def fcompare(f1name, f2name):
f1 = fopen(f1name)
f2 = fopen(f2name)
if not f1 or not f2:
return 0
a = f1.readlines()
f1.close()
b = f2.readlines()
f2.close()
cruncher = SequenceMatcher(IS_LINE_JUNK, a, b)
for tag, alo, ahi, blo, bhi in cruncher.get_opcodes():
if tag == 'replace':
fancy_replace(a, alo, ahi, b, blo, bhi)
elif tag == 'delete':
dump('-', a, alo, ahi)
elif tag == 'insert':
dump('+', b, blo, bhi)
elif tag == 'equal':
dump(' ', a, alo, ahi)
else:
raise ValueError, 'unknown tag ' + ` tag `
return 1
def fancy_replace(a, alo, ahi, b, blo, bhi):
if TRACE:
print '*** fancy_replace', alo, ahi, blo, bhi
dump('>', a, alo, ahi)
dump('<', b, blo, bhi)
# don't synch up unless the lines have a similarity score of at
# least cutoff; best_ratio tracks the best score seen so far
best_ratio, cutoff = 0.74, 0.75
cruncher = SequenceMatcher(IS_CHARACTER_JUNK)
eqi, eqj = None, None # 1st indices of equal lines (if any)
# search for the pair that matches best without being identical
# (identical lines must be junk lines, & we don't want to synch up
# on junk -- unless we have to)
for j in xrange(blo, bhi):
bj = b[j]
cruncher.set_seq2(bj)
for i in xrange(alo, ahi):
ai = a[i]
if ai == bj:
if eqi is None:
eqi, eqj = i, j
continue
cruncher.set_seq1(ai)
# computing similarity is expensive, so use the quick
# upper bounds first -- have seen this speed up messy
# compares by a factor of 3.
# note that ratio() is only expensive to compute the first
# time it's called on a sequence pair; the expensive part
# of the computation is cached by cruncher
if cruncher.real_quick_ratio() > best_ratio and \
cruncher.quick_ratio() > best_ratio and \
cruncher.ratio() > best_ratio:
best_ratio, best_i, best_j = cruncher.ratio(), i, j
if best_ratio < cutoff:
# no non-identical "pretty close" pair
if eqi is None:
# no identical pair either -- treat it as a straight replace
plain_replace(a, alo, ahi, b, blo, bhi)
return
# no close pair, but an identical pair -- synch up on that
best_i, best_j, best_ratio = eqi, eqj, 1.0
else:
# there's a close pair, so forget the identical pair (if any)
eqi = None
# a[best_i] very similar to b[best_j]; eqi is None iff they're not
# identical
if TRACE:
print '*** best_ratio', best_ratio, best_i, best_j
dump('>', a, best_i, best_i + 1)
dump('<', b, best_j, best_j + 1)
# pump out diffs from before the synch point
fancy_helper(a, alo, best_i, b, blo, best_j)
# do intraline marking on the synch pair
aelt, belt = a[best_i], b[best_j]
if eqi is None:
# pump out a '-', '?', '+', '?' quad for the synched lines
atags = btags = ""
cruncher.set_seqs(aelt, belt)
for tag, ai1, ai2, bj1, bj2 in cruncher.get_opcodes():
la, lb = ai2 - ai1, bj2 - bj1
if tag == 'replace':
atags = atags + '^' * la
btags = btags + '^' * lb
elif tag == 'delete':
atags = atags + '-' * la
elif tag == 'insert':
btags = btags + '+' * lb
elif tag == 'equal':
atags = atags + ' ' * la
btags = btags + ' ' * lb
else:
raise ValueError, 'unknown tag ' + ` tag `
printq(aelt, belt, atags, btags)
else:
# the synch pair is identical
print ' ', aelt,
# pump out diffs from after the synch point
fancy_helper(a, best_i + 1, ahi, b, best_j + 1, bhi)