645 lines
24 KiB
Python
Executable File
645 lines
24 KiB
Python
Executable File
#! /usr/bin/env python
|
|
|
|
# Module ndiff version 1.5.0
|
|
# Released to the public domain 08-Oct-2000,
|
|
# by Tim Peters (tim_one@email.msn.com).
|
|
|
|
# Provided as-is; use at your own risk; no warranty; no promises; enjoy!
|
|
|
|
"""ndiff [-q] file1 file2
|
|
or
|
|
ndiff (-r1 | -r2) < ndiff_output > file1_or_file2
|
|
|
|
Print a human-friendly file difference report to stdout. Both inter-
|
|
and intra-line differences are noted. In the second form, recreate file1
|
|
(-r1) or file2 (-r2) on stdout, from an ndiff report on stdin.
|
|
|
|
In the first form, if -q ("quiet") is not specified, the first two lines
|
|
of output are
|
|
|
|
-: file1
|
|
+: file2
|
|
|
|
Each remaining line begins with a two-letter code:
|
|
|
|
"- " line unique to file1
|
|
"+ " line unique to file2
|
|
" " line common to both files
|
|
"? " line not present in either input file
|
|
|
|
Lines beginning with "? " attempt to guide the eye to intraline
|
|
differences, and were not present in either input file. These lines can be
|
|
confusing if the source files contain tab characters.
|
|
|
|
The first file can be recovered by retaining only lines that begin with
|
|
" " or "- ", and deleting those 2-character prefixes; use ndiff with -r1.
|
|
|
|
The second file can be recovered similarly, but by retaining only " " and
|
|
"+ " lines; use ndiff with -r2; or, on Unix, the second file can be
|
|
recovered by piping the output through
|
|
|
|
sed -n '/^[+ ] /s/^..//p'
|
|
|
|
See module comments for details and programmatic interface.
|
|
"""
