On 20/05/13 14:49, Garth N. Wells wrote: > On 20 May 2013 14:33, Anders Logg <[email protected]> wrote: >> On Mon, May 20, 2013 at 01:09:20PM +0100, Garth N. Wells wrote: >>> On 20 May 2013 12:44, David Ham <[email protected]> wrote: >>>> Hi all, >>>> >>>> I'm writing Dolfin-compatible wrappers for PyOP2 as previously advertised >>>> at >>>> FEniCS '13, which is causing me to bump into one of the "interesting" >>>> quirks >>>> of the Python Dolfin API. Lots of things which would appear to naturally be >>>> properties are actually methods and have to be called to be accessed. For >>>> one among many, many examples, consider the value_size method of a >>>> Function. >>>> This is accessed with: >>>> >>>> f.value_size() >>>> >>>> while >>>> >>>> f.value_size >>>> >>>> would seem more natural. Given the existence of the @property decorator in >>>> standard Python which translates the former into the latter, this is >>>> particularly mysterious. Is there a reason why this is done in Dolfin? >>>> >>> >>> A few of us discussed this in January. I agree that the latter is cleaner. >>> >>> First point, the Python interface is largely generated automatically, >>> so that's our starting position. We would save on C++ code and get the >>> syntax ' f.value_size' in many cases by not accessing member data via >>> functions. I like skipping the function, and have been doing so lately >>> with new code. The issue we discussed in January was backwards >>> compatibility - we could make a lot of C++ changes to get the syntax >>> 'f.size', but users would have to update their code (this point >>> bothers me less than it does others :)). >>> >>> In some cases we need a method, e.g. to get the size of a vector from >>> a linear algebra backend. Storing the size in a wrapper is error >>> prone. >>> >>> In summary, the reason for the interface in some parts is >>> history/convention (with no technical reason), and in other cases it's >>> a method for technical reasons. We could move more towards direct >>> access to member data. >> >> I don't agree with these conlusions. >> >> The reasons for the use of methods are:
I think David didn't argue for direct access to member data (as in access to the C++ members), or in fact about changing the C++ layer at all. Rather we would like the semantic attribute access on Python layer provided by @property, which I think circumvents most of the issue Anders raises (note again I'm only talking about the Python interface): >> 1. Tradition: following some C++ guidelines we read 10 years back that >> member data should never be accessed directly. > > It's done at times in the STL, e.g std::pair. One reason of using @property is not accessing member data directly. >> 2. Safety: Being able to access member variables means they can be >> changed from the outside (for a non-const object). This might lead to >> all kinds of unwanted behavior. A member variable can rarely be >> changed safely without changing a whole bunch of other data. >> > > If the data must be hidden, then it can be hidden behind a function. > Otherwise, if the object is const, then member data cannot be changed > and only const functions can be called on the data. > Something that would make things cleaner around the code would be to > let more objects have immutable data (e.g., not allow Vector > resizing), which allows some member data to be made const. > > At present we have annoying code duplication in numerous classes to > provide const and non-const access functions. @property is read-only be default. You can also define a setter, which would then be able to take care of changing all the other data. >> 3. Consistency: Sometimes, there is no member data to be accessed but >> it gets computed or extracted by the accessor function. This means if >> we moved to more access of member data, there would be mix of both and >> it would be confusing and inconsistent. > > This is a major plus to accessing data directly. It makes explicit > that accessing a data member involves no computation. With @property you would keep the accessor function as it is but access it as if it were a property. In addition, if the access involves expensive computation that would only need to be done once, it can be cached directly on the attribute using e.g. cached_property: http://www.toofishes.net/blog/python-cached-property-decorator/ >> On top of theses strong reasons (2 + 3), we would also break the >> interface. > > Which is a drawback. Yes, also using @property would be an interface-breaking change. Florian > Garth > >> -- >> Anders > _______________________________________________ > fenics mailing list > [email protected] > http://fenicsproject.org/mailman/listinfo/fenics >
smime.p7s
Description: S/MIME Cryptographic Signature
_______________________________________________ fenics mailing list [email protected] http://fenicsproject.org/mailman/listinfo/fenics
