So while I was mowing my grass last night*, I got to thinking about Python 2.5's enhanced generators and how I hadn't tried them out yet. Here is a simple example that uses the consumer/pipeline model described in PEP 342.

__author__ = "Christian Wyglendowski" __license__ = "MIT" def consumer(func): """Automatically advance generator to 1st yield point - (from PEP 342)""" def wrapper(*args, **kw): gen = func(*args, **kw) gen.next() return gen wrapper.__name__ = func.__name__ wrapper.__dict__ = func.__dict__ wrapper.__doc__ = func.__doc__ return wrapper @consumer def reverser(next=None): """A string-reversing consumer""" t = yield if next: yield next.send("".join(reversed(t))) else: yield "".join(reversed(t)) def transformer(methodname, *args, **params): """Creates a consumer for the given string methodname. Passes *args and **params to the string method.""" @consumer def _transform(next=None): text = yield m = getattr(text, methodname) transformed = m(*args, **params) if next: yield next.send(transformed) else: yield transformed _transform.__name__ = methodname return _transform def transform(text, transformers): """Passes text through a list of transformers and returns the result.""" next = None for t in reversed(transformers): next = t(next) return next.send(text)

(Is this too much code for a blog post?)

So what can you do with all of that? Easily perform various combinations of string transformations!

In [1]: title = transformer('title') In [2]: transform('python', [title, reverser]) Out[2]: 'nohtyP' In [3]: transform('python', [reverser, title]) Out[3]: 'Nohtyp'

It's a fairly contrived example, but the concept of this pipeline of transformations (described in much more detail in PEP 342) is really pretty cool. An application applying a more advanced version of something like this could process it's output using a variety of plugins that a user enabled.

Here is one final example:

In [4]: decode = transformer('decode', 'utf-8') In [5]: replace = transformer('replace', unichr(347), 's') In [6]: encode = transformer('encode', 'utf-8') In [7]: transform('Chri\xc5\x9btian', [decode, replace, encode]) Out[7]: 'Christian'

Has anyone else seen any neat examples of PEP 342 in the wild?

cw

* I usually gravitate to thinking about some obscure programming paradigm or feature while I am mowing grass. I think it has to do with how exceptionally boring mowing is.

EDIT: I guess I could have made the generators, um, more generative, so they aren't simply one-shot function-like simpletons. Oh well.