|
|
|
|
__version__ = 1, 5, 0
|
|
|
|
# SequenceMatcher tries to compute a "human-friendly diff" between
|
|
# two sequences (chiefly picturing a file as a sequence of lines,
|
|
# and a line as a sequence of characters, here). Unlike e.g. UNIX(tm)
|
|
# diff, the fundamental notion is the longest *contiguous* & junk-free
|
|
# matching subsequence. That's what catches peoples' eyes. The
|
|
# Windows(tm) windiff has another interesting notion, pairing up elements
|
|
# that appear uniquely in each sequence. That, and the method here,
|
|
# appear to yield more intuitive difference reports than does diff. This
|
|
# method appears to be the least vulnerable to synching up on blocks
|
|
# of "junk lines", though (like blank lines in ordinary text files,
|
|
# or maybe "<P>" lines in HTML files). That may be because this is
|
|
# the only method of the 3 that has a *concept* of "junk" <wink>.
|
|
#
|
|
# Note that ndiff makes no claim to produce a *minimal* diff. To the
|
|
# contrary, minimal diffs are often counter-intuitive, because they
|
|
# synch up anywhere possible, sometimes accidental matches 100 pages
|
|
# apart. Restricting synch points to contiguous matches preserves some
|
|
# notion of locality, at the occasional cost of producing a longer diff.
|
|
#
|
|
# With respect to junk, an earlier version of ndiff simply refused to
|
|
# *start* a match with a junk element. The result was cases like this:
|
|
# before: private Thread currentThread;
|
|
# after: private volatile Thread currentThread;
|
|
# If you consider whitespace to be junk, the longest contiguous match
|
|
# not starting with junk is "e Thread currentThread". So ndiff reported
|
|
# that "e volatil" was inserted between the 't' and the 'e' in "private".
|
|
# While an accurate view, to people that's absurd. The current version
|
|
# looks for matching blocks that are entirely junk-free, then extends the
|
|
# longest one of those as far as possible but only with matching junk.
|
|
# So now "currentThread" is matched, then extended to suck up the
|
|
# preceding blank; then "private" is matched, and extended to suck up the
|
|
# following blank; then "Thread" is matched; and finally ndiff reports
|
|
# that "volatile " was inserted before "Thread". The only quibble
|
|
# remaining is that perhaps it was really the case that " volatile"
|
|
# was inserted after "private". I can live with that <wink>.
|
|
#
|
|
# NOTE on junk: the module-level names
|
|
# IS_LINE_JUNK
|
|
# IS_CHARACTER_JUNK
|
|
# can be set to any functions you like. The first one should accept
|
|
# a single string argument, and return true iff the string is junk.
|
|
# The default is whether the regexp r"\s*#?\s*$" matches (i.e., a
|
|
# line without visible characters, except for at most one splat).
|
|
# The second should accept a string of length 1 etc. The default is
|
|
# whether the character is a blank or tab (note: bad idea to include
|
|
# newline in this!).
|
|
#
|
|
# After setting those, you can call fcompare(f1name, f2name) with the
|
|
# names of the files you want to compare. The difference report
|
|
# is sent to stdout. Or you can call main(args), passing what would
|
|
# have been in sys.argv[1:] had the cmd-line form been used.
|
|
|
|
import string
|
|
TRACE = 0
|
|
|
|
# define what "junk" means
|
|
import re
|
|
|
|
def IS_LINE_JUNK(line, pat=re.compile(r"\s*#?\s*$").match):
|
|
return pat(line) is not None
|
|
|
|
def IS_CHARACTER_JUNK(ch, ws=" \t"):
|
|
return ch in ws
|
|
|
|
del re
|
|
|
|
class SequenceMatcher:
|
|
def __init__(self, isjunk=None, a='', b=''):
|
|
# Members:
|
|
# a
|
|
# first sequence
|
|
# b
|
|
# second sequence; differences are computed as "what do
|
|
# we need to do to 'a' to change it into 'b'?"
|
|
# b2j
|
|
# for x in b, b2j[x] is a list of the indices (into b)
|
|
# at which x appears; junk elements do not appear
|
|
# b2jhas
|
|
# b2j.has_key
|
|
# fullbcount
|
|
# for x in b, fullbcount[x] == the number of times x
|
|
# appears in b; only materialized if really needed (used
|
|
# only for computing quick_ratio())
|
|
# matching_blocks
|
|
# a list of (i, j, k) triples, where a[i:i+k] == b[j:j+k];
|
|
# ascending & non-overlapping in i and in j; terminated by
|
|
# a dummy (len(a), len(b), 0) sentinel
|
|
# opcodes
|
|
# a list of (tag, i1, i2, j1, j2) tuples, where tag is
|
|
# one of
|
|
# 'replace' a[i1:i2] should be replaced by b[j1:j2]
|
|
# 'delete' a[i1:i2] should be deleted
|
|
# 'insert' b[j1:j2] should be inserted
|
|
# 'equal' a[i1:i2] == b[j1:j2]
|
|
# isjunk
|
|
# a user-supplied function taking a sequence element and
|
|
# returning true iff the element is "junk" -- this has
|
|
# subtle but helpful effects on the algorithm, which I'll
|
|
# get around to writing up someday <0.9 wink>.
|
|
# DON'T USE! Only __chain_b uses this. Use isbjunk.
|
|
# isbjunk
|
|
# for x in b, isbjunk(x) == isjunk(x) but much faster;
|
|
# it's really the has_key method of a hidden dict.
|
|
# DOES NOT WORK for x in a!
|
|
|
|
self.isjunk = isjunk
|
|
self.a = self.b = None
|
|
self.set_seqs(a, b)
|
|
|
|
def set_seqs(self, a, b):
|
|
self.set_seq1(a)
|
|
self.set_seq2(b)
|
|
|
|
def set_seq1(self, a):
|
|
if a is self.a:
|
|
return
|
|
self.a = a
|
|
self.matching_blocks = self.opcodes = None
|
|
|
|
def set_seq2(self, b):
|
|
if b is self.b:
|
|
return
|
|
self.b = b
|
|
self.matching_blocks = self.opcodes = None
|
|
self.fullbcount = None
|
|
self.__chain_b()
