| """ |
| 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. |
| |
| Function context_diff(a, b): |
| For two lists of strings, return a delta in context diff format. |
| |
| Function ndiff(a, b): |
| Return a delta: the difference between `a` and `b` (lists of strings). |
| |
| Function restore(delta, which): |
| Return one of the two sequences that generated an ndiff delta. |
| |
| Function unified_diff(a, b): |
| For two lists of strings, return a delta in unified diff format. |
| |
| Class SequenceMatcher: |
| A flexible class for comparing pairs of sequences of any type. |
| |
| Class Differ: |
| For producing human-readable deltas from sequences of lines of text. |
| |
| Class HtmlDiff: |
| For producing HTML side by side comparison with change highlights. |
| """ |
| |
| __all__ = ['get_close_matches', 'ndiff', 'restore', 'SequenceMatcher', |
| 'Differ','IS_CHARACTER_JUNK', 'IS_LINE_JUNK', 'context_diff', |
| 'unified_diff', 'HtmlDiff', 'Match'] |
| |
| import heapq |
| from collections import namedtuple as _namedtuple |
| |
| Match = _namedtuple('Match', 'a b size') |
| |
| def _calculate_ratio(matches, length): |
| if length: |
| return 2.0 * matches / length |
| return 1.0 |
| |
| 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. |
| |
| SequenceMatcher tries to compute a "human-friendly diff" between two |
| sequences. 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>. |
| |
| 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 21 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[8:29] b[17:38] |
| |
| See the Differ class for a fancy human-friendly file differencer, which |
| uses SequenceMatcher both to compare sequences of lines, and to compare |
| sequences of characters within similar (near-matching) lines. |
| |
| 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 for the worst case and has |
| expected-case behavior dependent in a complicated way on how many |
| elements the sequences have in common; best case time is linear. |
| |
| Methods: |
| |
| __init__(isjunk=None, a='', b='') |
| Construct a SequenceMatcher. |
| |
| set_seqs(a, b) |
| Set the two sequences to be compared. |
| |
| set_seq1(a) |
| Set the first sequence to be compared. |
| |
| set_seq2(b) |
| Set the second sequence to be compared. |
| |
| find_longest_match(alo, ahi, blo, bhi) |
| Find longest matching block in a[alo:ahi] and b[blo:bhi]. |
| |
| get_matching_blocks() |
| Return list of triples describing matching subsequences. |
| |
| get_opcodes() |
| Return list of 5-tuples describing how to turn a into b. |
| |
| ratio() |
| Return a measure of the sequences' similarity (float in [0,1]). |
| |
| quick_ratio() |
| Return an upper bound on .ratio() relatively quickly. |
| |
| real_quick_ratio() |
| Return an upper bound on ratio() very quickly. |
| """ |
| |
| def __init__(self, isjunk=None, a='', b='', autojunk=True): |
| """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 example, 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 b must be hashable. See |
| also .set_seqs() and .set_seq2(). |
| |
| Optional arg autojunk should be set to False to disable the |
| "automatic junk heuristic" that treats popular elements as junk |
| (see module documentation for more information). |
| """ |
| |
| # 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 and popular elements do not appear |
| # 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 "in self.bjunk". |
| # bjunk |
| # the items in b for which isjunk is True. |
| # bpopular |
| # nonjunk items in b treated as junk by the heuristic (if used). |
| |
| self.isjunk = isjunk |
| self.a = self.b = None |
| self.autojunk = autojunk |
| 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 ... |
| # b2j also does not contain entries for "popular" elements, meaning |
| # elements that account for more than 1 + 1% of the total elements, and |
| # when the sequence is reasonably large (>= 200 elements); this can |
| # be viewed as an adaptive notion of semi-junk, and yields an enormous |
| # speedup when, e.g., comparing program files with hundreds of |
| # instances of "return NULL;" ... |
| # 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 = {} |
| |
| for i, elt in enumerate(b): |
| indices = b2j.setdefault(elt, []) |
| indices.append(i) |
| |
| # Purge junk elements |
| self.bjunk = junk = set() |
| isjunk = self.isjunk |
| if isjunk: |
| for elt in b2j.keys(): |
| if isjunk(elt): |
| junk.add(elt) |
| for elt in junk: # separate loop avoids separate list of keys |
| del b2j[elt] |
| |
| # Purge popular elements that are not junk |
| self.bpopular = popular = set() |
| n = len(b) |
| if self.autojunk and n >= 200: |
| ntest = n // 100 + 1 |
| for elt, idxs in b2j.items(): |
| if len(idxs) > ntest: |
| popular.add(elt) |
| for elt in popular: # ditto; as fast for 1% deletion |
| del b2j[elt] |
| |
| 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) |
| Match(a=0, b=4, size=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) |
| Match(a=1, b=0, size=4) |
| |
| If no blocks match, return (alo, blo, 0). |
| |
| >>> s = SequenceMatcher(None, "ab", "c") |
| >>> s.find_longest_match(0, 2, 0, 1) |
| Match(a=0, b=0, size=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.bjunk.__contains__ |
| 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 range(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 |
| |
| # Extend the best by non-junk elements on each end. In particular, |
| # "popular" non-junk elements aren't in b2j, which greatly speeds |
| # the inner loop above, but also means "the best" match so far |
| # doesn't contain any junk *or* popular non-junk elements. |
| while besti > alo and bestj > blo and \ |
| not 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 \ |
| not isbjunk(b[bestj+bestsize]) and \ |
| a[besti+bestsize] == b[bestj+bestsize]: |
| bestsize += 1 |
| |
| # 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 |
| |
| return Match(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. New in Python 2.5, it's also guaranteed that if |
| (i, j, n) and (i', j', n') are adjacent triples in the list, and |
| the second is not the last triple in the list, then i+n != i' or |
| j+n != j'. IOW, adjacent triples never describe adjacent equal |
| blocks. |
| |
| The last triple is a dummy, (len(a), len(b), 0), and is the only |
| triple with n==0. |
| |
| >>> s = SequenceMatcher(None, "abxcd", "abcd") |
| >>> list(s.get_matching_blocks()) |
| [Match(a=0, b=0, size=2), Match(a=3, b=2, size=2), Match(a=5, b=4, size=0)] |
| """ |
| |
| if self.matching_blocks is not None: |
| return self.matching_blocks |
| la, lb = len(self.a), len(self.b) |
| |
| # This is most naturally expressed as a recursive algorithm, but |
