"""Class containing the diff, match and patch methods.

def __init__(self):

"""Inits a diff_match_patch object with default settings.

# Number of seconds to map a diff before giving up (0 for infinity).

self.Diff_Timeout = 1.0

# Cost of an empty edit operation in terms of edit characters.

self.Diff_EditCost = 4

# At what point is no match declared (0.0 = perfection, 1.0 = very loose).

self.Match_Threshold = 0.5

# How far to search for a match (0 = exact location, 1000+ = broad match).

# A match this many characters away from the expected location will add

# 1.0 to the score (0.0 is a perfect match).

self.Match_Distance = 1000

# When deleting a large block of text (over ~64 characters), how close do

# the contents have to be to match the expected contents. (0.0 = perfection,

# 1.0 = very loose). Note that Match_Threshold controls how closely the

# end points of a delete need to match.

self.Patch_DeleteThreshold = 0.5

# Chunk size for context length.

self.Patch_Margin = 4

# The number of bits in an int.

# Python has no maximum, thus to disable patch splitting set to 0.

# However to avoid long patches in certain pathological cases, use 32.

# Multiple short patches (using native ints) are much faster than long ones.

self.Match_MaxBits = 32

# DIFF FUNCTIONS

# The data structure representing a diff is an array of tuples:

# [(DIFF_DELETE, "Hello"), (DIFF_INSERT, "Goodbye"), (DIFF_EQUAL, " world.")]

# which means: delete "Hello", add "Goodbye" and keep " world."

DIFF_DELETE = -1

DIFF_INSERT = 1

DIFF_EQUAL = 0

def diff_main(self, text1, text2, checklines=True, deadline=None):

"""Find the differences between two texts. Simplifies the problem by

# Set a deadline by which time the diff must be complete.

if deadline == None:

# Unlike in most languages, Python counts time in seconds.

if self.Diff_Timeout <= 0:

deadline = sys.maxsize

else:

deadline = time.time() + self.Diff_Timeout

# Check for null inputs.

if text1 == None or text2 == None:

raise ValueError("Null inputs. (diff_main)")

# Check for equality (speedup).

if text1 == text2:

if text1:

return [(self.DIFF_EQUAL, text1)]

return []

# Trim off common prefix (speedup).

commonlength = self.diff_commonPrefix(text1, text2)

commonprefix = text1[:commonlength]

text1 = text1[commonlength:]

text2 = text2[commonlength:]

# Trim off common suffix (speedup).

commonlength = self.diff_commonSuffix(text1, text2)

if commonlength == 0:

commonsuffix = ''

else:

commonsuffix = text1[-commonlength:]

text1 = text1[:-commonlength]

text2 = text2[:-commonlength]

# Compute the diff on the middle block.

diffs = self.diff_compute(text1, text2, checklines, deadline)

# Restore the prefix and suffix.

if commonprefix:

diffs[:0] = [(self.DIFF_EQUAL, commonprefix)]

if commonsuffix:

diffs.append((self.DIFF_EQUAL, commonsuffix))

self.diff_cleanupMerge(diffs)

return diffs

def diff_compute(self, text1, text2, checklines, deadline):

"""Find the differences between two texts. Assumes that the texts do not

if not text1:

# Just add some text (speedup).

return [(self.DIFF_INSERT, text2)]

if not text2:

# Just delete some text (speedup).

return [(self.DIFF_DELETE, text1)]

if len(text1) > len(text2):

(longtext, shorttext) = (text1, text2)

else:

(shorttext, longtext) = (text1, text2)

i = longtext.find(shorttext)

if i != -1:

# Shorter text is inside the longer text (speedup).

diffs = [(self.DIFF_INSERT, longtext[:i]), (self.DIFF_EQUAL, shorttext),

(self.DIFF_INSERT, longtext[i + len(shorttext):])]

# Swap insertions for deletions if diff is reversed.

if len(text1) > len(text2):

diffs[0] = (self.DIFF_DELETE, diffs[0][1])

diffs[2] = (self.DIFF_DELETE, diffs[2][1])

return diffs

if len(shorttext) == 1:

# Single character string.

# After the previous speedup, the character can't be an equality.

return [(self.DIFF_DELETE, text1), (self.DIFF_INSERT, text2)]