|
|
|
|
# For each element x in b, set b2j[x] to a list of the indices in
|
|
# b where x appears; the indices are in increasing order; note that
|
|
# the number of times x appears in b is len(b2j[x]) ...
|
|
# when self.isjunk is defined, junk elements don't show up in this
|
|
# map at all, which stops the central find_longest_match method
|
|
# from starting any matching block at a junk element ...
|
|
# also creates the fast isbjunk function ...
|
|
# note that this is only called when b changes; so for cross-product
|
|
# kinds of matches, it's best to call set_seq2 once, then set_seq1
|
|
# repeatedly
|
|
|
|
def __chain_b(self):
|
|
# Because isjunk is a user-defined (not C) function, and we test
|
|
# for junk a LOT, it's important to minimize the number of calls.
|
|
# Before the tricks described here, __chain_b was by far the most
|
|
# time-consuming routine in the whole module! If anyone sees
|
|
# Jim Roskind, thank him again for profile.py -- I never would
|
|
# have guessed that.
|
|
# The first trick is to build b2j ignoring the possibility
|
|
# of junk. I.e., we don't call isjunk at all yet. Throwing
|
|
# out the junk later is much cheaper than building b2j "right"
|
|
# from the start.
|
|
b = self.b
|
|
self.b2j = b2j = {}
|
|
self.b2jhas = b2jhas = b2j.has_key
|
|
for i in xrange(len(b)):
|
|
elt = b[i]
|
|
if b2jhas(elt):
|
|
b2j[elt].append(i)
|
|
else:
|
|
b2j[elt] = [i]
|
|
|
|
# Now b2j.keys() contains elements uniquely, and especially when
|
|
# the sequence is a string, that's usually a good deal smaller
|
|
# than len(string). The difference is the number of isjunk calls
|
|
# saved.
|
|
isjunk, junkdict = self.isjunk, {}
|
|
if isjunk:
|
|
for elt in b2j.keys():
|
|
if isjunk(elt):
|
|
junkdict[elt] = 1 # value irrelevant; it's a set
|
|
del b2j[elt]
|
|
|
|
# Now for x in b, isjunk(x) == junkdict.has_key(x), but the
|
|
# latter is much faster. Note too that while there may be a
|
|
# lot of junk in the sequence, the number of *unique* junk
|
|
# elements is probably small. So the memory burden of keeping
|
|
# this dict alive is likely trivial compared to the size of b2j.
|
|
self.isbjunk = junkdict.has_key
|
|
|
|
def find_longest_match(self, alo, ahi, blo, bhi):
|
|
"""Find longest matching block in a[alo:ahi] and b[blo:bhi].
|
|
|
|
If isjunk is not defined:
|
|
|
|
Return (i,j,k) such that a[i:i+k] is equal to b[j:j+k], where
|
|
alo <= i <= i+k <= ahi
|
|
blo <= j <= j+k <= bhi
|
|
and for all (i',j',k') meeting those conditions,
|
|
k >= k'
|
|
i <= i'
|
|
and if i == i', j <= j'
|
|
In other words, of all maximal matching blocks, return one
|
|
that starts earliest in a, and of all those maximal matching
|
|
blocks that start earliest in a, return the one that starts
|
|
earliest in b.
|
|
|
|
If isjunk is defined, first the longest matching block is
|
|
determined as above, but with the additional restriction that
|
|
no junk element appears in the block. Then that block is
|
|
extended as far as possible by matching (only) junk elements on
|
|
both sides. So the resulting block never matches on junk except
|
|
as identical junk happens to be adjacent to an "interesting"
|
|
match.
|
|
|
|
If no blocks match, return (alo, blo, 0).
