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from __future__ import division
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"""Diff Match and Patch
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Copyright 2006 Google Inc.
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http://code.google.com/p/google-diff-match-patch/
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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"""
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"""Functions for diff, match and patch.
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Computes the difference between two texts to create a patch.
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Applies the patch onto another text, allowing for errors.
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"""
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__author__ = 'fraser@google.com (Neil Fraser)'
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import math
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import re
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import sys
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import time
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import urllib
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from pyramid import compat
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class diff_match_patch:
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"""Class containing the diff, match and patch methods.
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Also contains the behaviour settings.
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"""
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def __init__(self):
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"""Inits a diff_match_patch object with default settings.
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Redefine these in your program to override the defaults.
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"""
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# Number of seconds to map a diff before giving up (0 for infinity).
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self.Diff_Timeout = 1.0
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# Cost of an empty edit operation in terms of edit characters.
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self.Diff_EditCost = 4
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# At what point is no match declared (0.0 = perfection, 1.0 = very loose).
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self.Match_Threshold = 0.5
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# How far to search for a match (0 = exact location, 1000+ = broad match).
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# A match this many characters away from the expected location will add
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# 1.0 to the score (0.0 is a perfect match).
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self.Match_Distance = 1000
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# When deleting a large block of text (over ~64 characters), how close do
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# the contents have to be to match the expected contents. (0.0 = perfection,
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# 1.0 = very loose). Note that Match_Threshold controls how closely the
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# end points of a delete need to match.
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self.Patch_DeleteThreshold = 0.5
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# Chunk size for context length.
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self.Patch_Margin = 4
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# The number of bits in an int.
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# Python has no maximum, thus to disable patch splitting set to 0.
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# However to avoid long patches in certain pathological cases, use 32.
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# Multiple short patches (using native ints) are much faster than long ones.
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self.Match_MaxBits = 32
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# DIFF FUNCTIONS
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# The data structure representing a diff is an array of tuples:
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# [(DIFF_DELETE, "Hello"), (DIFF_INSERT, "Goodbye"), (DIFF_EQUAL, " world.")]
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# which means: delete "Hello", add "Goodbye" and keep " world."
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DIFF_DELETE = -1
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DIFF_INSERT = 1
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DIFF_EQUAL = 0
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def diff_main(self, text1, text2, checklines=True, deadline=None):
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"""Find the differences between two texts. Simplifies the problem by
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stripping any common prefix or suffix off the texts before diffing.
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Args:
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text1: Old string to be diffed.
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text2: New string to be diffed.
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checklines: Optional speedup flag. If present and false, then don't run
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a line-level diff first to identify the changed areas.
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Defaults to true, which does a faster, slightly less optimal diff.
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deadline: Optional time when the diff should be complete by. Used
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internally for recursive calls. Users should set DiffTimeout instead.
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Returns:
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Array of changes.
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"""
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# Set a deadline by which time the diff must be complete.
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if deadline is None:
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# Unlike in most languages, Python counts time in seconds.
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if self.Diff_Timeout <= 0:
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deadline = sys.maxint
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else:
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deadline = time.time() + self.Diff_Timeout
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# Check for null inputs.
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if text1 is None or text2 is None:
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raise ValueError("Null inputs. (diff_main)")
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# Check for equality (speedup).
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if text1 == text2:
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if text1:
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return [(self.DIFF_EQUAL, text1)]
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return []
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# Trim off common prefix (speedup).
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commonlength = self.diff_commonPrefix(text1, text2)
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commonprefix = text1[:commonlength]
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text1 = text1[commonlength:]
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text2 = text2[commonlength:]
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# Trim off common suffix (speedup).
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commonlength = self.diff_commonSuffix(text1, text2)
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if commonlength == 0:
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commonsuffix = ''
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else:
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commonsuffix = text1[-commonlength:]
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text1 = text1[:-commonlength]
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text2 = text2[:-commonlength]
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# Compute the diff on the middle block.
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diffs = self.diff_compute(text1, text2, checklines, deadline)
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# Restore the prefix and suffix.
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if commonprefix:
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diffs[:0] = [(self.DIFF_EQUAL, commonprefix)]
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if commonsuffix:
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diffs.append((self.DIFF_EQUAL, commonsuffix))
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self.diff_cleanupMerge(diffs)
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return diffs
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def diff_compute(self, text1, text2, checklines, deadline):
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"""Find the differences between two texts. Assumes that the texts do not
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have any common prefix or suffix.
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Args:
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text1: Old string to be diffed.
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text2: New string to be diffed.
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checklines: Speedup flag. If false, then don't run a line-level diff
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first to identify the changed areas.
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If true, then run a faster, slightly less optimal diff.
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deadline: Time when the diff should be complete by.
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Returns:
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Array of changes.
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"""
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if not text1:
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# Just add some text (speedup).
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return [(self.DIFF_INSERT, text2)]
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if not text2:
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# Just delete some text (speedup).
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return [(self.DIFF_DELETE, text1)]
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if len(text1) > len(text2):
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(longtext, shorttext) = (text1, text2)
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else:
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(shorttext, longtext) = (text1, text2)
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i = longtext.find(shorttext)
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if i != -1:
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# Shorter text is inside the longer text (speedup).
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diffs = [(self.DIFF_INSERT, longtext[:i]), (self.DIFF_EQUAL, shorttext),
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(self.DIFF_INSERT, longtext[i + len(shorttext):])]
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# Swap insertions for deletions if diff is reversed.
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if len(text1) > len(text2):
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diffs[0] = (self.DIFF_DELETE, diffs[0][1])
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diffs[2] = (self.DIFF_DELETE, diffs[2][1])
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return diffs
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if len(shorttext) == 1:
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# Single character string.
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# After the previous speedup, the character can't be an equality.
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return [(self.DIFF_DELETE, text1), (self.DIFF_INSERT, text2)]
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# Check to see if the problem can be split in two.