| # at least one user bumped into extreme use cases that exceeded |
| # the recursion limit on their box. So, now we maintain a list |
| # ('queue`) of blocks we still need to look at, and append partial |
| # results to `matching_blocks` in a loop; the matches are sorted |
| # at the end. |
| queue = [(0, la, 0, lb)] |
| matching_blocks = [] |
| while queue: |
| alo, ahi, blo, bhi = queue.pop() |
| 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 k is 0, there was no matching block |
| matching_blocks.append(x) |
| if alo < i and blo < j: |
| queue.append((alo, i, blo, j)) |
| if i+k < ahi and j+k < bhi: |
| queue.append((i+k, ahi, j+k, bhi)) |
| matching_blocks.sort() |
| |
| # It's possible that we have adjacent equal blocks in the |
| # matching_blocks list now. Starting with 2.5, this code was added |
| # to collapse them. |
| i1 = j1 = k1 = 0 |
| non_adjacent = [] |
| for i2, j2, k2 in matching_blocks: |
| # Is this block adjacent to i1, j1, k1? |
| if i1 + k1 == i2 and j1 + k1 == j2: |
| # Yes, so collapse them -- this just increases the length of |
| # the first block by the length of the second, and the first |
| # block so lengthened remains the block to compare against. |
| k1 += k2 |
| else: |
| # Not adjacent. Remember the first block (k1==0 means it's |
| # the dummy we started with), and make the second block the |
| # new block to compare against. |
| if k1: |
| non_adjacent.append((i1, j1, k1)) |
| i1, j1, k1 = i2, j2, k2 |
| if k1: |
| non_adjacent.append((i1, j1, k1)) |
| |
| non_adjacent.append( (la, lb, 0) ) |
| self.matching_blocks = non_adjacent |
| return map(Match._make, self.matching_blocks) |
| |
| 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 get_grouped_opcodes(self, n=3): |
| """ Isolate change clusters by eliminating ranges with no changes. |
| |
| Return a generator of groups with up to n lines of context. |
| Each group is in the same format as returned by get_opcodes(). |
| |
| >>> from pprint import pprint |
| >>> a = list(map(str, range(1,40))) |
| >>> b = a[:] |
| >>> b[8:8] = ['i'] # Make an insertion |
| >>> b[20] += 'x' # Make a replacement |
| >>> b[23:28] = [] # Make a deletion |
| >>> b[30] += 'y' # Make another replacement |
| >>> pprint(list(SequenceMatcher(None,a,b).get_grouped_opcodes())) |
| [[('equal', 5, 8, 5, 8), ('insert', 8, 8, 8, 9), ('equal', 8, 11, 9, 12)], |
| [('equal', 16, 19, 17, 20), |
| ('replace', 19, 20, 20, 21), |
| ('equal', 20, 22, 21, 23), |
| ('delete', 22, 27, 23, 23), |
| ('equal', 27, 30, 23, 26)], |
| [('equal', 31, 34, 27, 30), |
| ('replace', 34, 35, 30, 31), |
| ('equal', 35, 38, 31, 34)]] |
| """ |
| |
| codes = self.get_opcodes() |
| if not codes: |
| codes = [("equal", 0, 1, 0, 1)] |
| # Fixup leading and trailing groups if they show no changes. |
| if codes[0][0] == 'equal': |
| tag, i1, i2, j1, j2 = codes[0] |
| codes[0] = tag, max(i1, i2-n), i2, max(j1, j2-n), j2 |
| if codes[-1][0] == 'equal': |
| tag, i1, i2, j1, j2 = codes[-1] |
| codes[-1] = tag, i1, min(i2, i1+n), j1, min(j2, j1+n) |
| |
| nn = n + n |
| group = [] |
| for tag, i1, i2, j1, j2 in codes: |
| # End the current group and start a new one whenever |
| # there is a large range with no changes. |
| if tag == 'equal' and i2-i1 > nn: |
| group.append((tag, i1, min(i2, i1+n), j1, min(j2, j1+n))) |
| yield group |
| group = [] |
| i1, j1 = max(i1, i2-n), max(j1, j2-n) |
| group.append((tag, i1, i2, j1 ,j2)) |
| if group and not (len(group)==1 and group[0][0] == 'equal'): |
| yield group |
| |
| 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 = sum(triple[-1] for triple in self.get_matching_blocks()) |
| return _calculate_ratio(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.__contains__, 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 _calculate_ratio(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 _calculate_ratio(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 as _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: %r" % (n,)) |
| if not 0.0 <= cutoff <= 1.0: |
| raise ValueError("cutoff must be in [0.0, 1.0]: %r" % (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)) |
| |
| # Move the best scorers to head of list |
| result = heapq.nlargest(n, result) |
| # Strip scores for the best n matches |
| return [x for score, x in result] |
| |
| def _count_leading(line, ch): |
| """ |
| Return number of `ch` characters at the start of `line`. |
| |
| Example: |
| |
| >>> _count_leading(' abc', ' ') |
| 3 |
| """ |
| |
| i, n = 0, len(line) |
| while i < n and line[i] == ch: |
| i += 1 |
| return i |
| |
| class Differ: |
| r""" |
| Differ is a class for comparing sequences of lines of text, and |
| producing human-readable differences or deltas. Differ uses |
| SequenceMatcher both to compare sequences of lines, and to compare |
| sequences of characters within similar (near-matching) lines. |
| |
| Each line of a Differ delta begins with a two-letter code: |
| |
| '- ' line unique to sequence 1 |
| '+ ' line unique to sequence 2 |
| ' ' line common to both sequences |
| '? ' line not present in either input sequence |
| |
| Lines beginning with '? ' attempt to guide the eye to intraline |
| differences, and were not present in either input sequence. These lines |
| can be confusing if the sequences contain tab characters. |
| |
| Note that Differ 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. |
| |
| Example: Comparing two texts. |
| |
| First we set up the texts, sequences of individual single-line strings |
| ending with newlines (such sequences can also be obtained from the |
| `readlines()` method of file-like objects): |
| |
| >>> text1 = ''' 1. Beautiful is better than ugly. |
| ... 2. Explicit is better than implicit. |
| ... 3. Simple is better than complex. |
| ... 4. Complex is better than complicated. |
| ... '''.splitlines(keepends=True) |
| >>> len(text1) |
| 4 |
| >>> text1[0][-1] |
| '\n' |
| >>> text2 = ''' 1. Beautiful is better than ugly. |
| ... 3. Simple is better than complex. |
| ... 4. Complicated is better than complex. |
| ... 5. Flat is better than nested. |
| ... '''.splitlines(keepends=True) |
| |
| Next we instantiate a Differ object: |
| |
| >>> d = Differ() |
| |
| Note that when instantiating a Differ object we may pass functions to |
| filter out line and character 'junk'. See Differ.__init__ for details. |
| |
| Finally, we compare the two: |
| |
| >>> result = list(d.compare(text1, text2)) |
| |
| 'result' is a list of strings, so let's pretty-print it: |
| |
| >>> from pprint import pprint as _pprint |
| >>> _pprint(result) |
| [' 1. Beautiful is better than ugly.\n', |
| '- 2. Explicit is better than implicit.\n', |
| '- 3. Simple is better than complex.\n', |