|
|
"""
|
|
|
|
# CAUTION: stripping common prefix or suffix would be incorrect.
|
|
# E.g.,
|
|
# ab
|
|
# acab
|
|
# Longest matching block is "ab", but if common prefix is
|
|
# stripped, it's "a" (tied with "b"). UNIX(tm) diff does so
|
|
# strip, so ends up claiming that ab is changed to acab by
|
|
# inserting "ca" in the middle. That's minimal but unintuitive:
|
|
# "it's obvious" that someone inserted "ac" at the front.
|
|
# Windiff ends up at the same place as diff, but by pairing up
|
|
# the unique 'b's and then matching the first two 'a's.
|
|
|
|
a, b, b2j, isbjunk = self.a, self.b, self.b2j, self.isbjunk
|
|
besti, bestj, bestsize = alo, blo, 0
|
|
# find longest junk-free match
|
|
# during an iteration of the loop, j2len[j] = length of longest
|
|
# junk-free match ending with a[i-1] and b[j]
|
|
j2len = {}
|
|
nothing = []
|
|
for i in xrange(alo, ahi):
|
|
# look at all instances of a[i] in b; note that because
|
|
# b2j has no junk keys, the loop is skipped if a[i] is junk
|
|
j2lenget = j2len.get
|
|
newj2len = {}
|
|
for j in b2j.get(a[i], nothing):
|
|
# a[i] matches b[j]
|
|
if j < blo:
|
|
continue
|
|
if j >= bhi:
|
|
break
|
|
k = newj2len[j] = j2lenget(j-1, 0) + 1
|
|
if k > bestsize:
|
|
besti, bestj, bestsize = i-k+1, j-k+1, k
|
|
j2len = newj2len
|
|
|
|
# Now that we have a wholly interesting match (albeit possibly
|
|
# empty!), we may as well suck up the matching junk on each
|
|
# side of it too. Can't think of a good reason not to, and it
|
|
# saves post-processing the (possibly considerable) expense of
|
|
# figuring out what to do with it. In the case of an empty
|
|
# interesting match, this is clearly the right thing to do,
|
|
# because no other kind of match is possible in the regions.
|
|
while besti > alo and bestj > blo and \
|
|
isbjunk(b[bestj-1]) and \
|
|
a[besti-1] == b[bestj-1]:
|
|
besti, bestj, bestsize = besti-1, bestj-1, bestsize+1
|
|
while besti+bestsize < ahi and bestj+bestsize < bhi and \
|
|
isbjunk(b[bestj+bestsize]) and \
|
|
a[besti+bestsize] == b[bestj+bestsize]:
|
|
bestsize = bestsize + 1
|
|
|
|
if TRACE:
|
|
print "get_matching_blocks", alo, ahi, blo, bhi
|
|
print " returns", besti, bestj, bestsize
|
|
return besti, bestj, bestsize
|
|
|
|
def get_matching_blocks(self):
|
|
if self.matching_blocks is not None:
|
|
return self.matching_blocks
|
|
self.matching_blocks = []
|
|
la, lb = len(self.a), len(self.b)
|
|
self.__helper(0, la, 0, lb, self.matching_blocks)
|
|
self.matching_blocks.append( (la, lb, 0) )
|
|
if TRACE:
|
|
print '*** matching blocks', self.matching_blocks
|
|
return self.matching_blocks
|
|
|
|
# builds list of matching blocks covering a[alo:ahi] and
|
|
# b[blo:bhi], appending them in increasing order to answer
|
|
|
|
def __helper(self, alo, ahi, blo, bhi, answer):
|
|
i, j, k = x = self.find_longest_match(alo, ahi, blo, bhi)
|
|
# a[alo:i] vs b[blo:j] unknown
|
|
# a[i:i+k] same as b[j:j+k]
|
|
# a[i+k:ahi] vs b[j+k:bhi] unknown
|
|
if k:
|
|
if alo < i and blo < j:
|
|
self.__helper(alo, i, blo, j, answer)
|
|
answer.append(x)
|
|
if i+k < ahi and j+k < bhi:
|
|
self.__helper(i+k, ahi, j+k, bhi, answer)
|
|
|
|
def ratio(self):
|
|
"""Return a measure of the sequences' similarity (float in [0,1]).
|
|
|
|
Where T is the total number of elements in both sequences, and
|
|
M is the number of matches, this is 2*M / T.