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hm = self.diff_halfMatch(text1, text2)
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if hm:
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# A half-match was found, sort out the return data.
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(text1_a, text1_b, text2_a, text2_b, mid_common) = hm
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# Send both pairs off for separate processing.
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diffs_a = self.diff_main(text1_a, text2_a, checklines, deadline)
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diffs_b = self.diff_main(text1_b, text2_b, checklines, deadline)
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# Merge the results.
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return diffs_a + [(self.DIFF_EQUAL, mid_common)] + diffs_b
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if checklines and len(text1) > 100 and len(text2) > 100:
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return self.diff_lineMode(text1, text2, deadline)
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return self.diff_bisect(text1, text2, deadline)
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def diff_lineMode(self, text1, text2, deadline):
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"""Do a quick line-level diff on both strings, then rediff the parts for
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greater accuracy.
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This speedup can produce non-minimal diffs.
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Args:
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text1: Old string to be diffed.
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text2: New string to be diffed.
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deadline: Time when the diff should be complete by.
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Returns:
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Array of changes.
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"""
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# Scan the text on a line-by-line basis first.
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(text1, text2, linearray) = self.diff_linesToChars(text1, text2)
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diffs = self.diff_main(text1, text2, False, deadline)
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# Convert the diff back to original text.
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self.diff_charsToLines(diffs, linearray)
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# Eliminate freak matches (e.g. blank lines)
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self.diff_cleanupSemantic(diffs)
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# Rediff any replacement blocks, this time character-by-character.
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# Add a dummy entry at the end.
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diffs.append((self.DIFF_EQUAL, ''))
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pointer = 0
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count_delete = 0
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count_insert = 0
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text_delete = ''
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text_insert = ''
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while pointer < len(diffs):
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if diffs[pointer][0] == self.DIFF_INSERT:
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count_insert += 1
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text_insert += diffs[pointer][1]
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elif diffs[pointer][0] == self.DIFF_DELETE:
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count_delete += 1
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text_delete += diffs[pointer][1]
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elif diffs[pointer][0] == self.DIFF_EQUAL:
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# Upon reaching an equality, check for prior redundancies.
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if count_delete >= 1 and count_insert >= 1:
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# Delete the offending records and add the merged ones.
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a = self.diff_main(text_delete, text_insert, False, deadline)
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diffs[pointer - count_delete - count_insert : pointer] = a
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pointer = pointer - count_delete - count_insert + len(a)
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count_insert = 0
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count_delete = 0
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text_delete = ''
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text_insert = ''
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pointer += 1
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diffs.pop() # Remove the dummy entry at the end.
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return diffs
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def diff_bisect(self, text1, text2, deadline):
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"""Find the 'middle snake' of a diff, split the problem in two
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and return the recursively constructed diff.
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See Myers 1986 paper: An O(ND) Difference Algorithm and Its Variations.
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Args:
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text1: Old string to be diffed.
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text2: New string to be diffed.
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deadline: Time at which to bail if not yet complete.
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Returns:
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Array of diff tuples.
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"""
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# Cache the text lengths to prevent multiple calls.
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text1_length = len(text1)
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text2_length = len(text2)
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max_d = (text1_length + text2_length + 1) // 2
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v_offset = max_d
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v_length = 2 * max_d
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v1 = [-1] * v_length
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v1[v_offset + 1] = 0
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v2 = v1[:]
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delta = text1_length - text2_length
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# If the total number of characters is odd, then the front path will
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# collide with the reverse path.
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front = (delta % 2 != 0)
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# Offsets for start and end of k loop.
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# Prevents mapping of space beyond the grid.
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k1start = 0
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k1end = 0
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k2start = 0
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k2end = 0
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for d in xrange(max_d):
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# Bail out if deadline is reached.
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if time.time() > deadline:
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break
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# Walk the front path one step.
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for k1 in xrange(-d + k1start, d + 1 - k1end, 2):
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k1_offset = v_offset + k1
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if k1 == -d or (k1 != d and
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v1[k1_offset - 1] < v1[k1_offset + 1]):
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x1 = v1[k1_offset + 1]
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else:
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x1 = v1[k1_offset - 1] + 1
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y1 = x1 - k1
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while (x1 < text1_length and y1 < text2_length and
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text1[x1] == text2[y1]):
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x1 += 1
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y1 += 1
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v1[k1_offset] = x1
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if x1 > text1_length:
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# Ran off the right of the graph.
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k1end += 2
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elif y1 > text2_length:
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# Ran off the bottom of the graph.
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k1start += 2
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elif front:
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k2_offset = v_offset + delta - k1
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if k2_offset >= 0 and k2_offset < v_length and v2[k2_offset] != -1:
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# Mirror x2 onto top-left coordinate system.
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x2 = text1_length - v2[k2_offset]
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if x1 >= x2:
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# Overlap detected.
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return self.diff_bisectSplit(text1, text2, x1, y1, deadline)
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# Walk the reverse path one step.
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for k2 in xrange(-d + k2start, d + 1 - k2end, 2):
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k2_offset = v_offset + k2
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if k2 == -d or (k2 != d and
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v2[k2_offset - 1] < v2[k2_offset + 1]):
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x2 = v2[k2_offset + 1]
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else:
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x2 = v2[k2_offset - 1] + 1
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y2 = x2 - k2
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while (x2 < text1_length and y2 < text2_length and
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text1[-x2 - 1] == text2[-y2 - 1]):
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x2 += 1
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y2 += 1
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v2[k2_offset] = x2
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if x2 > text1_length:
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# Ran off the left of the graph.
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k2end += 2
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elif y2 > text2_length:
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# Ran off the top of the graph.
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k2start += 2
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elif not front:
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k1_offset = v_offset + delta - k2
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if k1_offset >= 0 and k1_offset < v_length and v1[k1_offset] != -1:
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x1 = v1[k1_offset]
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y1 = v_offset + x1 - k1_offset
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# Mirror x2 onto top-left coordinate system.