# Check to see if the problem can be split in two.

hm = self.diff_halfMatch(text1, text2)

if hm:

# A half-match was found, sort out the return data.

(text1_a, text1_b, text2_a, text2_b, mid_common) = hm

# Send both pairs off for separate processing.

diffs_a = self.diff_main(text1_a, text2_a, checklines, deadline)

diffs_b = self.diff_main(text1_b, text2_b, checklines, deadline)

# Merge the results.

return diffs_a + [(self.DIFF_EQUAL, mid_common)] + diffs_b

if checklines and len(text1) > 100 and len(text2) > 100:

return self.diff_lineMode(text1, text2, deadline)

return self.diff_bisect(text1, text2, deadline)

def diff_lineMode(self, text1, text2, deadline):

"""Do a quick line-level diff on both strings, then rediff the parts for

# Scan the text on a line-by-line basis first.

(text1, text2, linearray) = self.diff_linesToChars(text1, text2)

diffs = self.diff_main(text1, text2, False, deadline)

# Convert the diff back to original text.

self.diff_charsToLines(diffs, linearray)

# Eliminate freak matches (e.g. blank lines)

self.diff_cleanupSemantic(diffs)

# Rediff any replacement blocks, this time character-by-character.

# Add a dummy entry at the end.

diffs.append((self.DIFF_EQUAL, ''))

pointer = 0

count_delete = 0

count_insert = 0

text_delete = ''

text_insert = ''

while pointer < len(diffs):

if diffs[pointer][0] == self.DIFF_INSERT:

count_insert += 1

text_insert += diffs[pointer][1]

elif diffs[pointer][0] == self.DIFF_DELETE:

count_delete += 1

text_delete += diffs[pointer][1]

elif diffs[pointer][0] == self.DIFF_EQUAL:

# Upon reaching an equality, check for prior redundancies.

if count_delete >= 1 and count_insert >= 1:

# Delete the offending records and add the merged ones.

a = self.diff_main(text_delete, text_insert, False, deadline)

diffs[pointer - count_delete - count_insert : pointer] = a

pointer = pointer - count_delete - count_insert + len(a)

count_insert = 0

count_delete = 0

text_delete = ''

text_insert = ''

pointer += 1

diffs.pop() # Remove the dummy entry at the end.

return diffs

def diff_bisect(self, text1, text2, deadline):

"""Find the 'middle snake' of a diff, split the problem in two

# Cache the text lengths to prevent multiple calls.

text1_length = len(text1)

text2_length = len(text2)

max_d = (text1_length + text2_length + 1) // 2

v_offset = max_d

v_length = 2 * max_d

v1 = [-1] * v_length

v1[v_offset + 1] = 0

v2 = v1[:]

delta = text1_length - text2_length

# If the total number of characters is odd, then the front path will

# collide with the reverse path.

front = (delta % 2 != 0)

# Offsets for start and end of k loop.

# Prevents mapping of space beyond the grid.

k1start = 0

k1end = 0

k2start = 0

k2end = 0

for d in range(max_d):

# Bail out if deadline is reached.

if time.time() > deadline:

break

# Walk the front path one step.

for k1 in range(-d + k1start, d + 1 - k1end, 2):

k1_offset = v_offset + k1

if k1 == -d or (k1 != d and

v1[k1_offset - 1] < v1[k1_offset + 1]):

x1 = v1[k1_offset + 1]

else:

x1 = v1[k1_offset - 1] + 1

y1 = x1 - k1

while (x1 < text1_length and y1 < text2_length and

text1[x1] == text2[y1]):

x1 += 1

y1 += 1

v1[k1_offset] = x1

if x1 > text1_length:

# Ran off the right of the graph.

k1end += 2

elif y1 > text2_length:

# Ran off the bottom of the graph.

k1start += 2

elif front:

k2_offset = v_offset + delta - k1

if k2_offset >= 0 and k2_offset < v_length and v2[k2_offset] != -1:

# Mirror x2 onto top-left coordinate system.

x2 = text1_length - v2[k2_offset]

if x1 >= x2:

# Overlap detected.

return self.diff_bisectSplit(text1, text2, x1, y1, deadline)

