Moved SequenceMatcher from ndiff into new std library module difflib.py.
Guido told me to do this <wink>.
Greatly expanded docstrings, and fleshed out with examples.
New std test.
Added new get_close_matches() function for ESR.
Needs docs, but LaTeXification of the module docstring is all it needs.
\CVS: ----------------------------------------------------------------------
diff --git a/Lib/difflib.py b/Lib/difflib.py
new file mode 100644
index 0000000..3997723
--- /dev/null
+++ b/Lib/difflib.py
@@ -0,0 +1,781 @@
+#! /usr/bin/env python
+
+"""
+Module difflib -- helpers for computing deltas between objects.
+
+Function get_close_matches(word, possibilities, n=3, cutoff=0.6):
+
+ Use SequenceMatcher to return list of the best "good enough" matches.
+
+ word is a sequence for which close matches are desired (typically a
+ string).
+
+ possibilities is a list of sequences against which to match word
+ (typically a list of strings).
+
+ Optional arg n (default 3) is the maximum number of close matches to
+ return. n must be > 0.
+
+ Optional arg cutoff (default 0.6) is a float in [0, 1]. Possibilities
+ that don't score at least that similar to word are ignored.
+
+ The best (no more than n) matches among the possibilities are returned
+ in a list, sorted by similarity score, most similar first.
+
+ >>> get_close_matches("appel", ["ape", "apple", "peach", "puppy"])
+ ['apple', 'ape']
+ >>> import keyword
+ >>> get_close_matches("wheel", keyword.kwlist)
+ ['while']
+ >>> get_close_matches("apple", keyword.kwlist)
+ []
+ >>> get_close_matches("accept", keyword.kwlist)
+ ['except']
+
+Class SequenceMatcher
+
+SequenceMatcher is a flexible class for comparing pairs of sequences of any
+type, so long as the sequence elements are hashable. The basic algorithm
+predates, and is a little fancier than, an algorithm published in the late
+1980's by Ratcliff and Obershelp under the hyperbolic name "gestalt pattern
+matching". The basic idea is to find the longest contiguous matching
+subsequence that contains no "junk" elements (R-O doesn't address junk).
+The same idea is then applied recursively to the pieces of the sequences to
+the left and to the right of the matching subsequence. This does not yield
+minimal edit sequences, but does tend to yield matches that "look right"
+to people.
+
+Example, comparing two strings, and considering blanks to be "junk":
+
+>>> s = SequenceMatcher(lambda x: x == " ",
+... "private Thread currentThread;",
+... "private volatile Thread currentThread;")
+>>>
+
+.ratio() returns a float in [0, 1], measuring the "similarity" of the
+sequences. As a rule of thumb, a .ratio() value over 0.6 means the
+sequences are close matches:
+
+>>> print round(s.ratio(), 3)
+0.866
+>>>
+
+If you're only interested in where the sequences match,
+.get_matching_blocks() is handy:
+
+>>> for block in s.get_matching_blocks():
+... print "a[%d] and b[%d] match for %d elements" % block
+a[0] and b[0] match for 8 elements
+a[8] and b[17] match for 6 elements
+a[14] and b[23] match for 15 elements
+a[29] and b[38] match for 0 elements
+
+Note that the last tuple returned by .get_matching_blocks() is always a
+dummy, (len(a), len(b), 0), and this is the only case in which the last
+tuple element (number of elements matched) is 0.
+
+If you want to know how to change the first sequence into the second, use
+.get_opcodes():
+
+>>> for opcode in s.get_opcodes():
+... print "%6s a[%d:%d] b[%d:%d]" % opcode
+ equal a[0:8] b[0:8]
+insert a[8:8] b[8:17]
+ equal a[8:14] b[17:23]
+ equal a[14:29] b[23:38]
+
+See Tools/scripts/ndiff.py for a fancy human-friendly file differencer,
+which uses SequenceMatcher both to view files as sequences of lines, and
+lines as sequences of characters.
+
+See also function get_close_matches() in this module, which shows how
+simple code building on SequenceMatcher can be used to do useful work.
+
+Timing: Basic R-O is cubic time worst case and quadratic time expected
+case. SequenceMatcher is quadratic time worst case and has expected-case
+behavior dependent on how many elements the sequences have in common; best
+case time (no elements in common) is linear.