|
|
Note that this is 1 if the sequences are identical, and 0 if
|
|
they have nothing in common.
|
|
"""
|
|
|
|
matches = reduce(lambda sum, triple: sum + triple[-1],
|
|
self.get_matching_blocks(), 0)
|
|
return 2.0 * matches / (len(self.a) + len(self.b))
|
|
|
|
def quick_ratio(self):
|
|
"""Return an upper bound on ratio() relatively quickly."""
|
|
# viewing a and b as multisets, set matches to the cardinality
|
|
# of their intersection; this counts the number of matches
|
|
# without regard to order, so is clearly an upper bound
|
|
if self.fullbcount is None:
|
|
self.fullbcount = fullbcount = {}
|
|
for elt in self.b:
|
|
fullbcount[elt] = fullbcount.get(elt, 0) + 1
|
|
fullbcount = self.fullbcount
|
|
# avail[x] is the number of times x appears in 'b' less the
|
|
# number of times we've seen it in 'a' so far ... kinda
|
|
avail = {}
|
|
availhas, matches = avail.has_key, 0
|
|
for elt in self.a:
|
|
if availhas(elt):
|
|
numb = avail[elt]
|
|
else:
|
|
numb = fullbcount.get(elt, 0)
|
|
avail[elt] = numb - 1
|
|
if numb > 0:
|
|
matches = matches + 1
|
|
return 2.0 * matches / (len(self.a) + len(self.b))
|
|
|
|
def real_quick_ratio(self):
|
|
"""Return an upper bound on ratio() very quickly"""
|
|
la, lb = len(self.a), len(self.b)
|
|
# can't have more matches than the number of elements in the
|
|
# shorter sequence
|
|
return 2.0 * min(la, lb) / (la + lb)
|
|
|
|
def get_opcodes(self):
|
|
if self.opcodes is not None:
|
|
return self.opcodes
|
|
i = j = 0
|
|
self.opcodes = answer = []
|
|
for ai, bj, size in self.get_matching_blocks():
|
|
# invariant: we've pumped out correct diffs to change
|
|
# a[:i] into b[:j], and the next matching block is
|
|
# a[ai:ai+size] == b[bj:bj+size]. So we need to pump
|
|
# out a diff to change a[i:ai] into b[j:bj], pump out
|
|
# the matching block, and move (i,j) beyond the match
|
|
tag = ''
|
|
if i < ai and j < bj:
|
|
tag = 'replace'
|
|
elif i < ai:
|
|
tag = 'delete'
|
|
elif j < bj:
|
|
tag = 'insert'
|
|
if tag:
|
|
answer.append( (tag, i, ai, j, bj) )
|
|
i, j = ai+size, bj+size
|
|
# the list of matching blocks is terminated by a
|
|
# sentinel with size 0
|
|
if size:
|
|
answer.append( ('equal', ai, i, bj, j) )
|
|
return answer
|
|
|
|
# meant for dumping lines
|
|
def dump(tag, x, lo, hi):
|
|
for i in xrange(lo, hi):
|
|
print tag, x[i],
|
|
|
|
# figure out which mark to stick under characters in lines that
|
|
# have changed (blank = same, - = deleted, + = inserted, ^ = replaced)
|
|
_combine = { ' ': ' ',
|
|
'. ': '-',
|
|
' .': '+',
|
|
'..': '^' }
|
|
|
|
def plain_replace(a, alo, ahi, b, blo, bhi):
|
|
assert alo < ahi and blo < bhi
|
|
# dump the shorter block first -- reduces the burden on short-term
|
|
# memory if the blocks are of very different sizes
|
|
if bhi - blo < ahi - alo:
|
|
dump('+', b, blo, bhi)
|
|
dump('-', a, alo, ahi)
|
|
else:
|
|
dump('-', a, alo, ahi)
|
|
dump('+', b, blo, bhi)
