| #! /usr/bin/env python |
| |
| # Module ndiff version 1.6.0 |
| # Released to the public domain 08-Dec-2000, |
| # by Tim Peters (tim.one@home.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], |
| |
| 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 '-', '?', '+', '?' 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 += '^' * la |
| btags += '^' * lb |
| elif tag == 'delete': |
| atags += '-' * la |
| elif tag == 'insert': |
| btags += '+' * lb |
| elif tag == 'equal': |
| atags += ' ' * la |
| 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) |
| |
| 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, atags, btags): |
| common = min(count_leading(aline, "\t"), |
| count_leading(bline, "\t")) |
| common = min(common, count_leading(atags[:common], " ")) |
| print "-", aline, |
| if count_leading(atags, " ") < len(atags): |
| print "?", "\t" * common + atags[common:] |
| print "+", bline, |
| if count_leading(btags, " ") < len(btags): |
| print "?", "\t" * common + btags[common:] |
| |
| 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) |