+
+SequenceMatcher methods:
+
+__init__(isjunk=None, a='', b='')
+ Construct a SequenceMatcher.
+
+ Optional arg isjunk is None (the default), or a one-argument function
+ that takes a sequence element and returns true iff the element is junk.
+ None is equivalent to passing "lambda x: 0", i.e. no elements are
+ considered to be junk. For examples, pass
+ lambda x: x in " \\t"
+ if you're comparing lines as sequences of characters, and don't want to
+ synch up on blanks or hard tabs.
+
+ Optional arg a is the first of two sequences to be compared. By
+ default, an empty string. The elements of a must be hashable.
+
+ Optional arg b is the second of two sequences to be compared. By
+ default, an empty string. The elements of b must be hashable.
+
+set_seqs(a, b)
+ Set the two sequences to be compared.
+
+ >>> s = SequenceMatcher()
+ >>> s.set_seqs("abcd", "bcde")
+ >>> s.ratio()
+ 0.75
+
+set_seq1(a)
+ Set the first sequence to be compared.
+
+ The second sequence to be compared is not changed.
+
+ >>> s = SequenceMatcher(None, "abcd", "bcde")
+ >>> s.ratio()
+ 0.75
+ >>> s.set_seq1("bcde")
+ >>> s.ratio()
+ 1.0
+ >>>
+
+ SequenceMatcher computes and caches detailed information about the
+ second sequence, so if you want to compare one sequence S against many
+ sequences, use .set_seq2(S) once and call .set_seq1(x) repeatedly for
+ each of the other sequences.
+
+ See also set_seqs() and set_seq2().
+
+set_seq2(b)
+ Set the second sequence to be compared.
+
+ The first sequence to be compared is not changed.
+
+ >>> s = SequenceMatcher(None, "abcd", "bcde")
+ >>> s.ratio()
+ 0.75
+ >>> s.set_seq2("abcd")
+ >>> s.ratio()
+ 1.0
+ >>>
+
+ SequenceMatcher computes and caches detailed information about the
+ second sequence, so if you want to compare one sequence S against many
+ sequences, use .set_seq2(S) once and call .set_seq1(x) repeatedly for
+ each of the other sequences.
+
+ See also set_seqs() and set_seq1().
+
+find_longest_match(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.
+
+ >>> s = SequenceMatcher(None, " abcd", "abcd abcd")
+ >>> s.find_longest_match(0, 5, 0, 9)
+ (0, 4, 5)
+
+ 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.
+
+ Here's the same example as before, but considering blanks to be junk.
+ That prevents " abcd" from matching the " abcd" at the tail end of the
+ second sequence directly. Instead only the "abcd" can match, and
+ matches the leftmost "abcd" in the second sequence:
+
+ >>> s = SequenceMatcher(lambda x: x==" ", " abcd", "abcd abcd")
+ >>> s.find_longest_match(0, 5, 0, 9)
+ (1, 0, 4)
+
+ If no blocks match, return (alo, blo, 0).
+
+ >>> s = SequenceMatcher(None, "ab", "c")
+ >>> s.find_longest_match(0, 2, 0, 1)
+ (0, 0, 0)
+
+get_matching_blocks()
+ Return list of triples describing matching subsequences.
+
+ Each triple is of the form (i, j, n), and means that
+ a[i:i+n] == b[j:j+n]. The triples are monotonically increasing in i
+ and in j.
+
+ The last triple is a dummy, (len(a), len(b), 0), and is the only triple
+ with n==0.
+
+ >>> s = SequenceMatcher(None, "abxcd", "abcd")
+ >>> s.get_matching_blocks()
+ [(0, 0, 2), (3, 2, 2), (5, 4, 0)]
+
+get_opcodes()
+ Return list of 5-tuples describing how to turn a into b.
+
+ Each tuple is of the form (tag, i1, i2, j1, j2). The first tuple has
+ i1 == j1 == 0, and remaining tuples have i1 == the i2 from the tuple
+ preceding it, and likewise for j1 == the previous j2.
+
+ The tags are strings, with these meanings:
+
+ 'replace': a[i1:i2] should be replaced by b[j1:j2]
+ 'delete': a[i1:i2] should be deleted.
+ Note that j1==j2 in this case.
+ 'insert': b[j1:j2] should be inserted at a[i1:i1].
