Best practice for operations on streams of text
rent.lupin.road at gmail.com
Thu May 7 15:59:50 EDT 2009
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):
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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