# Walk the reverse path one step.

for k2 in range(-d + k2start, d + 1 - k2end, 2):

k2_offset = v_offset + k2

if k2 == -d or (k2 != d and

v2[k2_offset - 1] < v2[k2_offset + 1]):

x2 = v2[k2_offset + 1]

else:

x2 = v2[k2_offset - 1] + 1

y2 = x2 - k2

while (x2 < text1_length and y2 < text2_length and

text1[-x2 - 1] == text2[-y2 - 1]):

x2 += 1

y2 += 1

v2[k2_offset] = x2

if x2 > text1_length:

# Ran off the left of the graph.

k2end += 2

elif y2 > text2_length:

# Ran off the top of the graph.

k2start += 2

elif not front:

k1_offset = v_offset + delta - k2

if k1_offset >= 0 and k1_offset < v_length and v1[k1_offset] != -1:

x1 = v1[k1_offset]

y1 = v_offset + x1 - k1_offset

# Mirror x2 onto top-left coordinate system.

x2 = text1_length - x2

if x1 >= x2:

# Overlap detected.

return self.diff_bisectSplit(text1, text2, x1, y1, deadline)

# Diff took too long and hit the deadline or

# number of diffs equals number of characters, no commonality at all.

return [(self.DIFF_DELETE, text1), (self.DIFF_INSERT, text2)]

def diff_bisectSplit(self, text1, text2, x, y, deadline):

"""Given the location of the 'middle snake', split the diff in two parts

text1a = text1[:x]

text2a = text2[:y]

text1b = text1[x:]

text2b = text2[y:]

# Compute both diffs serially.

diffs = self.diff_main(text1a, text2a, False, deadline)

diffsb = self.diff_main(text1b, text2b, False, deadline)

return diffs + diffsb

def diff_linesToChars(self, text1, text2):

"""Split two texts into an array of strings. Reduce the texts to a string

lineArray = [] # e.g. lineArray[4] == "Hello\n"

lineHash = {} # e.g. lineHash["Hello\n"] == 4

# "\x00" is a valid character, but various debuggers don't like it.

# So we'll insert a junk entry to avoid generating a null character.

lineArray.append('')

def diff_linesToCharsMunge(text):

"""Split a text into an array of strings. Reduce the texts to a string

chars = []

# Walk the text, pulling out a substring for each line.

# text.split('\n') would would temporarily double our memory footprint.

# Modifying text would create many large strings to garbage collect.

lineStart = 0

lineEnd = -1

while lineEnd < len(text) - 1:

lineEnd = text.find('\n', lineStart)

if lineEnd == -1:

lineEnd = len(text) - 1

line = text[lineStart:lineEnd + 1]

lineStart = lineEnd + 1

if line in lineHash:

chars.append(chr(lineHash[line]))

else:

lineArray.append(line)

lineHash[line] = len(lineArray) - 1

chars.append(chr(len(lineArray) - 1))

return "".join(chars)

chars1 = diff_linesToCharsMunge(text1)

chars2 = diff_linesToCharsMunge(text2)

return (chars1, chars2, lineArray)

def diff_charsToLines(self, diffs, lineArray):

"""Rehydrate the text in a diff from a string of line hashes to real lines

for x in range(len(diffs)):

text = []

for char in diffs[x][1]:

text.append(lineArray[ord(char)])

diffs[x] = (diffs[x][0], "".join(text))

def diff_commonPrefix(self, text1, text2):

"""Determine the common prefix of two strings.

# Quick check for common null cases.

if not text1 or not text2 or text1[0] != text2[0]:

return 0

# Binary search.

# Performance analysis: http://neil.fraser.name/news/2007/10/09/

pointermin = 0

pointermax = min(len(text1), len(text2))

pointermid = pointermax

pointerstart = 0

while pointermin < pointermid:

if text1[pointerstart:pointermid] == text2[pointerstart:pointermid]:

pointermin = pointermid

pointerstart = pointermin

else:

pointermax = pointermid

pointermid = (pointermax - pointermin) // 2 + pointermin

return pointermid

def diff_commonSuffix(self, text1, text2):

"""Determine the common suffix of two strings.