+ Note that i1==i2 in this case.
+ 'equal': a[i1:i2] == b[j1:j2]
+
+ >>> a = "qabxcd"
+ >>> b = "abycdf"
+ >>> s = SequenceMatcher(None, a, b)
+ >>> for tag, i1, i2, j1, j2 in s.get_opcodes():
+ ... print ("%7s a[%d:%d] (%s) b[%d:%d] (%s)" %
+ ... (tag, i1, i2, a[i1:i2], j1, j2, b[j1:j2]))
+ delete a[0:1] (q) b[0:0] ()
+ equal a[1:3] (ab) b[0:2] (ab)
+ replace a[3:4] (x) b[2:3] (y)
+ equal a[4:6] (cd) b[3:5] (cd)
+ insert a[6:6] () b[5:6] (f)
+
+ratio()
+ 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 2,0*M / T. Note that this is 1 if the
+ sequences are identical, and 0 if they have nothing in common.
+
+ .ratio() is expensive to compute if you haven't already computed
+ .get_matching_blocks() or .get_opcodes(), in which case you may want to
+ try .quick_ratio() or .real_quick_ratio() first to get an upper bound.
+
+ >>> s = SequenceMatcher(None, "abcd", "bcde")
+ >>> s.ratio()
+ 0.75
+ >>> s.quick_ratio()
+ 0.75
+ >>> s.real_quick_ratio()
+ 1.0
+
+quick_ratio()
+ Return an upper bound on .ratio() relatively quickly.
+
+ This isn't defined beyond that it is an upper bound on .ratio(), and
+ is faster to compute.
+
+real_quick_ratio():
+ Return an upper bound on ratio() very quickly.
+
+ This isn't defined beyond that it is an upper bound on .ratio(), and
+ is faster to compute than either .ratio() or .quick_ratio().
+"""
+
+TRACE = 0
+
+class SequenceMatcher:
+ def __init__(self, isjunk=None, a='', b=''):
+ """Construct a SequenceMatcher.
+
+ Optional arg isjunk is None (the default), or a one-argument
+ function that takes a sequence element and returns true iff the
+ element is junk. None is equivalent to passing "lambda x: 0", i.e.
+ no elements are considered to be junk. For examples, pass
+ lambda x: x in " \\t"
+ if you're comparing lines as sequences of characters, and don't
+ want to synch up on blanks or hard tabs.
+
+ Optional arg a is the first of two sequences to be compared. By
+ default, an empty string. The elements of a must be hashable. See
+ also .set_seqs() and .set_seq1().
+
+ Optional arg b is the second of two sequences to be compared. By
+ default, an empty string. The elements of a must be hashable. See
+ also .set_seqs() and .set_seq2().
+ """
+
+ # 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):
+ """Set the two sequences to be compared.
+
+ >>> s = SequenceMatcher()
+ >>> s.set_seqs("abcd", "bcde")
+ >>> s.ratio()
+ 0.75
+ """
+
+ self.set_seq1(a)
+ self.set_seq2(b)
+
+ def set_seq1(self, a):
+ """Set the first sequence to be compared.
+
+ The second sequence to be compared is not changed.
+
+ >>> s = SequenceMatcher(None, "abcd", "bcde")
+ >>> s.ratio()
+ 0.75
+ >>> s.set_seq1("bcde")
+ >>> s.ratio()
+ 1.0
+ >>>
+
+ SequenceMatcher computes and caches detailed information about the
+ second sequence, so if you want to compare one sequence S against
+ many sequences, use .set_seq2(S) once and call .set_seq1(x)
+ repeatedly for each of the other sequences.
+
+ See also set_seqs() and set_seq2().
+ """
+
+ if a is self.a:
+ return
+ self.a = a
+ self.matching_blocks = self.opcodes = None
+
+ def set_seq2(self, b):
+ """Set the second sequence to be compared.
+
+ The first sequence to be compared is not changed.
+
+ >>> s = SequenceMatcher(None, "abcd", "bcde")
+ >>> s.ratio()
+ 0.75
+ >>> s.set_seq2("abcd")
+ >>> s.ratio()
+ 1.0
+ >>>
+
+ SequenceMatcher computes and caches detailed information about the
+ second sequence, so if you want to compare one sequence S against
+ many sequences, use .set_seq2(S) once and call .set_seq1(x)
+ repeatedly for each of the other sequences.
