I am right in the middle of doing text parsing so I used your example as a
mental exercise. :-)
Here's a NDFA for your text:
b 0 1-9 a-Z , . + - ' " \n
S0: S0 E E S1 E E E S3 E S2 E
S1: T1 E E S1 E E E E E E T1
S2: S2 E E S2 E E E E E T2 E
S3: T3 E E S3 E E E E E E T3
and the end-states are:
E: error in text
T1: You have the words: moo, cow
T2: You get "farmer john" (w quotes)
T3: You get zug
Can't gurantee that I did it right - I did it really quick - and it's
*specific* to your text string.
Now just need to hire a programmer to write some clean Python parsing code.
:-)
--
It's me
"Freddie" <[EMAIL PROTECTED]> wrote in message
news:[EMAIL PROTECTED]
> Happy new year! Since I have run out of alcohol, I'll ask a question that
I
> haven't really worked out an answer for yet. Is there an elegant way to
turn
> something like:
>
> > moo cow "farmer john" -zug
>
> into:
>
> ['moo', 'cow', 'farmer john'], ['zug']
>
> I'm trying to parse a search string so I can use it for SQL WHERE
constraints,
> preferably without horrifying regular expressions. Uhh yeah.
>
> From 2005,
> Freddie
>
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