# Quick check for common null cases.

if not text1 or not text2 or text1[-1] != text2[-1]:

return 0

# Binary search.

# Performance analysis: http://neil.fraser.name/news/2007/10/09/

pointermin = 0

pointermax = min(len(text1), len(text2))

pointermid = pointermax

pointerend = 0

while pointermin < pointermid:

if (text1[-pointermid:len(text1) - pointerend] ==

text2[-pointermid:len(text2) - pointerend]):

pointermin = pointermid

pointerend = pointermin

else:

pointermax = pointermid

pointermid = (pointermax - pointermin) // 2 + pointermin

return pointermid

def diff_commonOverlap(self, text1, text2):

"""Determine if the suffix of one string is the prefix of another.

# Cache the text lengths to prevent multiple calls.

text1_length = len(text1)

text2_length = len(text2)

# Eliminate the null case.

if text1_length == 0 or text2_length == 0:

return 0

# Truncate the longer string.

if text1_length > text2_length:

text1 = text1[-text2_length:]

elif text1_length < text2_length:

text2 = text2[:text1_length]

text_length = min(text1_length, text2_length)

# Quick check for the worst case.

if text1 == text2:

return text_length

# Start by looking for a single character match

# and increase length until no match is found.

# Performance analysis: http://neil.fraser.name/news/2010/11/04/

best = 0

length = 1

while True:

pattern = text1[-length:]

found = text2.find(pattern)

if found == -1:

return best

length += found

if found == 0 or text1[-length:] == text2[:length]:

best = length

length += 1

def diff_halfMatch(self, text1, text2):

"""Do the two texts share a substring which is at least half the length of

if self.Diff_Timeout <= 0:

# Don't risk returning a non-optimal diff if we have unlimited time.

return None

if len(text1) > len(text2):

(longtext, shorttext) = (text1, text2)

else:

(shorttext, longtext) = (text1, text2)

if len(longtext) < 4 or len(shorttext) * 2 < len(longtext):

return None # Pointless.

def diff_halfMatchI(longtext, shorttext, i):

"""Does a substring of shorttext exist within longtext such that the

seed = longtext[i:i + len(longtext) // 4]

best_common = ''

j = shorttext.find(seed)

while j != -1:

prefixLength = self.diff_commonPrefix(longtext[i:], shorttext[j:])

suffixLength = self.diff_commonSuffix(longtext[:i], shorttext[:j])

if len(best_common) < suffixLength + prefixLength:

best_common = (shorttext[j - suffixLength:j] +

shorttext[j:j + prefixLength])

best_longtext_a = longtext[:i - suffixLength]

best_longtext_b = longtext[i + prefixLength:]

best_shorttext_a = shorttext[:j - suffixLength]

best_shorttext_b = shorttext[j + prefixLength:]

j = shorttext.find(seed, j + 1)

if len(best_common) * 2 >= len(longtext):

return (best_longtext_a, best_longtext_b,

best_shorttext_a, best_shorttext_b, best_common)

else:

return None

# First check if the second quarter is the seed for a half-match.

hm1 = diff_halfMatchI(longtext, shorttext, (len(longtext) + 3) // 4)

# Check again based on the third quarter.

hm2 = diff_halfMatchI(longtext, shorttext, (len(longtext) + 1) // 2)

if not hm1 and not hm2:

return None

elif not hm2:

hm = hm1

elif not hm1:

hm = hm2

else:

# Both matched. Select the longest.

if len(hm1[4]) > len(hm2[4]):

hm = hm1

else:

hm = hm2

# A half-match was found, sort out the return data.

if len(text1) > len(text2):

(text1_a, text1_b, text2_a, text2_b, mid_common) = hm

else:

(text2_a, text2_b, text1_a, text1_b, mid_common) = hm

return (text1_a, text1_b, text2_a, text2_b, mid_common)

def diff_cleanupSemantic(self, diffs):

"""Reduce the number of edits by eliminating semantically trivial

changes = False

equalities = [] # Stack of indices where equalities are found.

lastequality = None # Always equal to diffs[equalities[-1]][1]

pointer = 0 # Index of current position.