+
+ See also set_seqs() and set_seq1().
+ """
+
+ 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.
+
+ >>> s = SequenceMatcher(None, " abcd", "abcd abcd")
+ >>> s.find_longest_match(0, 5, 0, 9)
+ (0, 4, 5)
+
+ 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.
+
+ Here's the same example as before, but considering blanks to be
+ junk. That prevents " abcd" from matching the " abcd" at the tail
+ end of the second sequence directly. Instead only the "abcd" can
+ match, and matches the leftmost "abcd" in the second sequence:
+
+ >>> s = SequenceMatcher(lambda x: x==" ", " abcd", "abcd abcd")
+ >>> s.find_longest_match(0, 5, 0, 9)
+ (1, 0, 4)
+
+ If no blocks match, return (alo, blo, 0).
+
+ >>> s = SequenceMatcher(None, "ab", "c")
+ >>> s.find_longest_match(0, 2, 0, 1)
+ (0, 0, 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):
+ """Return list of triples describing matching subsequences.
+
+ Each triple is of the form (i, j, n), and means that
+ a[i:i+n] == b[j:j+n]. The triples are monotonically increasing in
+ i and in j.
+
+ The last triple is a dummy, (len(a), len(b), 0), and is the only
+ triple with n==0.
+
+ >>> s = SequenceMatcher(None, "abxcd", "abcd")
+ >>> s.get_matching_blocks()
+ [(0, 0, 2), (3, 2, 2), (5, 4, 0)]
+ """
+
+ 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 get_opcodes(self):
+ """Return list of 5-tuples describing how to turn a into b.
+
+ Each tuple is of the form (tag, i1, i2, j1, j2). The first tuple
+ has i1 == j1 == 0, and remaining tuples have i1 == the i2 from the
+ tuple preceding it, and likewise for j1 == the previous j2.
+
+ The tags are strings, with these meanings:
+
+ 'replace': a[i1:i2] should be replaced by b[j1:j2]
+ 'delete': a[i1:i2] should be deleted.
+ Note that j1==j2 in this case.
+ 'insert': b[j1:j2] should be inserted at a[i1:i1].
+ Note that i1==i2 in this case.
+ 'equal': a[i1:i2] == b[j1:j2]
+
+ >>> a = "qabxcd"
+ >>> b = "abycdf"
+ >>> s = SequenceMatcher(None, a, b)
+ >>> for tag, i1, i2, j1, j2 in s.get_opcodes():
+ ... print ("%7s a[%d:%d] (%s) b[%d:%d] (%s)" %
+ ... (tag, i1, i2, a[i1:i2], j1, j2, b[j1:j2]))
+ delete a[0:1] (q) b[0:0] ()
+ equal a[1:3] (ab) b[0:2] (ab)
+ replace a[3:4] (x) b[2:3] (y)
+ equal a[4:6] (cd) b[3:5] (cd)
+ insert a[6:6] () b[5:6] (f)
+ """
+
+ 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
+
+ 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 2,0*M / T.
+ Note that this is 1 if the sequences are identical, and 0 if
+ they have nothing in common.
+
+ .ratio() is expensive to compute if you haven't already computed
+ .get_matching_blocks() or .get_opcodes(), in which case you may
+ want to try .quick_ratio() or .real_quick_ratio() first to get an
+ upper bound.
+
+ >>> s = SequenceMatcher(None, "abcd", "bcde")
+ >>> s.ratio()
+ 0.75
+ >>> s.quick_ratio()
+ 0.75
+ >>> s.real_quick_ratio()
+ 1.0
+ """
+
+ 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.
+
+ This isn't defined beyond that it is an upper bound on .ratio(), and
+ is faster to compute.
+ """
+
+ # 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.
+
+ This isn't defined beyond that it is an upper bound on .ratio(), and
+ is faster to compute than either .ratio() or .quick_ratio().
+ """
+
+ 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_close_matches(word, possibilities, n=3, cutoff=0.6):
+ """Use SequenceMatcher to return list of the best "good enough" matches.
+
+ word is a sequence for which close matches are desired (typically a
+ string).
+
+ possibilities is a list of sequences against which to match word
+ (typically a list of strings).
+
+ Optional arg n (default 3) is the maximum number of close matches to
+ return. n must be > 0.