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x2 = text1_length - x2
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if x1 >= x2:
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# Overlap detected.
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return self.diff_bisectSplit(text1, text2, x1, y1, deadline)
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# Diff took too long and hit the deadline or
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# number of diffs equals number of characters, no commonality at all.
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return [(self.DIFF_DELETE, text1), (self.DIFF_INSERT, text2)]
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def diff_bisectSplit(self, text1, text2, x, y, deadline):
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"""Given the location of the 'middle snake', split the diff in two parts
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and recurse.
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Args:
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text1: Old string to be diffed.
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text2: New string to be diffed.
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x: Index of split point in text1.
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y: Index of split point in text2.
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deadline: Time at which to bail if not yet complete.
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Returns:
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Array of diff tuples.
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"""
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text1a = text1[:x]
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text2a = text2[:y]
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text1b = text1[x:]
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text2b = text2[y:]
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# Compute both diffs serially.
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diffs = self.diff_main(text1a, text2a, False, deadline)
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diffsb = self.diff_main(text1b, text2b, False, deadline)
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return diffs + diffsb
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def diff_linesToChars(self, text1, text2):
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"""Split two texts into an array of strings. Reduce the texts to a string
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of hashes where each Unicode character represents one line.
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Args:
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text1: First string.
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text2: Second string.
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Returns:
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Three element tuple, containing the encoded text1, the encoded text2 and
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the array of unique strings. The zeroth element of the array of unique
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strings is intentionally blank.
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"""
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lineArray = [] # e.g. lineArray[4] == "Hello\n"
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lineHash = {} # e.g. lineHash["Hello\n"] == 4
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# "\x00" is a valid character, but various debuggers don't like it.
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# So we'll insert a junk entry to avoid generating a null character.
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lineArray.append('')
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def diff_linesToCharsMunge(text):
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"""Split a text into an array of strings. Reduce the texts to a string
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of hashes where each Unicode character represents one line.
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Modifies linearray and linehash through being a closure.
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Args:
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text: String to encode.
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Returns:
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Encoded string.
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"""
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chars = []
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# Walk the text, pulling out a substring for each line.
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# text.split('\n') would would temporarily double our memory footprint.
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|
|
# 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(unichr(lineHash[line]))
|
|
|
else:
|
|
|
lineArray.append(line)
|
|
|
lineHash[line] = len(lineArray) - 1
|
|
|
chars.append(unichr(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
|
|
|
of text.
|
|
|
|
|
|
Args:
|
|
|
diffs: Array of diff tuples.
|
|
|
lineArray: Array of unique strings.
|
|
|
"""
|
|
|
for x in xrange(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.
|
|
|
|
|
|
Args:
|
|
|
text1: First string.
|
|
|
text2: Second string.
|
|
|
|
|
|
Returns:
|
|
|
The number of characters common to the start of each string.
|
|
|
"""
|
|
|
# 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.
|
|
|
|
|
|
Args:
|
|
|
text1: First string.
|
|
|
text2: Second string.
|
|
|
|
|
|
Returns:
|
|
|
The number of characters common to the end of each string.
|
|
|
"""
|
|
|
# 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.
|
|
|
|
|
|
Args:
|
|
|
text1 First string.
|
|
|
text2 Second string.
|
|
|
|
|
|
Returns:
|
|
|
The number of characters common to the end of the first
|
|
|
string and the start of the second string.
|
|
|
"""
|
|
|
# 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
|
|
|
the longer text?
|
|
|
This speedup can produce non-minimal diffs.
|
|
|
|
|
|
Args:
|
|
|
text1: First string.
|
|
|
text2: Second string.
|
|
|
|
|
|
Returns:
|
|
|
Five element Array, containing the prefix of text1, the suffix of text1,
|
|
|
the prefix of text2, the suffix of text2 and the common middle. Or None
|
|
|
if there was no match.
|
|
|
"""
|
|
|
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
|
|
|
substring is at least half the length of longtext?
|
|
|
Closure, but does not reference any external variables.
|
|
|
|
|
|
Args:
|
|
|
longtext: Longer string.
|
|
|
shorttext: Shorter string.
|
|
|
i: Start index of quarter length substring within longtext.
|
|
|
|
|
|
Returns:
|
|
|
Five element Array, containing the prefix of longtext, the suffix of
|
|
|
longtext, the prefix of shorttext, the suffix of shorttext and the
|
|
|
common middle. Or None if there was no match.
|
|
|
"""
|
|
|
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
|
|
|
equalities.
|
|
|
|
|
|
Args:
|
|
|
diffs: Array of diff tuples.
|
|
|
"""
|
|
|
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
|
|
|
which can be shifted sideways to align the edit to a word boundary.
|
|
|
e.g: The c<ins>at c</ins>ame. -> The <ins>cat </ins>came.
|
|
|
|
|
|
Args:
|
|
|
diffs: Array of diff tuples.
|
|
|
"""
|
|
|
|
|
|
def diff_cleanupSemanticScore(one, two):
|
|
|
"""Given two strings, compute a score representing whether the
|
|
|
internal boundary falls on logical boundaries.
|
|
|
Scores range from 6 (best) to 0 (worst).
|
|
|
Closure, but does not reference any external variables.
|
|
|
|
|
|
Args:
|
|
|
one: First string.
|
|
|
two: Second string.
|
|
|
|
|
|
Returns:
|
|
|
The score.
|
|
|
"""
|
|
|
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
|
|
|
equalities.
|
|
|
|
|
|
Args:
|
|
|
diffs: Array of diff tuples.
|
|
|
"""
|
|
|
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.
|
|
|
Any edit section can move as long as it doesn't cross an equality.
|
|
|
|
|
|
Args:
|
|
|
diffs: Array of diff tuples.