| '+ 3. Simple is better than complex.\n', |
| '? ++\n', |
| '- 4. Complex is better than complicated.\n', |
| '? ^ ---- ^\n', |
| '+ 4. Complicated is better than complex.\n', |
| '? ++++ ^ ^\n', |
| '+ 5. Flat is better than nested.\n'] |
| |
| As a single multi-line string it looks like this: |
| |
| >>> print(''.join(result), end="") |
| 1. Beautiful is better than ugly. |
| - 2. Explicit is better than implicit. |
| - 3. Simple is better than complex. |
| + 3. Simple is better than complex. |
| ? ++ |
| - 4. Complex is better than complicated. |
| ? ^ ---- ^ |
| + 4. Complicated is better than complex. |
| ? ++++ ^ ^ |
| + 5. Flat is better than nested. |
| |
| Methods: |
| |
| __init__(linejunk=None, charjunk=None) |
| Construct a text differencer, with optional filters. |
| |
| compare(a, b) |
| Compare two sequences of lines; generate the resulting delta. |
| """ |
| |
| def __init__(self, linejunk=None, charjunk=None): |
| """ |
| Construct a text differencer, with optional filters. |
| |
| The two optional keyword parameters are for filter functions: |
| |
| - `linejunk`: A function that should accept a single string argument, |
| and return true iff the string is junk. The module-level function |
| `IS_LINE_JUNK` may be used to filter out lines without visible |
| characters, except for at most one splat ('#'). It is recommended |
| to leave linejunk None; as of Python 2.3, the underlying |
| SequenceMatcher class has grown an adaptive notion of "noise" lines |
| that's better than any static definition the author has ever been |
| able to craft. |
| |
| - `charjunk`: A function that should accept a string of length 1. The |
| module-level function `IS_CHARACTER_JUNK` may be used to filter out |
| whitespace characters (a blank or tab; **note**: bad idea to include |
| newline in this!). Use of IS_CHARACTER_JUNK is recommended. |
| """ |
| |
| self.linejunk = linejunk |
| self.charjunk = charjunk |
| |
| def compare(self, a, b): |
| r""" |
| Compare two sequences of lines; generate the resulting delta. |
| |
| Each sequence must contain individual single-line strings ending with |
| newlines. Such sequences can be obtained from the `readlines()` method |
| of file-like objects. The delta generated also consists of newline- |
| terminated strings, ready to be printed as-is via the writeline() |
| method of a file-like object. |
| |
| Example: |
| |
| >>> print(''.join(Differ().compare('one\ntwo\nthree\n'.splitlines(True), |
| ... 'ore\ntree\nemu\n'.splitlines(True))), |
| ... end="") |
| - one |
| ? ^ |
| + ore |
| ? ^ |
| - two |
| - three |
| ? - |
| + tree |
| + emu |
| """ |
| |
| cruncher = SequenceMatcher(self.linejunk, a, b) |
| for tag, alo, ahi, blo, bhi in cruncher.get_opcodes(): |
| if tag == 'replace': |
| g = self._fancy_replace(a, alo, ahi, b, blo, bhi) |
| elif tag == 'delete': |
| g = self._dump('-', a, alo, ahi) |
| elif tag == 'insert': |
| g = self._dump('+', b, blo, bhi) |
| elif tag == 'equal': |
| g = self._dump(' ', a, alo, ahi) |
| else: |
| raise ValueError('unknown tag %r' % (tag,)) |
| |
| yield from g |
| |
| def _dump(self, tag, x, lo, hi): |
| """Generate comparison results for a same-tagged range.""" |
| for i in range(lo, hi): |
| yield '%s %s' % (tag, x[i]) |
| |
| def _plain_replace(self, 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: |
| first = self._dump('+', b, blo, bhi) |
| second = self._dump('-', a, alo, ahi) |
| else: |
| first = self._dump('-', a, alo, ahi) |
| second = self._dump('+', b, blo, bhi) |
| |
| for g in first, second: |
| yield from g |
| |
| def _fancy_replace(self, a, alo, ahi, b, blo, bhi): |
| r""" |
| When replacing one block of lines with another, search 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. |
| |
| Example: |
| |
| >>> d = Differ() |
| >>> results = d._fancy_replace(['abcDefghiJkl\n'], 0, 1, |
| ... ['abcdefGhijkl\n'], 0, 1) |
| >>> print(''.join(results), end="") |
| - abcDefghiJkl |
| ? ^ ^ ^ |
| + abcdefGhijkl |
| ? ^ ^ ^ |
| """ |
| |
| # 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(self.charjunk) |
| 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 range(blo, bhi): |
| bj = b[j] |
| cruncher.set_seq2(bj) |
| for i in range(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 |
| yield from self._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 |
| |
| # pump out diffs from before the synch point |
| yield from self._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 %r' % (tag,)) |
| yield from self._qformat(aelt, belt, atags, btags) |
| else: |
| # the synch pair is identical |
| yield ' ' + aelt |
| |
| # pump out diffs from after the synch point |
| yield from self._fancy_helper(a, best_i+1, ahi, b, best_j+1, bhi) |
| |
| def _fancy_helper(self, a, alo, ahi, b, blo, bhi): |
| g = [] |
| if alo < ahi: |
| if blo < bhi: |
| g = self._fancy_replace(a, alo, ahi, b, blo, bhi) |
| else: |
| g = self._dump('-', a, alo, ahi) |
| elif blo < bhi: |
| g = self._dump('+', b, blo, bhi) |
| |
| yield from g |
| |
| def _qformat(self, aline, bline, atags, btags): |
| r""" |
| Format "?" output and deal with leading tabs. |
| |
| Example: |
| |
| >>> d = Differ() |
| >>> results = d._qformat('\tabcDefghiJkl\n', '\tabcdefGhijkl\n', |
| ... ' ^ ^ ^ ', ' ^ ^ ^ ') |
| >>> for line in results: print(repr(line)) |
| ... |
| '- \tabcDefghiJkl\n' |
| '? \t ^ ^ ^\n' |
| '+ \tabcdefGhijkl\n' |
| '? \t ^ ^ ^\n' |
| """ |
| |
| # Can hurt, but will probably help most of the time. |
| common = min(_count_leading(aline, "\t"), |
| _count_leading(bline, "\t")) |
| common = min(common, _count_leading(atags[:common], " ")) |
| common = min(common, _count_leading(btags[:common], " ")) |
| atags = atags[common:].rstrip() |
| btags = btags[common:].rstrip() |
| |
| yield "- " + aline |
| if atags: |
| yield "? %s%s\n" % ("\t" * common, atags) |
| |
| yield "+ " + bline |
| if btags: |
| yield "? %s%s\n" % ("\t" * common, btags) |
| |
| # 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>. |
| |
| import re |
| |
| def IS_LINE_JUNK(line, pat=re.compile(r"\s*#?\s*$").match): |
| r""" |
| Return 1 for ignorable line: iff `line` is blank or contains a single '#'. |
| |
| Examples: |
| |
| >>> IS_LINE_JUNK('\n') |
| True |
| >>> IS_LINE_JUNK(' # \n') |
| True |
| >>> IS_LINE_JUNK('hello\n') |
| False |
| """ |
| |
| return pat(line) is not None |
| |
| def IS_CHARACTER_JUNK(ch, ws=" \t"): |
| r""" |
| Return 1 for ignorable character: iff `ch` is a space or tab. |
| |
| Examples: |
| |
| >>> IS_CHARACTER_JUNK(' ') |
| True |
| >>> IS_CHARACTER_JUNK('\t') |
| True |
| >>> IS_CHARACTER_JUNK('\n') |
| False |
| >>> IS_CHARACTER_JUNK('x') |
| False |
| """ |
| |
| return ch in ws |
| |
| |
| ######################################################################## |