+
+ Optional arg cutoff (default 0.6) is a float in [0, 1]. Possibilities
+ that don't score at least that similar to word are ignored.
+
+ The best (no more than n) matches among the possibilities are returned
+ in a list, sorted by similarity score, most similar first.
+
+ >>> get_close_matches("appel", ["ape", "apple", "peach", "puppy"])
+ ['apple', 'ape']
+ >>> import keyword
+ >>> get_close_matches("wheel", keyword.kwlist)
+ ['while']
+ >>> get_close_matches("apple", keyword.kwlist)
+ []
+ >>> get_close_matches("accept", keyword.kwlist)
+ ['except']
+ """
+
+ if not n > 0:
+ raise ValueError("n must be > 0: %s" % `n`)
+ if not 0.0 <= cutoff <= 1.0:
+ raise ValueError("cutoff must be in [0.0, 1.0]: %s" % `cutoff`)
+ result = []
+ s = SequenceMatcher()
+ s.set_seq2(word)
+ for x in possibilities:
+ s.set_seq1(x)
+ if s.real_quick_ratio() >= cutoff and \
+ s.quick_ratio() >= cutoff and \
+ s.ratio() >= cutoff:
+ result.append((s.ratio(), x))
+ # Sort by score.
+ result.sort()
+ # Retain only the best n.
+ result = result[-n:]
+ # Move best-scorer to head of list.
+ result.reverse()
+ # Strip scores.
+ return [x for score, x in result]
+
+def _test():
+ import doctest, difflib
+ return doctest.testmod(difflib)
+
+if __name__ == "__main__":
+ _test()
diff --git a/Lib/test/output/test_difflib b/Lib/test/output/test_difflib
new file mode 100644
index 0000000..0ea1048
--- /dev/null
+++ b/Lib/test/output/test_difflib
@@ -0,0 +1,280 @@
+test_difflib
+Running difflib.__doc__
+Trying: get_close_matches("appel", ["ape", "apple", "peach", "puppy"])
+Expecting: ['apple', 'ape']
+ok
+Trying: import keyword
+Expecting: nothing
+ok
+Trying: get_close_matches("wheel", keyword.kwlist)
+Expecting: ['while']
+ok
+Trying: get_close_matches("apple", keyword.kwlist)
+Expecting: []
+ok
+Trying: get_close_matches("accept", keyword.kwlist)
+Expecting: ['except']
+ok
+Trying:
+s = SequenceMatcher(lambda x: x == " ",
+ "private Thread currentThread;",
+ "private volatile Thread currentThread;")
+Expecting: nothing
+ok
+Trying: print round(s.ratio(), 3)
+Expecting: 0.866
+ok
+Trying:
+for block in s.get_matching_blocks():
+ print "a[%d] and b[%d] match for %d elements" % block
+Expecting:
+a[0] and b[0] match for 8 elements
+a[8] and b[17] match for 6 elements
+a[14] and b[23] match for 15 elements
+a[29] and b[38] match for 0 elements
+ok
+Trying:
+for opcode in s.get_opcodes():
+ print "%6s a[%d:%d] b[%d:%d]" % opcode
+Expecting:
+ equal a[0:8] b[0:8]
+insert a[8:8] b[8:17]
+ equal a[8:14] b[17:23]
+ equal a[14:29] b[23:38]
+ok
+Trying: s = SequenceMatcher()
+Expecting: nothing
+ok
+Trying: s.set_seqs("abcd", "bcde")
+Expecting: nothing
+ok
+Trying: s.ratio()
+Expecting: 0.75
+ok
+Trying: s = SequenceMatcher(None, "abcd", "bcde")
+Expecting: nothing
+ok
+Trying: s.ratio()
+Expecting: 0.75
+ok
+Trying: s.set_seq1("bcde")
+Expecting: nothing
+ok
+Trying: s.ratio()
+Expecting: 1.0
+ok
+Trying: s = SequenceMatcher(None, "abcd", "bcde")
+Expecting: nothing
+ok
+Trying: s.ratio()