|
|
|
"""
|
|
|
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):
|
|
|
# This is a single edit surrounded by equalities.
|
|
|
if diffs[pointer][1].endswith(diffs[pointer - 1][1]):
|
|
|
# Shift the edit over the previous equality.
|
|
|
diffs[pointer] = (diffs[pointer][0],
|
|
|
diffs[pointer - 1][1] +
|
|
|
diffs[pointer][1][:-len(diffs[pointer - 1][1])])
|
|
|
diffs[pointer + 1] = (diffs[pointer + 1][0],
|
|
|
diffs[pointer - 1][1] + diffs[pointer + 1][1])
|
|
|
del diffs[pointer - 1]
|
|
|
changes = True
|
|
|
elif diffs[pointer][1].startswith(diffs[pointer + 1][1]):
|
|
|
# Shift the edit over the next equality.
|
|
|
diffs[pointer - 1] = (diffs[pointer - 1][0],
|
|
|
diffs[pointer - 1][1] + diffs[pointer + 1][1])
|
|
|
diffs[pointer] = (diffs[pointer][0],
|
|
|
diffs[pointer][1][len(diffs[pointer + 1][1]):] +
|
|
|
diffs[pointer + 1][1])
|
|
|
del diffs[pointer + 1]
|
|
|
changes = True
|
|
|
pointer += 1
|
|
|
|
|
|
# If shifts were made, the diff needs reordering and another shift sweep.
|
|
|
if changes:
|
|
|
self.diff_cleanupMerge(diffs)
|
|
|
|
|
|
def diff_xIndex(self, diffs, loc):
|
|
|
"""loc is a location in text1, compute and return the equivalent location
|
|
|
in text2. e.g. "The cat" vs "The big cat", 1->1, 5->8
|
|
|
|
|
|
Args:
|
|
|
diffs: Array of diff tuples.
|
|
|
loc: Location within text1.
|
|
|
|
|
|
Returns:
|
|
|
Location within text2.
|
|
|
"""
|
|
|
chars1 = 0
|
|
|
chars2 = 0
|
|
|
last_chars1 = 0
|
|
|
last_chars2 = 0
|
|
|
for x in xrange(len(diffs)):
|
|
|
(op, text) = diffs[x]
|
|
|
if op != self.DIFF_INSERT: # Equality or deletion.
|
|
|
chars1 += len(text)
|
|
|
if op != self.DIFF_DELETE: # Equality or insertion.
|
|
|
chars2 += len(text)
|
|
|
if chars1 > loc: # Overshot the location.
|
|
|
break
|
|
|
last_chars1 = chars1
|
|
|
last_chars2 = chars2
|
|
|
|
|
|
if len(diffs) != x and diffs[x][0] == self.DIFF_DELETE:
|
|
|
# The location was deleted.
|
|
|
return last_chars2
|
|
|
# Add the remaining len(character).
|
|
|
return last_chars2 + (loc - last_chars1)
|
|
|
|
|
|
def diff_prettyHtml(self, diffs):
|
|
|
"""Convert a diff array into a pretty HTML report.
|
|
|
|
|
|
Args:
|
|
|
diffs: Array of diff tuples.
|
|
|
|
|
|
Returns:
|
|
|
HTML representation.
|
|
|
"""
|
|
|
html = []
|
|
|
for (op, data) in diffs:
|
|
|
text = (data.replace("&", "&").replace("<", "<")
|
|
|
.replace(">", ">").replace("\n", "¶<br>"))
|
|
|
if op == self.DIFF_INSERT:
|
|
|
html.append("<ins style=\"background:#e6ffe6;\">%s</ins>" % text)
|
|
|
elif op == self.DIFF_DELETE:
|
|
|
html.append("<del style=\"background:#ffe6e6;\">%s</del>" % text)
|
|
|
elif op == self.DIFF_EQUAL:
|
|
|
html.append("<span>%s</span>" % text)
|
|
|
return "".join(html)
|
|
|
|
|
|
def diff_text1(self, diffs):
|
|
|
"""Compute and return the source text (all equalities and deletions).
|
|
|
|
|
|
Args:
|
|
|
diffs: Array of diff tuples.
|
|
|
|
|
|
Returns:
|
|
|
Source text.
|
|
|
"""
|
|
|
text = []
|
|
|
for (op, data) in diffs:
|
|
|
if op != self.DIFF_INSERT:
|
|
|
text.append(data)
|
|
|
return "".join(text)
|
|
|
|
|
|
def diff_text2(self, diffs):
|
|
|
"""Compute and return the destination text (all equalities and insertions).
|
|
|
|
|
|
Args:
|
|
|
diffs: Array of diff tuples.
|
|
|
|
|
|
Returns:
|
|
|
Destination text.
|
|
|
"""
|
|
|
text = []
|
|
|
for (op, data) in diffs:
|
|
|
if op != self.DIFF_DELETE:
|
|
|
text.append(data)
|
|
|
return "".join(text)
|
|
|
|
|
|
def diff_levenshtein(self, diffs):
|
|
|
"""Compute the Levenshtein distance; the number of inserted, deleted or
|
|
|
substituted characters.
|
|
|
|
|
|
Args:
|
|
|
diffs: Array of diff tuples.
|
|
|
|
|
|
Returns:
|
|
|
Number of changes.
|
|
|
"""
|
|
|
levenshtein = 0
|
|
|
insertions = 0
|
|
|
deletions = 0
|
|
|
for (op, data) in diffs:
|
|
|
if op == self.DIFF_INSERT:
|
|
|
insertions += len(data)
|
|
|
elif op == self.DIFF_DELETE:
|
|
|
deletions += len(data)
|
|
|
elif op == self.DIFF_EQUAL:
|
|
|
# A deletion and an insertion is one substitution.
|
|
|
levenshtein += max(insertions, deletions)
|
|
|
insertions = 0
|
|
|
deletions = 0
|
|
|
levenshtein += max(insertions, deletions)
|
|
|
return levenshtein
|
|
|
|
|
|
def diff_toDelta(self, diffs):
|
|
|
"""Crush the diff into an encoded string which describes the operations
|
|
|
required to transform text1 into text2.
