmodule
> and distribute this module with DOLFIN.

Ok
 
> The current approach that we're pursuing is:
> For the classes in cpp, we generate the docstrings.i,
> For add on functions in *_post.i we need to either generate *_post.i
> or assign to __doc__ of those particular functions on import.
> For classes functions in the Python layer we just assign to __doc__ in
> the definition of classes/functions.

Ok
 
> or as I suggested:
> 
> Extend the Python layer with whatever classes/functions that we want
> to have documented in detail and assign to __doc__ in the definitions.

Ok

Johan

> Kristian
> 
> > Johan
> > 
> >> Kristian
> >> 
> >> >> One question w.r.t this approach, when is docstrings.i being
> >> >> generated? I see it is distributed with DOLFIN but shouldn't it be
> >> >> generated everytime DOLFIN is rebuild with enablePython, or does
> >> >> enableDocs have to be switched on as well?
> >> > 
> >> > It is generated by running dolfin/swig/generate.py. It takes quite a
> >> > long time so I think it is good to pre-generate this in the
> >> > distribution.
> >> > 
> >> >> 2) Extend our Python layer with all functions and classes that we
> >> >> want to use the dolfindoc docstrings for.
> >> >> These should just be empty and redirect calls to classes and
> >> >> functions of the cpp. In dolfin/mesh/mesh.py:
> >> >> 
> >> >> class Mesh(cpp.Mesh):
> >> >>     def size(self):
> >> >>         try:
> >> >>             import dolfindoc.mesh.mesh
> >> >>             __doc__ = dolfindoc.mesh.mesh.Mesh.__doc__
> >> >>         except:
> >> >>             __doc__ = cpp.Mesh.__doc__
> >> >>         return cpp.Mesh.size()
> >> >> 
> >> >> An additional benefit of this approach is that the module structure
> >> >> can be identical to what we have in the _real_ DOLFIN, not as it is
> >> >> now where everything is dumped in the dolfin.cpp module.
> >> >> I don't know how much overhead this will create, alternatively we can
> >> >> skip the try/except clause and simply have the documentation as a
> >> >> dependency, or not add the docstrings for memberfunctions and add
> >> >> them later on import as was the original idea.
> >> > 
> >> > This sounds cumbersome and in the example above will the try: except
> >> > clause be called everytime size is called.
> >> > 
> >> > Johan
> >> > 
> >> >> Suggestions and comments are more than welcome!
> >> >> 
> >> >> Kristian
> >> >> 
> >> >> > then in dolfin/__init__.py we load the classes as we do now from
> >> >> > the dolfin module, and then iterate over all functions and member
> >> >> > functions and substitute docstrings from the dolfindoc module.
> >> >> > 
> >> >> > Kristian
> >> >> > 
> >> >> >>> 2) The added python classes and methods can be documented using
> >> >> >>> your suggested approach, but instead of adding the docstring
> >> >> >>> after class creation, do it during class (method or function)
> >> >> >>> creation, a la:
> >> >> >>> 
> >> >> >>>  class Foo(object):
> >> >> >>>      __doc__ = docstrings.Foo.__doc__
> >> >> >>>      ...
> >> >> >>> 
> >> >> >>> where docstrings is the generated module containing the
> >> >> >>> docstrings.
> >> >> >>> 
> >> >> >>> Johan
> >> >> >>> 
> >> >> >>>> In other words we can't assign to the __doc__ of
> >> >> >>>> 
> >> >> >>>> class Foo(object):
> >> >> >>>>     "Foo doc"
> >> >> >>>>     pass
> >> >> >>>> 
> >> >> >>>> Which is a new-style class and found in UFL and the SWIG code in
> >> >> >>>> DOLFIN.
> >> >> >>>> 
> >> >> >>>> It works fine for
> >> >> >>>> 
> >> >> >>>> def some_function(v):
> >> >> >>>>     "function doc"
> >> >> >>>>     return 2*v
> >> >> >>>> 
> >> >> >>>> and
> >> >> >>>> 
> >> >> >>>> class Bar:
> >> >> >>>>     "Bar doc"
> >> >> >>>>     pass
> >> >> >>>> 
> >> >> >>>> which is the old-style class often found in FFC.
> >> >> >>>> 
> >> >> >>>> Does anyone have a solution or comments to the above approach,
> >> >> >>>> or maybe we can do it in a completely different way.
> >> >> >>>> 
> >> >> >>>> I read about some workaround for the 'assign to __doc__'
> >> >> >>>> problem, but it doesn't seem that nice and it might be a
> >> >> >>>> problem to incorporate in the SWIG generated code?
> >> >> >>>> 
> >> >> >>>> http://stackoverflow.com/questions/71817/using-the-docstring-fro
> >> >> >>>> m-o ne- metho d-to-automatically-overwrite-that-of-another-me
> >> >> >>>> 
> >> >> >>>> 
> >> >> >>>> Kristian
> >> >> >>>> 
> >> >> >>>> _______________________________________________
> >> >> >>>> Mailing list: https://launchpad.net/~fenics
> >> >> >>>> Post to     : fenics@xxxxxxxxxxxxxxxxxxx
> >> >> >>>> Unsubscribe : https://launchpad.net/~fenics
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> >> >> 
> >> >> _______________________________________________
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> >> 
> >> _______________________________________________
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> 
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