+Expecting: 0.75
+ok
+Trying: s.set_seq2("abcd")
+Expecting: nothing
+ok
+Trying: s.ratio()
+Expecting: 1.0
+ok
+Trying: s = SequenceMatcher(None, " abcd", "abcd abcd")
+Expecting: nothing
+ok
+Trying: s.find_longest_match(0, 5, 0, 9)
+Expecting: (0, 4, 5)
+ok
+Trying: s = SequenceMatcher(lambda x: x==" ", " abcd", "abcd abcd")
+Expecting: nothing
+ok
+Trying: s.find_longest_match(0, 5, 0, 9)
+Expecting: (1, 0, 4)
+ok
+Trying: s = SequenceMatcher(None, "ab", "c")
+Expecting: nothing
+ok
+Trying: s.find_longest_match(0, 2, 0, 1)
+Expecting: (0, 0, 0)
+ok
+Trying: s = SequenceMatcher(None, "abxcd", "abcd")
+Expecting: nothing
+ok
+Trying: s.get_matching_blocks()
+Expecting: [(0, 0, 2), (3, 2, 2), (5, 4, 0)]
+ok
+Trying: a = "qabxcd"
+Expecting: nothing
+ok
+Trying: b = "abycdf"
+Expecting: nothing
+ok
+Trying: s = SequenceMatcher(None, a, b)
+Expecting: nothing
+ok
+Trying:
+for tag, i1, i2, j1, j2 in s.get_opcodes():
+ print ("%7s a[%d:%d] (%s) b[%d:%d] (%s)" %
+ (tag, i1, i2, a[i1:i2], j1, j2, b[j1:j2]))
+Expecting:
+ delete a[0:1] (q) b[0:0] ()
+ equal a[1:3] (ab) b[0:2] (ab)
+replace a[3:4] (x) b[2:3] (y)
+ equal a[4:6] (cd) b[3:5] (cd)
+ insert a[6:6] () b[5:6] (f)
+ok
+Trying: s = SequenceMatcher(None, "abcd", "bcde")
+Expecting: nothing
+ok
+Trying: s.ratio()
+Expecting: 0.75
+ok
+Trying: s.quick_ratio()
+Expecting: 0.75
+ok
+Trying: s.real_quick_ratio()
+Expecting: 1.0
+ok
+0 of 36 examples failed in difflib.__doc__
+Running difflib.SequenceMatcher.__doc__
+0 of 0 examples failed in difflib.SequenceMatcher.__doc__
+Running difflib.SequenceMatcher.__init__.__doc__
+0 of 0 examples failed in difflib.SequenceMatcher.__init__.__doc__
+Running difflib.SequenceMatcher.find_longest_match.__doc__
+Trying: s = SequenceMatcher(None, " abcd", "abcd abcd")
+Expecting: nothing
+ok
+Trying: s.find_longest_match(0, 5, 0, 9)
+Expecting: (0, 4, 5)
+ok
+Trying: s = SequenceMatcher(lambda x: x==" ", " abcd", "abcd abcd")
+Expecting: nothing
+ok
+Trying: s.find_longest_match(0, 5, 0, 9)
+Expecting: (1, 0, 4)
+ok
+Trying: s = SequenceMatcher(None, "ab", "c")
+Expecting: nothing
+ok
+Trying: s.find_longest_match(0, 2, 0, 1)
+Expecting: (0, 0, 0)
+ok
+0 of 6 examples failed in difflib.SequenceMatcher.find_longest_match.__doc__
+Running difflib.SequenceMatcher.get_opcodes.__doc__
+Trying: a = "qabxcd"
+Expecting: nothing
+ok
+Trying: b = "abycdf"
+Expecting: nothing
+ok
+Trying: s = SequenceMatcher(None, a, b)
+Expecting: nothing
+ok
+Trying:
+for tag, i1, i2, j1, j2 in s.get_opcodes():
+ print ("%7s a[%d:%d] (%s) b[%d:%d] (%s)" %
+ (tag, i1, i2, a[i1:i2], j1, j2, b[j1:j2]))
+Expecting:
+ delete a[0:1] (q) b[0:0] ()
+ equal a[1:3] (ab) b[0:2] (ab)
+replace a[3:4] (x) b[2:3] (y)
+ equal a[4:6] (cd) b[3:5] (cd)
+ insert a[6:6] () b[5:6] (f)
+ok
+0 of 4 examples failed in difflib.SequenceMatcher.get_opcodes.__doc__
+Running difflib.SequenceMatcher.quick_ratio.__doc__
+0 of 0 examples failed in difflib.SequenceMatcher.quick_ratio.__doc__
+Running difflib.SequenceMatcher.set_seqs.__doc__