| ### Unified Diff |
| ######################################################################## |
| |
| def _format_range_unified(start, stop): |
| 'Convert range to the "ed" format' |
| # Per the diff spec at http://www.unix.org/single_unix_specification/ |
| beginning = start + 1 # lines start numbering with one |
| length = stop - start |
| if length == 1: |
| return '{}'.format(beginning) |
| if not length: |
| beginning -= 1 # empty ranges begin at line just before the range |
| return '{},{}'.format(beginning, length) |
| |
| def unified_diff(a, b, fromfile='', tofile='', fromfiledate='', |
| tofiledate='', n=3, lineterm='\n'): |
| r""" |
| Compare two sequences of lines; generate the delta as a unified diff. |
| |
| Unified diffs are a compact way of showing line changes and a few |
| lines of context. The number of context lines is set by 'n' which |
| defaults to three. |
| |
| By default, the diff control lines (those with ---, +++, or @@) are |
| created with a trailing newline. This is helpful so that inputs |
| created from file.readlines() result in diffs that are suitable for |
| file.writelines() since both the inputs and outputs have trailing |
| newlines. |
| |
| For inputs that do not have trailing newlines, set the lineterm |
| argument to "" so that the output will be uniformly newline free. |
| |
| The unidiff format normally has a header for filenames and modification |
| times. Any or all of these may be specified using strings for |
| 'fromfile', 'tofile', 'fromfiledate', and 'tofiledate'. |
| The modification times are normally expressed in the ISO 8601 format. |
| |
| Example: |
| |
| >>> for line in unified_diff('one two three four'.split(), |
| ... 'zero one tree four'.split(), 'Original', 'Current', |
| ... '2005-01-26 23:30:50', '2010-04-02 10:20:52', |
| ... lineterm=''): |
| ... print(line) # doctest: +NORMALIZE_WHITESPACE |
| --- Original 2005-01-26 23:30:50 |
| +++ Current 2010-04-02 10:20:52 |
| @@ -1,4 +1,4 @@ |
| +zero |
| one |
| -two |
| -three |
| +tree |
| four |
| """ |
| |
| started = False |
| for group in SequenceMatcher(None,a,b).get_grouped_opcodes(n): |
| if not started: |
| started = True |
| fromdate = '\t{}'.format(fromfiledate) if fromfiledate else '' |
| todate = '\t{}'.format(tofiledate) if tofiledate else '' |
| yield '--- {}{}{}'.format(fromfile, fromdate, lineterm) |
| yield '+++ {}{}{}'.format(tofile, todate, lineterm) |
| |
| first, last = group[0], group[-1] |
| file1_range = _format_range_unified(first[1], last[2]) |
| file2_range = _format_range_unified(first[3], last[4]) |
| yield '@@ -{} +{} @@{}'.format(file1_range, file2_range, lineterm) |
| |
| for tag, i1, i2, j1, j2 in group: |
| if tag == 'equal': |
| for line in a[i1:i2]: |
| yield ' ' + line |
| continue |
| if tag in {'replace', 'delete'}: |
| for line in a[i1:i2]: |
| yield '-' + line |
| if tag in {'replace', 'insert'}: |
| for line in b[j1:j2]: |
| yield '+' + line |
| |
| |
| ######################################################################## |
| ### Context Diff |
| ######################################################################## |
| |
| def _format_range_context(start, stop): |
| 'Convert range to the "ed" format' |
| # Per the diff spec at http://www.unix.org/single_unix_specification/ |
| beginning = start + 1 # lines start numbering with one |
| length = stop - start |
| if not length: |
| beginning -= 1 # empty ranges begin at line just before the range |
| if length <= 1: |
| return '{}'.format(beginning) |
| return '{},{}'.format(beginning, beginning + length - 1) |
| |
| # See http://www.unix.org/single_unix_specification/ |
| def context_diff(a, b, fromfile='', tofile='', |
| fromfiledate='', tofiledate='', n=3, lineterm='\n'): |
| r""" |
| Compare two sequences of lines; generate the delta as a context diff. |
| |
| Context diffs are a compact way of showing line changes and a few |
| lines of context. The number of context lines is set by 'n' which |
| defaults to three. |
| |
| By default, the diff control lines (those with *** or ---) are |
| created with a trailing newline. This is helpful so that inputs |
| created from file.readlines() result in diffs that are suitable for |
| file.writelines() since both the inputs and outputs have trailing |
| newlines. |
| |
| For inputs that do not have trailing newlines, set the lineterm |
| argument to "" so that the output will be uniformly newline free. |
| |
| The context diff format normally has a header for filenames and |
| modification times. Any or all of these may be specified using |
| strings for 'fromfile', 'tofile', 'fromfiledate', and 'tofiledate'. |
| The modification times are normally expressed in the ISO 8601 format. |
| If not specified, the strings default to blanks. |
| |
| Example: |
| |
| >>> print(''.join(context_diff('one\ntwo\nthree\nfour\n'.splitlines(True), |
| ... 'zero\none\ntree\nfour\n'.splitlines(True), 'Original', 'Current')), |
| ... end="") |
| *** Original |
| --- Current |
| *************** |
| *** 1,4 **** |
| one |
| ! two |
| ! three |
| four |
| --- 1,4 ---- |
| + zero |
| one |
| ! tree |
| four |
| """ |
| |
| prefix = dict(insert='+ ', delete='- ', replace='! ', equal=' ') |
| started = False |
| for group in SequenceMatcher(None,a,b).get_grouped_opcodes(n): |
| if not started: |
| started = True |
| fromdate = '\t{}'.format(fromfiledate) if fromfiledate else '' |
| todate = '\t{}'.format(tofiledate) if tofiledate else '' |
| yield '*** {}{}{}'.format(fromfile, fromdate, lineterm) |
| yield '--- {}{}{}'.format(tofile, todate, lineterm) |
| |
| first, last = group[0], group[-1] |
| yield '***************' + lineterm |
| |
| file1_range = _format_range_context(first[1], last[2]) |
| yield '*** {} ****{}'.format(file1_range, lineterm) |
| |
| if any(tag in {'replace', 'delete'} for tag, _, _, _, _ in group): |
| for tag, i1, i2, _, _ in group: |
| if tag != 'insert': |
| for line in a[i1:i2]: |
| yield prefix[tag] + line |
| |
| file2_range = _format_range_context(first[3], last[4]) |
| yield '--- {} ----{}'.format(file2_range, lineterm) |
| |
| if any(tag in {'replace', 'insert'} for tag, _, _, _, _ in group): |
| for tag, _, _, j1, j2 in group: |
| if tag != 'delete': |
| for line in b[j1:j2]: |
| yield prefix[tag] + line |
| |
| def ndiff(a, b, linejunk=None, charjunk=IS_CHARACTER_JUNK): |
| r""" |
| Compare `a` and `b` (lists of strings); return a `Differ`-style delta. |
| |
| Optional keyword parameters `linejunk` and `charjunk` are for filter |
| functions (or None): |
| |
| - linejunk: A function that should accept a single string argument, and |
| return true iff the string is junk. The default is None, and is |
| recommended; as of Python 2.3, an adaptive notion of "noise" lines is |
