Best practice for operations on streams of text

James at
Thu May 7 15:59:50 EDT 2009

Hello all,
I'm working on some NLP code - what I'm doing is passing a large
number of tokens through a number of filtering / processing steps.

The filters take a token as input, and may or may not yield a token as
a result. For example, I might have filters which lowercases the
input, filter out boring words and filter out duplicates chained

I originally had code like this:
for t0 in token_stream:
  for t1 in lowercase_token(t0):
    for t2 in remove_boring(t1):
      for t3 in remove_dupes(t2):
        yield t3

Apart from being ugly as sin, I only get one token out as
StopIteration is raised before the whole token stream is consumed.

Any suggestions on an elegant way to chain together a bunch of
generators, with processing steps in between?


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