# Number of chars that changed prior to the equality.

length_insertions1, length_deletions1 = 0, 0

# Number of chars that changed after the equality.

length_insertions2, length_deletions2 = 0, 0

while pointer < len(diffs):

if diffs[pointer][0] == self.DIFF_EQUAL: # Equality found.

equalities.append(pointer)

length_insertions1, length_insertions2 = length_insertions2, 0

length_deletions1, length_deletions2 = length_deletions2, 0

lastequality = diffs[pointer][1]

else: # An insertion or deletion.

if diffs[pointer][0] == self.DIFF_INSERT:

length_insertions2 += len(diffs[pointer][1])

else:

length_deletions2 += len(diffs[pointer][1])

# Eliminate an equality that is smaller or equal to the edits on both

# sides of it.

if (lastequality and (len(lastequality) <=

max(length_insertions1, length_deletions1)) and

(len(lastequality) <= max(length_insertions2, length_deletions2))):

# Duplicate record.

diffs.insert(equalities[-1], (self.DIFF_DELETE, lastequality))

# Change second copy to insert.

diffs[equalities[-1] + 1] = (self.DIFF_INSERT,

diffs[equalities[-1] + 1][1])

# Throw away the equality we just deleted.

equalities.pop()

# Throw away the previous equality (it needs to be reevaluated).

if len(equalities):

equalities.pop()

if len(equalities):

pointer = equalities[-1]

else:

pointer = -1

# Reset the counters.

length_insertions1, length_deletions1 = 0, 0

length_insertions2, length_deletions2 = 0, 0

lastequality = None

changes = True

pointer += 1

# Normalize the diff.

if changes:

self.diff_cleanupMerge(diffs)

self.diff_cleanupSemanticLossless(diffs)

# Find any overlaps between deletions and insertions.

# e.g: <del>abcxxx</del><ins>xxxdef</ins>

# -> <del>abc</del>xxx<ins>def</ins>

# e.g: <del>xxxabc</del><ins>defxxx</ins>

# -> <ins>def</ins>xxx<del>abc</del>

# Only extract an overlap if it is as big as the edit ahead or behind it.

pointer = 1

while pointer < len(diffs):

if (diffs[pointer - 1][0] == self.DIFF_DELETE and

diffs[pointer][0] == self.DIFF_INSERT):

deletion = diffs[pointer - 1][1]

insertion = diffs[pointer][1]

overlap_length1 = self.diff_commonOverlap(deletion, insertion)

overlap_length2 = self.diff_commonOverlap(insertion, deletion)

if overlap_length1 >= overlap_length2:

if (overlap_length1 >= len(deletion) / 2.0 or

overlap_length1 >= len(insertion) / 2.0):

# Overlap found. Insert an equality and trim the surrounding edits.

diffs.insert(pointer, (self.DIFF_EQUAL,

insertion[:overlap_length1]))

diffs[pointer - 1] = (self.DIFF_DELETE,

deletion[:len(deletion) - overlap_length1])

diffs[pointer + 1] = (self.DIFF_INSERT,

insertion[overlap_length1:])

pointer += 1

else:

if (overlap_length2 >= len(deletion) / 2.0 or

overlap_length2 >= len(insertion) / 2.0):

# Reverse overlap found.

# Insert an equality and swap and trim the surrounding edits.

diffs.insert(pointer, (self.DIFF_EQUAL, deletion[:overlap_length2]))

diffs[pointer - 1] = (self.DIFF_INSERT,

insertion[:len(insertion) - overlap_length2])

diffs[pointer + 1] = (self.DIFF_DELETE, deletion[overlap_length2:])

pointer += 1

pointer += 1

pointer += 1

def diff_cleanupSemanticLossless(self, diffs):

"""Look for single edits surrounded on both sides by equalities

def diff_cleanupSemanticScore(one, two):

"""Given two strings, compute a score representing whether the

if not one or not two:

# Edges are the best.

return 6

# Each port of this function behaves slightly differently due to

# subtle differences in each language's definition of things like

# 'whitespace'. Since this function's purpose is largely cosmetic,

# the choice has been made to use each language's native features

# rather than force total conformity.

char1 = one[-1]

char2 = two[0]

nonAlphaNumeric1 = not char1.isalnum()

nonAlphaNumeric2 = not char2.isalnum()

whitespace1 = nonAlphaNumeric1 and char1.isspace()

whitespace2 = nonAlphaNumeric2 and char2.isspace()

lineBreak1 = whitespace1 and (char1 == "\r" or char1 == "\n")

lineBreak2 = whitespace2 and (char2 == "\r" or char2 == "\n")

blankLine1 = lineBreak1 and self.BLANKLINEEND.search(one)

blankLine2 = lineBreak2 and self.BLANKLINESTART.match(two)

if blankLine1 or blankLine2:

# Five points for blank lines.

return 5

elif lineBreak1 or lineBreak2:

# Four points for line breaks.

return 4

elif nonAlphaNumeric1 and not whitespace1 and whitespace2:

# Three points for end of sentences.

return 3

elif whitespace1 or whitespace2:

# Two points for whitespace.

return 2

elif nonAlphaNumeric1 or nonAlphaNumeric2:

# One point for non-alphanumeric.

return 1

return 0

pointer = 1

# Intentionally ignore the first and last element (don't need checking).

while pointer < len(diffs) - 1:

if (diffs[pointer - 1][0] == self.DIFF_EQUAL and

diffs[pointer + 1][0] == self.DIFF_EQUAL):

# This is a single edit surrounded by equalities.

equality1 = diffs[pointer - 1][1]

edit = diffs[pointer][1]

equality2 = diffs[pointer + 1][1]

# First, shift the edit as far left as possible.

commonOffset = self.diff_commonSuffix(equality1, edit)

if commonOffset:

commonString = edit[-commonOffset:]

equality1 = equality1[:-commonOffset]

edit = commonString + edit[:-commonOffset]

equality2 = commonString + equality2

# Second, step character by character right, looking for the best fit.

bestEquality1 = equality1

bestEdit = edit

bestEquality2 = equality2

bestScore = (diff_cleanupSemanticScore(equality1, edit) +

diff_cleanupSemanticScore(edit, equality2))

while edit and equality2 and edit[0] == equality2[0]:

equality1 += edit[0]

edit = edit[1:] + equality2[0]

equality2 = equality2[1:]

score = (diff_cleanupSemanticScore(equality1, edit) +

diff_cleanupSemanticScore(edit, equality2))

# The >= encourages trailing rather than leading whitespace on edits.

if score >= bestScore:

bestScore = score

bestEquality1 = equality1

bestEdit = edit

bestEquality2 = equality2

if diffs[pointer - 1][1] != bestEquality1:

# We have an improvement, save it back to the diff.

if bestEquality1:

diffs[pointer - 1] = (diffs[pointer - 1][0], bestEquality1)

else:

del diffs[pointer - 1]

pointer -= 1

diffs[pointer] = (diffs[pointer][0], bestEdit)

if bestEquality2:

diffs[pointer + 1] = (diffs[pointer + 1][0], bestEquality2)

else:

del diffs[pointer + 1]

pointer -= 1

pointer += 1

# Define some regex patterns for matching boundaries.

BLANKLINEEND = re.compile(r"\n\r?\n$");

BLANKLINESTART = re.compile(r"^\r?\n\r?\n");

def diff_cleanupEfficiency(self, diffs):

"""Reduce the number of edits by eliminating operationally trivial

changes = False

equalities = [] # Stack of indices where equalities are found.

lastequality = None # Always equal to diffs[equalities[-1]][1]

pointer = 0 # Index of current position.

pre_ins = False # Is there an insertion operation before the last equality.

pre_del = False # Is there a deletion operation before the last equality.

post_ins = False # Is there an insertion operation after the last equality.

post_del = False # Is there a deletion operation after the last equality.

while pointer < len(diffs):

if diffs[pointer][0] == self.DIFF_EQUAL: # Equality found.

if (len(diffs[pointer][1]) < self.Diff_EditCost and

(post_ins or post_del)):

# Candidate found.

equalities.append(pointer)

pre_ins = post_ins

pre_del = post_del

lastequality = diffs[pointer][1]

else:

# Not a candidate, and can never become one.

equalities = []

lastequality = None

post_ins = post_del = False

else: # An insertion or deletion.

if diffs[pointer][0] == self.DIFF_DELETE:

post_del = True

else:

post_ins = True

# Five types to be split:

# <ins>A</ins><del>B</del>XY<ins>C</ins><del>D</del>

# <ins>A</ins>X<ins>C</ins><del>D</del>

# <ins>A</ins><del>B</del>X<ins>C</ins>

# <ins>A</del>X<ins>C</ins><del>D</del>

# <ins>A</ins><del>B</del>X<del>C</del>

if lastequality and ((pre_ins and pre_del and post_ins and post_del) or

((len(lastequality) < self.Diff_EditCost / 2) and

(pre_ins + pre_del + post_ins + post_del) == 3)):