| used that does a good job on its own. |
| |
| - charjunk: A function that should accept a string of length 1. The |
| default is module-level function IS_CHARACTER_JUNK, which filters out |
| whitespace characters (a blank or tab; note: bad idea to include newline |
| in this!). |
| |
| Tools/scripts/ndiff.py is a command-line front-end to this function. |
| |
| Example: |
| |
| >>> diff = ndiff('one\ntwo\nthree\n'.splitlines(keepends=True), |
| ... 'ore\ntree\nemu\n'.splitlines(keepends=True)) |
| >>> print(''.join(diff), end="") |
| - one |
| ? ^ |
| + ore |
| ? ^ |
| - two |
| - three |
| ? - |
| + tree |
| + emu |
| """ |
| return Differ(linejunk, charjunk).compare(a, b) |
| |
| def _mdiff(fromlines, tolines, context=None, linejunk=None, |
| charjunk=IS_CHARACTER_JUNK): |
| r"""Returns generator yielding marked up from/to side by side differences. |
| |
| Arguments: |
| fromlines -- list of text lines to compared to tolines |
| tolines -- list of text lines to be compared to fromlines |
| context -- number of context lines to display on each side of difference, |
| if None, all from/to text lines will be generated. |
| linejunk -- passed on to ndiff (see ndiff documentation) |
| charjunk -- passed on to ndiff (see ndiff documentation) |
| |
| This function returns an iterator which returns a tuple: |
| (from line tuple, to line tuple, boolean flag) |
| |
| from/to line tuple -- (line num, line text) |
| line num -- integer or None (to indicate a context separation) |
| line text -- original line text with following markers inserted: |
| '\0+' -- marks start of added text |
| '\0-' -- marks start of deleted text |
| '\0^' -- marks start of changed text |
| '\1' -- marks end of added/deleted/changed text |
| |
| boolean flag -- None indicates context separation, True indicates |
| either "from" or "to" line contains a change, otherwise False. |
| |
| This function/iterator was originally developed to generate side by side |
| file difference for making HTML pages (see HtmlDiff class for example |
| usage). |
| |
| Note, this function utilizes the ndiff function to generate the side by |
| side difference markup. Optional ndiff arguments may be passed to this |
| function and they in turn will be passed to ndiff. |
| """ |
| import re |
| |
| # regular expression for finding intraline change indices |
| change_re = re.compile('(\++|\-+|\^+)') |
| |
| # create the difference iterator to generate the differences |
| diff_lines_iterator = ndiff(fromlines,tolines,linejunk,charjunk) |
| |
| def _make_line(lines, format_key, side, num_lines=[0,0]): |
| """Returns line of text with user's change markup and line formatting. |
| |
| lines -- list of lines from the ndiff generator to produce a line of |
| text from. When producing the line of text to return, the |
| lines used are removed from this list. |
| format_key -- '+' return first line in list with "add" markup around |
| the entire line. |
| '-' return first line in list with "delete" markup around |
| the entire line. |
| '?' return first line in list with add/delete/change |
| intraline markup (indices obtained from second line) |
| None return first line in list with no markup |
| side -- indice into the num_lines list (0=from,1=to) |
| num_lines -- from/to current line number. This is NOT intended to be a |
| passed parameter. It is present as a keyword argument to |
| maintain memory of the current line numbers between calls |
| of this function. |
| |
| Note, this function is purposefully not defined at the module scope so |
| that data it needs from its parent function (within whose context it |
| is defined) does not need to be of module scope. |
| """ |
| num_lines[side] += 1 |
| # Handle case where no user markup is to be added, just return line of |
| # text with user's line format to allow for usage of the line number. |
| if format_key is None: |
| return (num_lines[side],lines.pop(0)[2:]) |
| # Handle case of intraline changes |
| if format_key == '?': |
| text, markers = lines.pop(0), lines.pop(0) |
| # find intraline changes (store change type and indices in tuples) |
| sub_info = [] |
| def record_sub_info(match_object,sub_info=sub_info): |
| sub_info.append([match_object.group(1)[0],match_object.span()]) |
| return match_object.group(1) |
| change_re.sub(record_sub_info,markers) |
| # process each tuple inserting our special marks that won't be |
| # noticed by an xml/html escaper. |
| for key,(begin,end) in sub_info[::-1]: |
| text = text[0:begin]+'\0'+key+text[begin:end]+'\1'+text[end:] |
| text = text[2:] |
| # Handle case of add/delete entire line |
| else: |
| text = lines.pop(0)[2:] |
| # if line of text is just a newline, insert a space so there is |
| # something for the user to highlight and see. |
| if not text: |
| text = ' ' |
| # insert marks that won't be noticed by an xml/html escaper. |
| text = '\0' + format_key + text + '\1' |
| # Return line of text, first allow user's line formatter to do its |
| # thing (such as adding the line number) then replace the special |
| # marks with what the user's change markup. |
| return (num_lines[side],text) |
| |
| def _line_iterator(): |
| """Yields from/to lines of text with a change indication. |
| |
| This function is an iterator. It itself pulls lines from a |
| differencing iterator, processes them and yields them. When it can |
| it yields both a "from" and a "to" line, otherwise it will yield one |
| or the other. In addition to yielding the lines of from/to text, a |
| boolean flag is yielded to indicate if the text line(s) have |
| differences in them. |
| |
| Note, this function is purposefully not defined at the module scope so |
| that data it needs from its parent function (within whose context it |
| is defined) does not need to be of module scope. |
| """ |
| lines = [] |
| num_blanks_pending, num_blanks_to_yield = 0, 0 |
| while True: |
| # Load up next 4 lines so we can look ahead, create strings which |
| # are a concatenation of the first character of each of the 4 lines |
| # so we can do some very readable comparisons. |
| while len(lines) < 4: |
| try: |
| lines.append(next(diff_lines_iterator)) |
| except StopIteration: |
| lines.append('X') |
| s = ''.join([line[0] for line in lines]) |
| if s.startswith('X'): |
| # When no more lines, pump out any remaining blank lines so the |
| # corresponding add/delete lines get a matching blank line so |
| # all line pairs get yielded at the next level. |
| num_blanks_to_yield = num_blanks_pending |
| elif s.startswith('-?+?'): |
| # simple intraline change |
| yield _make_line(lines,'?',0), _make_line(lines,'?',1), True |
| continue |
| elif s.startswith('--++'): |