|
|
|
E.g. =3\t-2\t+ing -> Keep 3 chars, delete 2 chars, insert 'ing'.
|
|
|
Operations are tab-separated. Inserted text is escaped using %xx notation.
|
|
|
|
|
|
Args:
|
|
|
diffs: Array of diff tuples.
|
|
|
|
|
|
Returns:
|
|
|
Delta text.
|
|
|
"""
|
|
|
text = []
|
|
|
for (op, data) in diffs:
|
|
|
if op == self.DIFF_INSERT:
|
|
|
# High ascii will raise UnicodeDecodeError. Use Unicode instead.
|
|
|
data = data.encode("utf-8")
|
|
|
text.append("+" + urllib.quote(data, "!~*'();/?:@&=+$,# "))
|
|
|
elif op == self.DIFF_DELETE:
|
|
|
text.append("-%d" % len(data))
|
|
|
elif op == self.DIFF_EQUAL:
|
|
|
text.append("=%d" % len(data))
|
|
|
return "\t".join(text)
|
|
|
|
|
|
def diff_fromDelta(self, text1, delta):
|
|
|
"""Given the original text1, and an encoded string which describes the
|
|
|
operations required to transform text1 into text2, compute the full diff.
|
|
|
|
|
|
Args:
|
|
|
text1: Source string for the diff.
|
|
|
delta: Delta text.
|
|
|
|
|
|
Returns:
|
|
|
Array of diff tuples.
|
|
|
|
|
|
Raises:
|
|
|
ValueError: If invalid input.
|
|
|
"""
|
|
|
if type(delta) == unicode:
|
|
|
# Deltas should be composed of a subset of ascii chars, Unicode not
|
|
|
# required. If this encode raises UnicodeEncodeError, delta is invalid.
|
|
|
delta = delta.encode("ascii")
|
|
|
diffs = []
|
|
|
pointer = 0 # Cursor in text1
|
|
|
tokens = delta.split("\t")
|
|
|
for token in tokens:
|
|
|
if token == "":
|
|
|
# Blank tokens are ok (from a trailing \t).
|
|
|
continue
|
|
|
# Each token begins with a one character parameter which specifies the
|
|
|
# operation of this token (delete, insert, equality).
|
|
|
param = token[1:]
|
|
|
if token[0] == "+":
|
|
|
param = urllib.unquote(param).decode("utf-8")
|
|
|
diffs.append((self.DIFF_INSERT, param))
|
|
|
elif token[0] == "-" or token[0] == "=":
|
|
|
try:
|
|
|
n = int(param)
|
|
|
except ValueError:
|
|
|
raise ValueError("Invalid number in diff_fromDelta: " + param)
|
|
|
if n < 0:
|
|
|
raise ValueError("Negative number in diff_fromDelta: " + param)
|
|
|
text = text1[pointer : pointer + n]
|
|
|
pointer += n
|
|
|
if token[0] == "=":
|
|
|
diffs.append((self.DIFF_EQUAL, text))
|
|
|
else:
|
|
|
diffs.append((self.DIFF_DELETE, text))
|
|
|
else:
|
|
|
# Anything else is an error.
|
|
|
raise ValueError("Invalid diff operation in diff_fromDelta: " +
|
|
|
token[0])
|
|
|
if pointer != len(text1):
|
|
|
raise ValueError(
|
|
|
"Delta length (%d) does not equal source text length (%d)." %
|
|
|
(pointer, len(text1)))
|
|
|
return diffs
|
|
|
|
|
|
# MATCH FUNCTIONS
|
|
|
|
|
|
def match_main(self, text, pattern, loc):
|
|
|
"""Locate the best instance of 'pattern' in 'text' near 'loc'.
|
|
|
|
|
|
Args:
|
|
|
text: The text to search.
|
|
|
pattern: The pattern to search for.
|
|
|
loc: The location to search around.
|
|
|
|
|
|
Returns:
|
|
|
Best match index or -1.
|
|
|
"""
|
|
|
# Check for null inputs.
|
|
|
if text is None or pattern is None:
|
|
|
raise ValueError("Null inputs. (match_main)")
|
|
|
|
|
|
loc = max(0, min(loc, len(text)))
|
|
|
if text == pattern:
|
|
|
# Shortcut (potentially not guaranteed by the algorithm)
|
|
|
return 0
|
|
|
elif not text:
|
|
|
# Nothing to match.
|
|
|
return -1
|
|
|
elif text[loc:loc + len(pattern)] == pattern:
|
|
|
# Perfect match at the perfect spot! (Includes case of null pattern)
|
|
|
return loc
|
|
|
else:
|
|
|
# Do a fuzzy compare.
|
|
|
match = self.match_bitap(text, pattern, loc)
|
|
|
return match
|
|
|
|
|
|
def match_bitap(self, text, pattern, loc):
|
|
|
"""Locate the best instance of 'pattern' in 'text' near 'loc' using the
|
|
|
Bitap algorithm.
|
|
|
|
|
|
Args:
|
|
|
text: The text to search.
|
|
|
pattern: The pattern to search for.
|
|
|
loc: The location to search around.
|
|
|
|
|
|
Returns:
|
|
|
Best match index or -1.
|
|
|
"""
|
|
|
# Python doesn't have a maxint limit, so ignore this check.
|
|
|
#if self.Match_MaxBits != 0 and len(pattern) > self.Match_MaxBits:
|
|
|
# raise ValueError("Pattern too long for this application.")
|
|
|
|
|
|
# Initialise the alphabet.
|
|
|
s = self.match_alphabet(pattern)
|
|
|
|
|
|
def match_bitapScore(e, x):
|
|
|
"""Compute and return the score for a match with e errors and x location.