# Duplicate record.

diffs.insert(equalities[-1], (self.DIFF_DELETE, lastequality))

# Change second copy to insert.

diffs[equalities[-1] + 1] = (self.DIFF_INSERT,

diffs[equalities[-1] + 1][1])

equalities.pop() # Throw away the equality we just deleted.

lastequality = None

if pre_ins and pre_del:

# No changes made which could affect previous entry, keep going.

post_ins = post_del = True

equalities = []

else:

if len(equalities):

equalities.pop() # Throw away the previous equality.

if len(equalities):

pointer = equalities[-1]

else:

pointer = -1

post_ins = post_del = False

changes = True

pointer += 1

if changes:

self.diff_cleanupMerge(diffs)

def diff_cleanupMerge(self, diffs):

"""Reorder and merge like edit sections. Merge equalities.

diffs.append((self.DIFF_EQUAL, '')) # Add a dummy entry at the end.

pointer = 0

count_delete = 0

count_insert = 0

text_delete = ''

text_insert = ''

while pointer < len(diffs):

if diffs[pointer][0] == self.DIFF_INSERT:

count_insert += 1

text_insert += diffs[pointer][1]

pointer += 1

elif diffs[pointer][0] == self.DIFF_DELETE:

count_delete += 1

text_delete += diffs[pointer][1]

pointer += 1

elif diffs[pointer][0] == self.DIFF_EQUAL:

# Upon reaching an equality, check for prior redundancies.

if count_delete + count_insert > 1:

if count_delete != 0 and count_insert != 0:

# Factor out any common prefixies.

commonlength = self.diff_commonPrefix(text_insert, text_delete)

if commonlength != 0:

x = pointer - count_delete - count_insert - 1

if x >= 0 and diffs[x][0] == self.DIFF_EQUAL:

diffs[x] = (diffs[x][0], diffs[x][1] +

text_insert[:commonlength])

else:

diffs.insert(0, (self.DIFF_EQUAL, text_insert[:commonlength]))

pointer += 1

text_insert = text_insert[commonlength:]

text_delete = text_delete[commonlength:]

# Factor out any common suffixies.

commonlength = self.diff_commonSuffix(text_insert, text_delete)

if commonlength != 0:

diffs[pointer] = (diffs[pointer][0], text_insert[-commonlength:] +

diffs[pointer][1])

text_insert = text_insert[:-commonlength]

text_delete = text_delete[:-commonlength]

# Delete the offending records and add the merged ones.

if count_delete == 0:

diffs[pointer - count_insert : pointer] = [

(self.DIFF_INSERT, text_insert)]

elif count_insert == 0:

diffs[pointer - count_delete : pointer] = [

(self.DIFF_DELETE, text_delete)]

else:

diffs[pointer - count_delete - count_insert : pointer] = [

(self.DIFF_DELETE, text_delete),

(self.DIFF_INSERT, text_insert)]

pointer = pointer - count_delete - count_insert + 1

if count_delete != 0:

pointer += 1

if count_insert != 0:

pointer += 1

elif pointer != 0 and diffs[pointer - 1][0] == self.DIFF_EQUAL:

# Merge this equality with the previous one.

diffs[pointer - 1] = (diffs[pointer - 1][0],

diffs[pointer - 1][1] + diffs[pointer][1])

del diffs[pointer]

else:

pointer += 1

count_insert = 0

count_delete = 0

text_delete = ''

text_insert = ''

if diffs[-1][1] == '':

diffs.pop() # Remove the dummy entry at the end.

# Second pass: look for single edits surrounded on both sides by equalities

# which can be shifted sideways to eliminate an equality.

# e.g: A<ins>BA</ins>C -> <ins>AB</ins>AC

changes = False

pointer = 1

# Intentionally ignore the first and last element (don't need checking).

while pointer < len(diffs) - 1:

if (diffs[pointer - 1][0] == self.DIFF_EQUAL and

diffs[pointer + 1][0] == self.DIFF_EQUAL):