| # in delete block, add block coming: we do NOT want to get |
| # caught up on blank lines yet, just process the delete line |
| num_blanks_pending -= 1 |
| yield _make_line(lines,'-',0), None, True |
| continue |
| elif s.startswith(('--?+', '--+', '- ')): |
| # in delete block and see a intraline change or unchanged line |
| # coming: yield the delete line and then blanks |
| from_line,to_line = _make_line(lines,'-',0), None |
| num_blanks_to_yield,num_blanks_pending = num_blanks_pending-1,0 |
| elif s.startswith('-+?'): |
| # intraline change |
| yield _make_line(lines,None,0), _make_line(lines,'?',1), True |
| continue |
| elif s.startswith('-?+'): |
| # intraline change |
| yield _make_line(lines,'?',0), _make_line(lines,None,1), True |
| continue |
| elif s.startswith('-'): |
| # delete FROM line |
| num_blanks_pending -= 1 |
| yield _make_line(lines,'-',0), None, True |
| continue |
| elif s.startswith('+--'): |
| # in add block, delete block coming: we do NOT want to get |
| # caught up on blank lines yet, just process the add line |
| num_blanks_pending += 1 |
| yield None, _make_line(lines,'+',1), True |
| continue |
| elif s.startswith(('+ ', '+-')): |
| # will be leaving an add block: yield blanks then add line |
| from_line, to_line = None, _make_line(lines,'+',1) |
| num_blanks_to_yield,num_blanks_pending = num_blanks_pending+1,0 |
| elif s.startswith('+'): |
| # inside an add block, yield the add line |
| num_blanks_pending += 1 |
| yield None, _make_line(lines,'+',1), True |
| continue |
| elif s.startswith(' '): |
| # unchanged text, yield it to both sides |
| yield _make_line(lines[:],None,0),_make_line(lines,None,1),False |
| continue |
| # Catch up on the blank lines so when we yield the next from/to |
| # pair, they are lined up. |
| while(num_blanks_to_yield < 0): |
| num_blanks_to_yield += 1 |
| yield None,('','\n'),True |
| while(num_blanks_to_yield > 0): |
| num_blanks_to_yield -= 1 |
| yield ('','\n'),None,True |
| if s.startswith('X'): |
| raise StopIteration |
| else: |
| yield from_line,to_line,True |
| |
| def _line_pair_iterator(): |
| """Yields from/to lines of text with a change indication. |
| |
| This function is an iterator. It itself pulls lines from the line |
| iterator. Its difference from that iterator is that this function |
| always yields a pair of from/to text lines (with the change |
| indication). If necessary it will collect single from/to lines |
| until it has a matching pair from/to pair to yield. |
| |
| Note, this function is purposefully not defined at the module scope so |
| that data it needs from its parent function (within whose context it |
| is defined) does not need to be of module scope. |
| """ |
| line_iterator = _line_iterator() |
| fromlines,tolines=[],[] |
| while True: |
| # Collecting lines of text until we have a from/to pair |
| while (len(fromlines)==0 or len(tolines)==0): |
| from_line, to_line, found_diff = next(line_iterator) |
| if from_line is not None: |
| fromlines.append((from_line,found_diff)) |
| if to_line is not None: |
| tolines.append((to_line,found_diff)) |
| # Once we have a pair, remove them from the collection and yield it |
| from_line, fromDiff = fromlines.pop(0) |
| to_line, to_diff = tolines.pop(0) |
| yield (from_line,to_line,fromDiff or to_diff) |
| |
| # Handle case where user does not want context differencing, just yield |
| # them up without doing anything else with them. |
| line_pair_iterator = _line_pair_iterator() |
| if context is None: |
| while True: |
| yield next(line_pair_iterator) |
| # Handle case where user wants context differencing. We must do some |
| # storage of lines until we know for sure that they are to be yielded. |
| else: |
| context += 1 |
| lines_to_write = 0 |
| while True: |
| # Store lines up until we find a difference, note use of a |
| # circular queue because we only need to keep around what |
| # we need for context. |
| index, contextLines = 0, [None]*(context) |
| found_diff = False |
| while(found_diff is False): |
| from_line, to_line, found_diff = next(line_pair_iterator) |
| i = index % context |
| contextLines[i] = (from_line, to_line, found_diff) |
| index += 1 |
| # Yield lines that we have collected so far, but first yield |
| # the user's separator. |
| if index > context: |
| yield None, None, None |
| lines_to_write = context |
| else: |
| lines_to_write = index |
| index = 0 |
| while(lines_to_write): |
| i = index % context |
| index += 1 |
| yield contextLines[i] |
| lines_to_write -= 1 |
| # Now yield the context lines after the change |
| lines_to_write = context-1 |
| while(lines_to_write): |
| from_line, to_line, found_diff = next(line_pair_iterator) |
| # If another change within the context, extend the context |
| if found_diff: |
| lines_to_write = context-1 |
| else: |
| lines_to_write -= 1 |
| yield from_line, to_line, found_diff |
| |
| |
| _file_template = """ |
| <!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" |
| "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"> |
| |
| <html> |
| |
| <head> |
| <meta http-equiv="Content-Type" |
| content="text/html; charset=ISO-8859-1" /> |
| <title></title> |
| <style type="text/css">%(styles)s |
| </style> |
| </head> |
| |
| <body> |
| %(table)s%(legend)s |
| </body> |
| |
| </html>""" |
| |
| _styles = """ |
| table.diff {font-family:Courier; border:medium;} |
| .diff_header {background-color:#e0e0e0} |
| td.diff_header {text-align:right} |
| .diff_next {background-color:#c0c0c0} |
| .diff_add {background-color:#aaffaa} |
| .diff_chg {background-color:#ffff77} |
| .diff_sub {background-color:#ffaaaa}""" |
| |
| _table_template = """ |
| <table class="diff" id="difflib_chg_%(prefix)s_top" |
| cellspacing="0" cellpadding="0" rules="groups" > |
| <colgroup></colgroup> <colgroup></colgroup> <colgroup></colgroup> |
| <colgroup></colgroup> <colgroup></colgroup> <colgroup></colgroup> |
| %(header_row)s |
| <tbody> |
| %(data_rows)s </tbody> |
| </table>""" |
| |
| _legend = """ |
| <table class="diff" summary="Legends"> |
| <tr> <th colspan="2"> Legends </th> </tr> |
| <tr> <td> <table border="" summary="Colors"> |
| <tr><th> Colors </th> </tr> |
| <tr><td class="diff_add"> Added </td></tr> |
| <tr><td class="diff_chg">Changed</td> </tr> |
| <tr><td class="diff_sub">Deleted</td> </tr> |
| </table></td> |
| <td> <table border="" summary="Links"> |
| <tr><th colspan="2"> Links </th> </tr> |
| <tr><td>(f)irst change</td> </tr> |
| <tr><td>(n)ext change</td> </tr> |
| <tr><td>(t)op</td> </tr> |
| </table></td> </tr> |
| </table>""" |
| |
| class HtmlDiff(object): |
| """For producing HTML side by side comparison with change highlights. |
| |
| This class can be used to create an HTML table (or a complete HTML file |
