I have a large set of real-world text that I need to pull words out of to input into a spell checker. I'd like to extract as many meaningful words as possible without too much noise. I know there's plenty of regex ninjas around here, so hopefully someone can help me out.
Currently I'm extracting all alphabetical sequences with '[a-z]+'
. This is an okay approximation, but it drags a lot of rubbish out with it.
Ideally I would like some regex (doesn't have to be pretty or efficient) that extracts all alphabetical sequences delimited by natural word separators (such as [/-_,.: ]
etc.), and ignores any alphabetical sequences with illegal bounds.
However I'd also be happy to just be able to get all alphabetical sequences that ARE NOT adjacent to a number. So for instance 'pie21'
would NOT extract 'pie'
, but 'http://foo.com'
would extract ['http', 'foo', 'com']
.
I tried lookahead
and lookbehind
assertions, but they were applied per-character (so for example re.findall('(?<!d)[a-z]+(?!d)', 'pie21')
would return 'pi'
when I want it to return nothing). I tried wrapping the alpha part as a term ((?:[a-z]+)
) but it didn't help.
More detail: The data is an email database, so it's mostly plain English with normal numbers, but occasionally there's rubbish strings like GIHQ4NWL0S5SCGBDD40ZXE5IDP13TYNEA
and AC7A21C0
that I'd like to ignore completely. I'm assuming any alphabetical sequence with a number in it is rubbish.
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