+Trying: s = SequenceMatcher()
+Expecting: nothing
+ok
+Trying: s.set_seqs("abcd", "bcde")
+Expecting: nothing
+ok
+Trying: s.ratio()
+Expecting: 0.75
+ok
+0 of 3 examples failed in difflib.SequenceMatcher.set_seqs.__doc__
+Running difflib.SequenceMatcher.set_seq2.__doc__
+Trying: s = SequenceMatcher(None, "abcd", "bcde")
+Expecting: nothing
+ok
+Trying: s.ratio()
+Expecting: 0.75
+ok
+Trying: s.set_seq2("abcd")
+Expecting: nothing
+ok
+Trying: s.ratio()
+Expecting: 1.0
+ok
+0 of 4 examples failed in difflib.SequenceMatcher.set_seq2.__doc__
+Running difflib.SequenceMatcher.set_seq1.__doc__
+Trying: s = SequenceMatcher(None, "abcd", "bcde")
+Expecting: nothing
+ok
+Trying: s.ratio()
+Expecting: 0.75
+ok
+Trying: s.set_seq1("bcde")
+Expecting: nothing
+ok
+Trying: s.ratio()
+Expecting: 1.0
+ok
+0 of 4 examples failed in difflib.SequenceMatcher.set_seq1.__doc__
+Running difflib.SequenceMatcher.get_matching_blocks.__doc__
+Trying: s = SequenceMatcher(None, "abxcd", "abcd")
+Expecting: nothing
+ok
+Trying: s.get_matching_blocks()
+Expecting: [(0, 0, 2), (3, 2, 2), (5, 4, 0)]
+ok
+0 of 2 examples failed in difflib.SequenceMatcher.get_matching_blocks.__doc__
+Running difflib.SequenceMatcher.real_quick_ratio.__doc__
+0 of 0 examples failed in difflib.SequenceMatcher.real_quick_ratio.__doc__
+Running difflib.SequenceMatcher.ratio.__doc__
+Trying: s = SequenceMatcher(None, "abcd", "bcde")
+Expecting: nothing
+ok
+Trying: s.ratio()
+Expecting: 0.75
+ok
+Trying: s.quick_ratio()
+Expecting: 0.75
+ok
+Trying: s.real_quick_ratio()
+Expecting: 1.0
+ok
+0 of 4 examples failed in difflib.SequenceMatcher.ratio.__doc__
+Running difflib.get_close_matches.__doc__
+Trying: get_close_matches("appel", ["ape", "apple", "peach", "puppy"])
+Expecting: ['apple', 'ape']
+ok
+Trying: import keyword
+Expecting: nothing
+ok
+Trying: get_close_matches("wheel", keyword.kwlist)
+Expecting: ['while']
+ok
+Trying: get_close_matches("apple", keyword.kwlist)
+Expecting: []
+ok
+Trying: get_close_matches("accept", keyword.kwlist)
+Expecting: ['except']
+ok
+0 of 5 examples failed in difflib.get_close_matches.__doc__
+4 items had no tests:
+ difflib.SequenceMatcher
+ difflib.SequenceMatcher.__init__
+ difflib.SequenceMatcher.quick_ratio
+ difflib.SequenceMatcher.real_quick_ratio
+9 items passed all tests:
+ 36 tests in difflib
+ 6 tests in difflib.SequenceMatcher.find_longest_match
+ 2 tests in difflib.SequenceMatcher.get_matching_blocks
+ 4 tests in difflib.SequenceMatcher.get_opcodes
+ 4 tests in difflib.SequenceMatcher.ratio
+ 4 tests in difflib.SequenceMatcher.set_seq1
+ 4 tests in difflib.SequenceMatcher.set_seq2
+ 3 tests in difflib.SequenceMatcher.set_seqs
+ 5 tests in difflib.get_close_matches
+68 tests in 13 items.
+68 passed and 0 failed.
+Test passed.
diff --git a/Lib/test/test_difflib.py b/Lib/test/test_difflib.py
new file mode 100644
index 0000000..b1bcbd8
--- /dev/null
+++ b/Lib/test/test_difflib.py
@@ -0,0 +1,2 @@
+import doctest, difflib
+doctest.testmod(difflib, verbose=1)