| containing the table) showing a side by side, line by line comparison |
| of text with inter-line and intra-line change highlights. The table can |
| be generated in either full or contextual difference mode. |
| |
| The following methods are provided for HTML generation: |
| |
| make_table -- generates HTML for a single side by side table |
| make_file -- generates complete HTML file with a single side by side table |
| |
| See tools/scripts/diff.py for an example usage of this class. |
| """ |
| |
| _file_template = _file_template |
| _styles = _styles |
| _table_template = _table_template |
| _legend = _legend |
| _default_prefix = 0 |
| |
| def __init__(self,tabsize=8,wrapcolumn=None,linejunk=None, |
| charjunk=IS_CHARACTER_JUNK): |
| """HtmlDiff instance initializer |
| |
| Arguments: |
| tabsize -- tab stop spacing, defaults to 8. |
| wrapcolumn -- column number where lines are broken and wrapped, |
| defaults to None where lines are not wrapped. |
| linejunk,charjunk -- keyword arguments passed into ndiff() (used to by |
| HtmlDiff() to generate the side by side HTML differences). See |
| ndiff() documentation for argument default values and descriptions. |
| """ |
| self._tabsize = tabsize |
| self._wrapcolumn = wrapcolumn |
| self._linejunk = linejunk |
| self._charjunk = charjunk |
| |
| def make_file(self,fromlines,tolines,fromdesc='',todesc='',context=False, |
| numlines=5): |
| """Returns HTML file of side by side comparison with change highlights |
| |
| Arguments: |
| fromlines -- list of "from" lines |
| tolines -- list of "to" lines |
| fromdesc -- "from" file column header string |
| todesc -- "to" file column header string |
| context -- set to True for contextual differences (defaults to False |
| which shows full differences). |
| numlines -- number of context lines. When context is set True, |
| controls number of lines displayed before and after the change. |
| When context is False, controls the number of lines to place |
| the "next" link anchors before the next change (so click of |
| "next" link jumps to just before the change). |
| """ |
| |
| return self._file_template % dict( |
| styles = self._styles, |
| legend = self._legend, |
| table = self.make_table(fromlines,tolines,fromdesc,todesc, |
| context=context,numlines=numlines)) |
| |
| def _tab_newline_replace(self,fromlines,tolines): |
| """Returns from/to line lists with tabs expanded and newlines removed. |
| |
| Instead of tab characters being replaced by the number of spaces |
| needed to fill in to the next tab stop, this function will fill |
| the space with tab characters. This is done so that the difference |
| algorithms can identify changes in a file when tabs are replaced by |
| spaces and vice versa. At the end of the HTML generation, the tab |
| characters will be replaced with a nonbreakable space. |
| """ |
| def expand_tabs(line): |
| # hide real spaces |
| line = line.replace(' ','\0') |
| # expand tabs into spaces |
| line = line.expandtabs(self._tabsize) |
| # replace spaces from expanded tabs back into tab characters |
| # (we'll replace them with markup after we do differencing) |
| line = line.replace(' ','\t') |
| return line.replace('\0',' ').rstrip('\n') |
| fromlines = [expand_tabs(line) for line in fromlines] |
| tolines = [expand_tabs(line) for line in tolines] |
| return fromlines,tolines |
| |
| def _split_line(self,data_list,line_num,text): |
| """Builds list of text lines by splitting text lines at wrap point |
| |
| This function will determine if the input text line needs to be |
| wrapped (split) into separate lines. If so, the first wrap point |
| will be determined and the first line appended to the output |
| text line list. This function is used recursively to handle |
| the second part of the split line to further split it. |
| """ |
| # if blank line or context separator, just add it to the output list |
| if not line_num: |
| data_list.append((line_num,text)) |
| return |
| |
| # if line text doesn't need wrapping, just add it to the output list |
| size = len(text) |
| max = self._wrapcolumn |
| if (size <= max) or ((size -(text.count('\0')*3)) <= max): |
| data_list.append((line_num,text)) |
| return |
| |
| # scan text looking for the wrap point, keeping track if the wrap |
| # point is inside markers |
| i = 0 |
| n = 0 |
| mark = '' |
| while n < max and i < size: |
| if text[i] == '\0': |
| i += 1 |
| mark = text[i] |
| i += 1 |
| elif text[i] == '\1': |
| i += 1 |
| mark = '' |
| else: |
| i += 1 |
| n += 1 |
| |
| # wrap point is inside text, break it up into separate lines |
| line1 = text[:i] |
| line2 = text[i:] |
| |
| # if wrap point is inside markers, place end marker at end of first |
| # line and start marker at beginning of second line because each |
| # line will have its own table tag markup around it. |
| if mark: |
| line1 = line1 + '\1' |
| line2 = '\0' + mark + line2 |
| |
| # tack on first line onto the output list |
| data_list.append((line_num,line1)) |
| |
| # use this routine again to wrap the remaining text |
| self._split_line(data_list,'>',line2) |
| |
| def _line_wrapper(self,diffs): |
| """Returns iterator that splits (wraps) mdiff text lines""" |
| |
| # pull from/to data and flags from mdiff iterator |
| for fromdata,todata,flag in diffs: |
| # check for context separators and pass them through |
| if flag is None: |
| yield fromdata,todata,flag |
| continue |
| (fromline,fromtext),(toline,totext) = fromdata,todata |
| # for each from/to line split it at the wrap column to form |
| # list of text lines. |
| fromlist,tolist = [],[] |
| self._split_line(fromlist,fromline,fromtext) |
| self._split_line(tolist,toline,totext) |
| # yield from/to line in pairs inserting blank lines as |
| # necessary when one side has more wrapped lines |
| while fromlist or tolist: |
| if fromlist: |
| fromdata = fromlist.pop(0) |
| else: |
| fromdata = ('',' ') |
| if tolist: |
| todata = tolist.pop(0) |
| else: |
| todata = ('',' ') |
| yield fromdata,todata,flag |
| |
| def _collect_lines(self,diffs): |
| """Collects mdiff output into separate lists |
| |
| Before storing the mdiff from/to data into a list, it is converted |
| into a single line of text with HTML markup. |
| """ |
| |
| fromlist,tolist,flaglist = [],[],[] |
| # pull from/to data and flags from mdiff style iterator |
| for fromdata,todata,flag in diffs: |
| try: |
| # store HTML markup of the lines into the lists |
| fromlist.append(self._format_line(0,flag,*fromdata)) |
| tolist.append(self._format_line(1,flag,*todata)) |
| except TypeError: |
| # exceptions occur for lines where context separators go |
| fromlist.append(None) |
| tolist.append(None) |
| flaglist.append(flag) |
| return fromlist,tolist,flaglist |
| |