|
|
|
Accesses loc and pattern through being a closure.
|
|
|
|
|
|
Args:
|
|
|
e: Number of errors in match.
|
|
|
x: Location of match.
|
|
|
|
|
|
Returns:
|
|
|
Overall score for match (0.0 = good, 1.0 = bad).
|
|
|
"""
|
|
|
accuracy = float(e) / len(pattern)
|
|
|
proximity = abs(loc - x)
|
|
|
if not self.Match_Distance:
|
|
|
# Dodge divide by zero error.
|
|
|
return proximity and 1.0 or accuracy
|
|
|
return accuracy + (proximity / float(self.Match_Distance))
|
|
|
|
|
|
# Highest score beyond which we give up.
|
|
|
score_threshold = self.Match_Threshold
|
|
|
# Is there a nearby exact match? (speedup)
|
|
|
best_loc = text.find(pattern, loc)
|
|
|
if best_loc != -1:
|
|
|
score_threshold = min(match_bitapScore(0, best_loc), score_threshold)
|
|
|
# What about in the other direction? (speedup)
|
|
|
best_loc = text.rfind(pattern, loc + len(pattern))
|
|
|
if best_loc != -1:
|
|
|
score_threshold = min(match_bitapScore(0, best_loc), score_threshold)
|
|
|
|
|
|
# Initialise the bit arrays.
|
|
|
matchmask = 1 << (len(pattern) - 1)
|
|
|
best_loc = -1
|
|
|
|
|
|
bin_max = len(pattern) + len(text)
|
|
|
# Empty initialization added to appease pychecker.
|
|
|
last_rd = None
|
|
|
for d in xrange(len(pattern)):
|
|
|
# Scan for the best match each iteration allows for one more error.
|
|
|
# Run a binary search to determine how far from 'loc' we can stray at
|
|
|
# this error level.
|
|
|
bin_min = 0
|
|
|
bin_mid = bin_max
|
|
|
while bin_min < bin_mid:
|
|
|
if match_bitapScore(d, loc + bin_mid) <= score_threshold:
|
|
|
bin_min = bin_mid
|
|
|
else:
|
|
|
bin_max = bin_mid
|
|
|
bin_mid = (bin_max - bin_min) // 2 + bin_min
|
|
|
|
|
|
# Use the result from this iteration as the maximum for the next.
|
|
|
bin_max = bin_mid
|
|
|
start = max(1, loc - bin_mid + 1)
|
|
|
finish = min(loc + bin_mid, len(text)) + len(pattern)
|
|
|
|
|
|
rd = [0] * (finish + 2)
|
|
|
rd[finish + 1] = (1 << d) - 1
|
|
|
for j in xrange(finish, start - 1, -1):
|
|
|
if len(text) <= j - 1:
|
|
|
# Out of range.
|
|
|
charMatch = 0
|
|
|
else:
|
|
|
charMatch = s.get(text[j - 1], 0)
|
|
|
if d == 0: # First pass: exact match.
|
|
|
rd[j] = ((rd[j + 1] << 1) | 1) & charMatch
|
|
|
else: # Subsequent passes: fuzzy match.
|
|
|
rd[j] = (((rd[j + 1] << 1) | 1) & charMatch) | (
|
|
|
((last_rd[j + 1] | last_rd[j]) << 1) | 1) | last_rd[j + 1]
|
|
|
if rd[j] & matchmask:
|
|
|
score = match_bitapScore(d, j - 1)
|
|
|
# This match will almost certainly be better than any existing match.
|
|
|
# But check anyway.
|
|
|
if score <= score_threshold:
|
|
|
# Told you so.
|
|
|
score_threshold = score
|
|
|
best_loc = j - 1
|
|
|
if best_loc > loc:
|
|
|
# When passing loc, don't exceed our current distance from loc.
|
|
|
start = max(1, 2 * loc - best_loc)
|
|
|
else:
|
|
|
# Already passed loc, downhill from here on in.
|
|
|
break
|
|
|
# No hope for a (better) match at greater error levels.
|
|
|
if match_bitapScore(d + 1, loc) > score_threshold:
|
|
|
break
|
|
|
last_rd = rd
|
|
|
return best_loc
|
|
|
|
|
|
def match_alphabet(self, pattern):
|
|
|
"""Initialise the alphabet for the Bitap algorithm.
|
|
|
|
|
|
Args:
|
|
|
pattern: The text to encode.
|
|
|
|
|
|
Returns:
|
|
|
Hash of character locations.
|
|
|
"""
|
|
|
s = {}
|
|
|
for char in pattern:
|
|
|
s[char] = 0
|
|
|
for i in xrange(len(pattern)):
|
|
|
s[pattern[i]] |= 1 << (len(pattern) - i - 1)
|
|
|
return s
|
|
|
|
|
|
# PATCH FUNCTIONS
|
|
|
|
|
|
def patch_addContext(self, patch, text):
|
|
|
"""Increase the context until it is unique,
|
|
|
but don't let the pattern expand beyond Match_MaxBits.
|
|
|
|
|
|
Args:
|
|
|
patch: The patch to grow.
|
|
|
text: Source text.
