Display context snippet for search phrase match optimisation request

[Follower]

Hi,

I am working on a function to return extracts from a text document
with a specific phrase highlighted (i.e. display the context of the
matched phrase).

The requirements are:

* Match should be case-insensitive, but extract should have case
preserved.

* The extract should show N words or characters of context on both
sides of the match.

* The phrase should be highlighted. i.e. Bracketed by arbitrary text
e.g. "<b>" & "</b>".

* The phrase is simple. e.g. "double" or "Another option"

* Only the first N matches should be returned.

* There will always be at least one match. (The extracts are only
requested if another process has determined a match exists in the
document.)

* The size of the text document varies from a few hundred
kilobytes to a little under 20 megabytes.

I've found two alternative methods (included below) and was wondering
if anyone had suggestions for improvements. One method uses the string
"index()" method and the other uses a regular expression.

As tested, there seems to be a lack of consistency in results, in
"real world" testing the regular expression seems to be faster most of
the time, but in "timeit" tests it almost always seems to considerably
slower which surprised me. I'm beginning to think the only time when
the regular expression method is faster is when the matches are near
the beginning of the document.

I'm using the Python Swish-E binding
<http://jibe.freeshell.org/bits/SwishE/> on Windows with Python 2.3.
The purpose of the code is to display context for each found document
(which is actually a PDF file with the content converted to text).

In "real world" practice for a set of fifteen results there's only
around two to five seconds difference between the two methods, so I
should probably stop worrying about it. I really just wanted to know
if any other approach is likely to be significantly better. And if
not, then anyone else can feel free to use this code.

--Phil.

# ========== Test Output ============

For the following test output:

"getNext_A" uses the "index()" string method.
"getNext_B" uses regular expressions.


# 17MB file with phrase "simply"
------ getNext_B ------
1.2671 sec/pass
126.72300005

------ getNext_A ------
0.5441 sec/pass
54.4189999104

# 17MB file with phrase "auckland"
------ getNext_B ------
0.0054 sec/pass
0.530999898911

------ getNext_A ------
0.4429 sec/pass
44.2940001488

# 132KB file with phrase "simply"
------ getNext_B ------
0.0111 sec/pass
1.12199997902

------ getNext_A ------
0.0041 sec/pass
0.411000013351

# 132KB file with phrase "auckland"
------ getNext_B ------
0.0109 sec/pass
1.10099983215

------ getNext_A ------
0.0041 sec/pass
0.411000013351


# ========== Script file "test_context.py" ============
# Remove first two comment characters in each line used to preserve
white space
# for Usenet post.

###!/usr/bin/python
##
##FILENAME = r"17MB_document.txt"
##
###PHRASE = "auckland"
###PHRASE = "simply"
##PHRASE = "proceedings"
##
##MAX_MATCHES = 7
##
##RANGE = 40
##
##
##def getNext_A(content, phrase, limit):
## """
## """
## lowContent = content.lower()
## lowPhrase = phrase.lower()
## phraseLen = len(phrase)
##
## idx = -1
## for matchCount in range(limit):
## try:
## idx = lowContent.index(lowPhrase, idx + 1)
## except ValueError:
## break
##
## yield (content[max([idx - RANGE, 0]): idx].lstrip(),
## content[idx: idx + phraseLen],
## content[idx + phraseLen : idx + phraseLen +
RANGE].rstrip())
##
##
##def getNext_B(content, phrase, limit):
## """
## """
## matcher = re.compile(phrase, re.IGNORECASE) # TODO: Escape
"phrase"?
##
## for match in itertools.islice(matcher.finditer(content), limit):
## start, end = match.span()
## yield (content[max([start - RANGE, 0]): start].lstrip(),
## content[start: end],
## content[end: end + RANGE].rstrip())
##
##
##def getContext(content, phrase, func):
## """
## """
## results = []
## for match in func(content, phrase, MAX_MATCHES):
## results.append("...%s<b>%s</b>%s..." % match)
## return "".join(results)
##
##
##import timeit
##import time
##if __name__ == "__main__":
## print
## content = open(FILENAME).read()
##
## for (f, n) in [(getNext_B, "getNext_B"), (getNext_A,
"getNext_A") ]:
## print "------ %s ------" % n
## ta = time.time()
##
## t = timeit.Timer(stmt="getContext(content, PHRASE, %s)" % n,
## setup="from __main__ import getContext,
content,
## PHRASE, getNext_A, getNext_B")
## print "%.4f sec/pass" % (t.timeit(number=100)/100)
##
## print time.time() - ta
##
## print
## #print getContext(content, PHRASE, f)