[Tutor] Efficiency of Doxygen on Python vs C++?

[Stephen McInerney]

My friend clarifies: "It's not the efficiency of doxygen that's the 
question. The problem is that you can add fields to objects as you go in 
Python so you need to do a deep analysis of the code to determine the class 
structure which you don't have to do with C++ (or Java)."
He mentioned numbers like maybe ~20+x slower on lines-of-code for Python vs 
C++.
A second friend of mine who is an XML/Java enthusiast echoed similar 
comments about scalability in large builds with weakly-typed dynamic 
languages such as Python.

(I said "why doesn't doxygen have optional pragmas to annotate the type of 
tricky class members to the tool?")

Has anyone used Doxygen and can comment?

(Alan - their build setup was generating the docs every nightly build. Yes 
it sounds like overkill and an inefficient setup, but notwithstanding that 
I'm interested in the question as stands.)

Thanks,
Stephen

>"Stephen McInerney" <spmcinerney at hotmail.com> wrote
>
> > My friend said the runtime efficiency of Doxygen on his build was
> > much
> > worse on the Python code than the C++ code, i.e. it took ages to
> > parse
> > the Python code.
> >
> > Anyone agree/disagree, or have any efficiency tips on how to
> > structure
> > things for decent Doxygen performance?
>
>Until your post I had never heard of it.
>Having read the wiki article I gather its a Javadoc style
>documentation
>generator. Not being a fan of such beasts I doubt I'd be inclined to
>use
>it, but why is performamce an issue for a documentation generator?
>
>Presumably you only need to generate the documents periodically
>- say once a day - rather than with every build? In-code documentation
>is
>what is being used to create the docs so you can use that in day to
>day coding - one reason I find doc generators fairly useless!
>
>Documentation should be about what the comments don;t say not
>merely a comment and interface extraction. IMHO of course :-)
>
>Alan G.

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