| def _format_line(self,side,flag,linenum,text): |
| """Returns HTML markup of "from" / "to" text lines |
| |
| side -- 0 or 1 indicating "from" or "to" text |
| flag -- indicates if difference on line |
| linenum -- line number (used for line number column) |
| text -- line text to be marked up |
| """ |
| try: |
| linenum = '%d' % linenum |
| id = ' id="%s%s"' % (self._prefix[side],linenum) |
| except TypeError: |
| # handle blank lines where linenum is '>' or '' |
| id = '' |
| # replace those things that would get confused with HTML symbols |
| text=text.replace("&","&").replace(">",">").replace("<","<") |
| |
| # make space non-breakable so they don't get compressed or line wrapped |
| text = text.replace(' ',' ').rstrip() |
| |
| return '<td class="diff_header"%s>%s</td><td nowrap="nowrap">%s</td>' \ |
| % (id,linenum,text) |
| |
| def _make_prefix(self): |
| """Create unique anchor prefixes""" |
| |
| # Generate a unique anchor prefix so multiple tables |
| # can exist on the same HTML page without conflicts. |
| fromprefix = "from%d_" % HtmlDiff._default_prefix |
| toprefix = "to%d_" % HtmlDiff._default_prefix |
| HtmlDiff._default_prefix += 1 |
| # store prefixes so line format method has access |
| self._prefix = [fromprefix,toprefix] |
| |
| def _convert_flags(self,fromlist,tolist,flaglist,context,numlines): |
| """Makes list of "next" links""" |
| |
| # all anchor names will be generated using the unique "to" prefix |
| toprefix = self._prefix[1] |
| |
| # process change flags, generating middle column of next anchors/links |
| next_id = ['']*len(flaglist) |
| next_href = ['']*len(flaglist) |
| num_chg, in_change = 0, False |
| last = 0 |
| for i,flag in enumerate(flaglist): |
| if flag: |
| if not in_change: |
| in_change = True |
| last = i |
| # at the beginning of a change, drop an anchor a few lines |
| # (the context lines) before the change for the previous |
| # link |
| i = max([0,i-numlines]) |
| next_id[i] = ' id="difflib_chg_%s_%d"' % (toprefix,num_chg) |
| # at the beginning of a change, drop a link to the next |
| # change |
| num_chg += 1 |
| next_href[last] = '<a href="#difflib_chg_%s_%d">n</a>' % ( |
| toprefix,num_chg) |
| else: |
| in_change = False |
| # check for cases where there is no content to avoid exceptions |
| if not flaglist: |
| flaglist = [False] |
| next_id = [''] |
| next_href = [''] |
| last = 0 |
| if context: |
| fromlist = ['<td></td><td> No Differences Found </td>'] |
| tolist = fromlist |
| else: |
| fromlist = tolist = ['<td></td><td> Empty File </td>'] |
| # if not a change on first line, drop a link |
| if not flaglist[0]: |
| next_href[0] = '<a href="#difflib_chg_%s_0">f</a>' % toprefix |
| # redo the last link to link to the top |
| next_href[last] = '<a href="#difflib_chg_%s_top">t</a>' % (toprefix) |
| |
| return fromlist,tolist,flaglist,next_href,next_id |
| |
| def make_table(self,fromlines,tolines,fromdesc='',todesc='',context=False, |
| numlines=5): |
| """Returns HTML table of side by side comparison with change highlights |
| |
| Arguments: |
| fromlines -- list of "from" lines |
| tolines -- list of "to" lines |
| fromdesc -- "from" file column header string |
| todesc -- "to" file column header string |
| context -- set to True for contextual differences (defaults to False |
| which shows full differences). |
| numlines -- number of context lines. When context is set True, |
| controls number of lines displayed before and after the change. |
| When context is False, controls the number of lines to place |
| the "next" link anchors before the next change (so click of |
| "next" link jumps to just before the change). |
| """ |
| |
| # make unique anchor prefixes so that multiple tables may exist |
| # on the same page without conflict. |
| self._make_prefix() |
| |
| # change tabs to spaces before it gets more difficult after we insert |
| # markup |
| fromlines,tolines = self._tab_newline_replace(fromlines,tolines) |
| |
| # create diffs iterator which generates side by side from/to data |
| if context: |
| context_lines = numlines |
| else: |
| context_lines = None |
| diffs = _mdiff(fromlines,tolines,context_lines,linejunk=self._linejunk, |
| charjunk=self._charjunk) |
| |
| # set up iterator to wrap lines that exceed desired width |
| if self._wrapcolumn: |
| diffs = self._line_wrapper(diffs) |
| |
| # collect up from/to lines and flags into lists (also format the lines) |
| fromlist,tolist,flaglist = self._collect_lines(diffs) |
| |
| # process change flags, generating middle column of next anchors/links |
| fromlist,tolist,flaglist,next_href,next_id = self._convert_flags( |
| fromlist,tolist,flaglist,context,numlines) |
| |
| s = [] |
| fmt = ' <tr><td class="diff_next"%s>%s</td>%s' + \ |
| '<td class="diff_next">%s</td>%s</tr>\n' |
| for i in range(len(flaglist)): |
| if flaglist[i] is None: |
| # mdiff yields None on separator lines skip the bogus ones |
| # generated for the first line |
| if i > 0: |
| s.append(' </tbody> \n <tbody>\n') |
| else: |
| s.append( fmt % (next_id[i],next_href[i],fromlist[i], |
| next_href[i],tolist[i])) |
| if fromdesc or todesc: |
| header_row = '<thead><tr>%s%s%s%s</tr></thead>' % ( |
| '<th class="diff_next"><br /></th>', |
| '<th colspan="2" class="diff_header">%s</th>' % fromdesc, |
| '<th class="diff_next"><br /></th>', |
| '<th colspan="2" class="diff_header">%s</th>' % todesc) |
| else: |
| header_row = '' |
| |
| table = self._table_template % dict( |
| data_rows=''.join(s), |
| header_row=header_row, |
| prefix=self._prefix[1]) |
| |
| return table.replace('\0+','<span class="diff_add">'). \ |
| replace('\0-','<span class="diff_sub">'). \ |
| replace('\0^','<span class="diff_chg">'). \ |
| replace('\1','</span>'). \ |
| replace('\t',' ') |
| |
| del re |
| |
| def restore(delta, which): |
| r""" |
| Generate one of the two sequences that generated a delta. |
| |
| Given a `delta` produced by `Differ.compare()` or `ndiff()`, extract |
| lines originating from file 1 or 2 (parameter `which`), stripping off line |
| prefixes. |
| |
| Examples: |
| |
| >>> diff = ndiff('one\ntwo\nthree\n'.splitlines(keepends=True), |
| ... 'ore\ntree\nemu\n'.splitlines(keepends=True)) |
| >>> diff = list(diff) |
| >>> print(''.join(restore(diff, 1)), end="") |
| one |
| two |
| three |
| >>> print(''.join(restore(diff, 2)), end="") |
| ore |
| tree |
| emu |
| """ |
| try: |
| tag = {1: "- ", 2: "+ "}[int(which)] |
| except KeyError: |
| raise ValueError('unknown delta choice (must be 1 or 2): %r' |
| % which) |
| prefixes = (" ", tag) |
| for line in delta: |
| if line[:2] in prefixes: |
| yield line[2:] |
| |
| def _test(): |
| import doctest, difflib |
| return doctest.testmod(difflib) |
| |
| if __name__ == "__main__": |
| _test() |