|
|
|
"""
|
|
|
if len(text) == 0:
|
|
|
return
|
|
|
pattern = text[patch.start2 : patch.start2 + patch.length1]
|
|
|
padding = 0
|
|
|
|
|
|
# Look for the first and last matches of pattern in text. If two different
|
|
|
# matches are found, increase the pattern length.
|
|
|
while (text.find(pattern) != text.rfind(pattern) and (self.Match_MaxBits ==
|
|
|
0 or len(pattern) < self.Match_MaxBits - self.Patch_Margin -
|
|
|
self.Patch_Margin)):
|
|
|
padding += self.Patch_Margin
|
|
|
pattern = text[max(0, patch.start2 - padding) :
|
|
|
patch.start2 + patch.length1 + padding]
|
|
|
# Add one chunk for good luck.
|
|
|
padding += self.Patch_Margin
|
|
|
|
|
|
# Add the prefix.
|
|
|
prefix = text[max(0, patch.start2 - padding) : patch.start2]
|
|
|
if prefix:
|
|
|
patch.diffs[:0] = [(self.DIFF_EQUAL, prefix)]
|
|
|
# Add the suffix.
|
|
|
suffix = text[patch.start2 + patch.length1 :
|
|
|
patch.start2 + patch.length1 + padding]
|
|
|
if suffix:
|
|
|
patch.diffs.append((self.DIFF_EQUAL, suffix))
|
|
|
|
|
|
# Roll back the start points.
|
|
|
patch.start1 -= len(prefix)
|
|
|
patch.start2 -= len(prefix)
|
|
|
# Extend lengths.
|
|
|
patch.length1 += len(prefix) + len(suffix)
|
|
|
patch.length2 += len(prefix) + len(suffix)
|
|
|
|
|
|
def patch_make(self, a, b=None, c=None):
|
|
|
"""Compute a list of patches to turn text1 into text2.
|
|
|
Use diffs if provided, otherwise compute it ourselves.
|
|
|
There are four ways to call this function, depending on what data is
|
|
|
available to the caller:
|
|
|
Method 1:
|
|
|
a = text1, b = text2
|
|
|
Method 2:
|
|
|
a = diffs
|
|
|
Method 3 (optimal):
|
|
|
a = text1, b = diffs
|
|
|
Method 4 (deprecated, use method 3):
|
|
|
a = text1, b = text2, c = diffs
|
|
|
|
|
|
Args:
|
|
|
a: text1 (methods 1,3,4) or Array of diff tuples for text1 to
|
|
|
text2 (method 2).
|
|
|
b: text2 (methods 1,4) or Array of diff tuples for text1 to
|
|
|
text2 (method 3) or undefined (method 2).
|
|
|
c: Array of diff tuples for text1 to text2 (method 4) or
|
|
|
undefined (methods 1,2,3).
|
|
|
|
|
|
Returns:
|
|
|
Array of Patch objects.
|
|
|
"""
|
|
|
text1 = None
|
|
|
diffs = None
|
|
|
# Note that texts may arrive as 'str' or 'unicode'.
|
|
|
if isinstance(a, compat.string_types) and isinstance(b, compat.string_types) and c is None:
|
|
|
# Method 1: text1, text2
|
|
|
# Compute diffs from text1 and text2.
|
|
|
text1 = a
|
|
|
diffs = self.diff_main(text1, b, True)
|
|
|
if len(diffs) > 2:
|
|
|
self.diff_cleanupSemantic(diffs)
|
|
|
self.diff_cleanupEfficiency(diffs)
|
|
|
elif isinstance(a, list) and b is None and c is None:
|
|
|
# Method 2: diffs
|
|
|
# Compute text1 from diffs.
|
|
|
diffs = a
|
|
|
text1 = self.diff_text1(diffs)
|
|
|
elif isinstance(a, compat.string_types) and isinstance(b, list) and c is None:
|
|
|
# Method 3: text1, diffs
|
|
|
text1 = a
|
|
|
diffs = b
|
|
|
elif (isinstance(a, compat.string_types) and isinstance(b, compat.string_types) and
|
|
|
isinstance(c, list)):
|
|
|
# Method 4: text1, text2, diffs
|
|
|
# text2 is not used.
|
|
|
text1 = a
|
|
|
diffs = c
|
|
|
else:
|
|
|
raise ValueError("Unknown call format to patch_make.")
|
|
|
|
|
|
if not diffs:
|
|
|
return [] # Get rid of the None case.
|
|
|
patches = []
|
|
|
patch = patch_obj()
|
|
|
char_count1 = 0 # Number of characters into the text1 string.
|
|
|
char_count2 = 0 # Number of characters into the text2 string.
|
|
|
prepatch_text = text1 # Recreate the patches to determine context info.
|
|
|
postpatch_text = text1
|
|
|
for x in xrange(len(diffs)):
|
|
|
(diff_type, diff_text) = diffs[x]
|
|
|
if len(patch.diffs) == 0 and diff_type != self.DIFF_EQUAL:
|
|
|
# A new patch starts here.
|
|
|
patch.start1 = char_count1
|
|
|
patch.start2 = char_count2
|
|
|
if diff_type == self.DIFF_INSERT:
|
|
|
# Insertion
|
|
|
patch.diffs.append(diffs[x])
|
|
|
patch.length2 += len(diff_text)
|
|
|
postpatch_text = (postpatch_text[:char_count2] + diff_text +
|
|
|
postpatch_text[char_count2:])
|
|
|
elif diff_type == self.DIFF_DELETE:
|
|
|
# Deletion.
|
|
|
patch.length1 += len(diff_text)
|
|
|
patch.diffs.append(diffs[x])
|
|
|
postpatch_text = (postpatch_text[:char_count2] +
|
|
|
postpatch_text[char_count2 + len(diff_text):])
|
|
|
elif (diff_type == self.DIFF_EQUAL and
|
|
|
len(diff_text) <= 2 * self.Patch_Margin and
|
|
|
len(patch.diffs) != 0 and len(diffs) != x + 1):
|
|
|
# Small equality inside a patch.
|
|
|
patch.diffs.append(diffs[x])
|
|
|
patch.length1 += len(diff_text)
|
|
|
patch.length2 += len(diff_text)
|
|
|
|
|
|
if (diff_type == self.DIFF_EQUAL and
|
|
|
len(diff_text) >= 2 * self.Patch_Margin):