|
|
|
|
# When replacing one block of lines with another, this guy searches
|
|
# the blocks for *similar* lines; the best-matching pair (if any) is
|
|
# used as a synch point, and intraline difference marking is done on
|
|
# the similar pair. Lots of work, but often worth it.
|
|
|
|
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 '-', '+', '?' triple 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`
|
|
la, lb = len(atags), len(btags)
|
|
if la < lb:
|
|
atags = atags + ' ' * (lb - la)
|
|
elif lb < la:
|
|
btags = btags + ' ' * (la - lb)
|
|
combined = map(lambda x,y: _combine[x+y], atags, btags)
|
|
printq(aelt, belt, string.rstrip(string.join(combined, '')))
|
|
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)
|
|
|
|
def fancy_helper(a, alo, ahi, b, blo, bhi):
|
|
if alo < ahi:
|
|
if blo < bhi:
|
|
fancy_replace(a, alo, ahi, b, blo, bhi)
|
|
else:
|
|
dump('-', a, alo, ahi)
|
|
elif blo < bhi:
|
|
dump('+', b, blo, bhi)
|
|
|
|
# Crap to deal with leading tabs in "?" output. Can hurt, but will
|
|
# probably help most of the time.
|
|
|
|
def printq(aline, bline, qline):
|
|
common = min(count_leading(aline, "\t"),
|
|
count_leading(bline, "\t"))
|
|
common = min(common, count_leading(qline[:common], " "))
|
|
qline = "\t" * common + qline[common:]
|
|
print '-', aline, '+', bline, '?', qline
|
|
|
|
def count_leading(line, ch):
|
|
i, n = 0, len(line)
|
|
while i < n and line[i] == ch:
|
|
i += 1
|
|
return i
|
|
|
|
def fail(msg):
|
|
import sys
|
|
out = sys.stderr.write
|
|
out(msg + "\n\n")
|
|
out(__doc__)
|
|
return 0
|
|
|
|
# open a file & return the file object; gripe and return 0 if it
|
|
# couldn't be opened
|
|
def fopen(fname):
|
|
try:
|
|
return open(fname, 'r')
|
|
except IOError, detail:
|
|
return fail("couldn't open " + fname + ": " + str(detail))
|
|
|
|
# open two files & spray the diff to stdout; return false iff a problem
|
|
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
|
|
|
|
# crack args (sys.argv[1:] is normal) & compare;
|
|
# return false iff a problem
|
|
|
|
def main(args):
|
|
import getopt
|
|
try:
|
|
opts, args = getopt.getopt(args, "qr:")
|
|
except getopt.error, detail:
|
|
return fail(str(detail))
|
|
noisy = 1
|
|
qseen = rseen = 0
|
|
for opt, val in opts:
|
|
if opt == "-q":
|
|
qseen = 1
|
|
noisy = 0
|
|
elif opt == "-r":
|
|
rseen = 1
|
|
whichfile = val
|
|
if qseen and rseen:
|
|
return fail("can't specify both -q and -r")
|
|
if rseen:
|
|
if args:
|
|
return fail("no args allowed with -r option")
|
|
if whichfile in "12":
|
|
restore(whichfile)
|
|
return 1
|
|
return fail("-r value must be 1 or 2")
|
|
if len(args) != 2:
|
|
return fail("need 2 filename args")
|
|
f1name, f2name = args
|
|
if noisy:
|
|
print '-:', f1name
|
|
print '+:', f2name
|
|
return fcompare(f1name, f2name)
|
|
|
|
def restore(which):
|
|
import sys
|
|
tag = {"1": "- ", "2": "+ "}[which]
|
|
prefixes = (" ", tag)
|
|
for line in sys.stdin.readlines():
|
|
if line[:2] in prefixes:
|
|
print line[2:],
|
|
|
|
if __name__ == '__main__':
|
|
import sys
|
|
args = sys.argv[1:]
|
|
if "-profile" in args:
|
|
import profile, pstats
|
|
args.remove("-profile")
|
|
statf = "ndiff.pro"
|
|
profile.run("main(args)", statf)
|
|
stats = pstats.Stats(statf)
|
|
stats.strip_dirs().sort_stats('time').print_stats()
|
|
else:
|
|
main(args)
|