PEP 3107 Function Annotations for review and comment

[John Roth]

BJörn Lindqvist wrote:
> On 12/29/06, Tony Lownds <tony at pagedna.com> wrote:
> > Rationale
> > =========
> >
> > Because Python's 2.x series lacks a standard way of annotating a
> > function's parameters and return values (e.g., with information about
> > what type a function's return value should be), a variety of tools
> > and libraries have appeared to fill this gap [#tailexamp]_.  Some
> > utilise the decorators introduced in "PEP 318", while others parse a
> > function's docstring, looking for annotations there.
> >
> > This PEP aims to provide a single, standard way of specifying this
> > information, reducing the confusion caused by the wide variation in
> > mechanism and syntax that has existed until this point.
>
> I think this rationale is very lacking and to weak for such a big
> change to Python. I definitely like to see it expanded.
>
> The reference links to two small libraries implementing type checking
> using decorators and doc strings. None of which to seem to be very
> popular in the Python community. Surely, those two libraries *alone*
> can't be enough of a motivation for this? To me, it is far from
> self-evident what purpose function annotations would serve.
>
> I also wonder why a very obtrusive syntax addition is needed when it
> clearly is possible to annotate functions in today's Python. Why is
> syntax better than just adding a function annotation decorator to the
> standard library?
>
>     @annotate(a = int, b = dict, c = int)
>     def foo(a, b, c = 5):
>         ...
>
> Are decorators too ugly?
>
> --
> mvh Björn

The problem I have with it is that it doesn't solve the problem
I've got, and I can see some user requests to use it rather than
the metadata solution I've got now in Python FIT. Neither do
decorators, by the way.

So, what are the problems I see?

First, it only handles functions/methods. Python FIT needs
metadata on properties and assignable/readable attributes
of all kinds. So in no sense is it a replacement. Parenthetically,
neither is the decorator facility, and for exactly the same reason.

Second, it has the potential to make reading the function
header difficult. In the languages I'm familiar with, static type
declarations are a very few, somewhat well chosen words.
In this proposal, it can be a general expression. In Python
FIT, that could well turn into a full blown dictionary with
multiple keys.

Third, it's half of a proposal. Type checking isn't the only use
for metadata about functions/methods, classes, properties
and other objects, and the notion that there are only going to
be a small number of non-intersecting libraries out there is
an abdication of responsibility to think this thing through.

I should note that there are quite a few packages out there
that use some form of annotation, be they comments
(like Ned Bachelder's coverage analyzer and the two
lint packages I'm aware of), docstrings, decorators or
auxilliary dictionarys (like Python FIT, and a possible
Python version of Naked Objects). They include a
fair number of documentation packages.

On a positive note, what I'd like is something similar to
Java's Javadoc, but a bit looser. It could be a comment
convention like Javadoc, but one that the compiler recognizes
and stashes in the compiled .pyc / .pyo file. Or it could have
different syntax. What is SHOULDN'T have is a mandatory tie
to function/method syntax.

Combined with a convention to identify which annotation
belongs to who, it could be a quite useful mechanism.
I, for one, have no difficulty with the notion of using someone
else's annotations if I can identify them unambiguously.

John Roth
Python FIT