|
|
|
# Time for a new patch.
|
|
|
if len(patch.diffs) != 0:
|
|
|
self.patch_addContext(patch, prepatch_text)
|
|
|
patches.append(patch)
|
|
|
patch = patch_obj()
|
|
|
# Unlike Unidiff, our patch lists have a rolling context.
|
|
|
# http://code.google.com/p/google-diff-match-patch/wiki/Unidiff
|
|
|
# Update prepatch text & pos to reflect the application of the
|
|
|
# just completed patch.
|
|
|
prepatch_text = postpatch_text
|
|
|
char_count1 = char_count2
|
|
|
|
|
|
# Update the current character count.
|
|
|
if diff_type != self.DIFF_INSERT:
|
|
|
char_count1 += len(diff_text)
|
|
|
if diff_type != self.DIFF_DELETE:
|
|
|
char_count2 += len(diff_text)
|
|
|
|
|
|
# Pick up the leftover patch if not empty.
|
|
|
if len(patch.diffs) != 0:
|
|
|
self.patch_addContext(patch, prepatch_text)
|
|
|
patches.append(patch)
|
|
|
return patches
|
|
|
|
|
|
def patch_deepCopy(self, patches):
|
|
|
"""Given an array of patches, return another array that is identical.
|
|
|
|
|
|
Args:
|
|
|
patches: Array of Patch objects.
|
|
|
|
|
|
Returns:
|
|
|
Array of Patch objects.
|
|
|
"""
|
|
|
patchesCopy = []
|
|
|
for patch in patches:
|
|
|
patchCopy = patch_obj()
|
|
|
# No need to deep copy the tuples since they are immutable.
|
|
|
patchCopy.diffs = patch.diffs[:]
|
|
|
patchCopy.start1 = patch.start1
|
|
|
patchCopy.start2 = patch.start2
|
|
|
patchCopy.length1 = patch.length1
|
|
|
patchCopy.length2 = patch.length2
|
|
|
patchesCopy.append(patchCopy)
|
|
|
return patchesCopy
|
|
|
|
|
|
def patch_apply(self, patches, text):
|
|
|
"""Merge a set of patches onto the text. Return a patched text, as well
|
|
|
as a list of true/false values indicating which patches were applied.
|
|
|
|
|
|
Args:
|
|
|
patches: Array of Patch objects.
|
|
|
text: Old text.
|
|
|
|
|
|
Returns:
|
|
|
Two element Array, containing the new text and an array of boolean values.
|
|
|
"""
|
|
|
if not patches:
|
|
|
return (text, [])
|
|
|
|
|
|
# Deep copy the patches so that no changes are made to originals.
|
|
|
patches = self.patch_deepCopy(patches)
|
|
|
|
|
|
nullPadding = self.patch_addPadding(patches)
|
|
|
text = nullPadding + text + nullPadding
|
|
|
self.patch_splitMax(patches)
|
|
|
|
|
|
# delta keeps track of the offset between the expected and actual location
|
|
|
# of the previous patch. If there are patches expected at positions 10 and
|
|
|
# 20, but the first patch was found at 12, delta is 2 and the second patch
|
|
|
# has an effective expected position of 22.
|
|
|
delta = 0
|
|
|
results = []
|
|
|
for patch in patches:
|
|
|
expected_loc = patch.start2 + delta
|
|
|
text1 = self.diff_text1(patch.diffs)
|
|
|
end_loc = -1
|
|
|
if len(text1) > self.Match_MaxBits:
|
|
|
# patch_splitMax will only provide an oversized pattern in the case of
|
|
|
# a monster delete.
|
|
|
start_loc = self.match_main(text, text1[:self.Match_MaxBits],
|
|
|
expected_loc)
|
|
|
if start_loc != -1:
|
|
|
end_loc = self.match_main(text, text1[-self.Match_MaxBits:],
|
|
|
expected_loc + len(text1) - self.Match_MaxBits)
|
|
|
if end_loc == -1 or start_loc >= end_loc:
|
|
|
# Can't find valid trailing context. Drop this patch.
|
|
|
start_loc = -1
|
|
|
else:
|
|
|
start_loc = self.match_main(text, text1, expected_loc)
|
|
|
if start_loc == -1:
|
|
|
# No match found. :(
|
|
|
results.append(False)
|
|
|
# Subtract the delta for this failed patch from subsequent patches.
|
|
|
delta -= patch.length2 - patch.length1
|
|
|
else:
|
|
|
# Found a match. :)
|
|
|
results.append(True)
|
|
|
delta = start_loc - expected_loc
|
|
|
if end_loc == -1:
|
|
|
text2 = text[start_loc : start_loc + len(text1)]
|
|
|
else:
|
|
|
text2 = text[start_loc : end_loc + self.Match_MaxBits]
|
|
|
if text1 == text2:
|
|
|
# Perfect match, just shove the replacement text in.
|
|
|
text = (text[:start_loc] + self.diff_text2(patch.diffs) +
|
|
|
text[start_loc + len(text1):])
|
|
|
else:
|
|
|
# Imperfect match.
|
|
|
# Run a diff to get a framework of equivalent indices.
|
|
|
diffs = self.diff_main(text1, text2, False)
|
|
|
if (len(text1) > self.Match_MaxBits and
|
|
|
self.diff_levenshtein(diffs) / float(len(text1)) >
|
|
|
self.Patch_DeleteThreshold):
|
|
|
# The end points match, but the content is unacceptably bad.
|
|
|
results[-1] = False
|
|
|
else:
|
|
|
self.diff_cleanupSemanticLossless(diffs)
|
|
|
index1 = 0
|
|
|
for (op, data) in patch.diffs:
|
|
|
if op != self.DIFF_EQUAL:
|
|
|
index2 = self.diff_xIndex(diffs, index1)
|
|
|
if op == self.DIFF_INSERT: # Insertion
|
|
|
text = text[:start_loc + index2] + data + text[start_loc +
|
|
|
index2:]
|
|
|
elif op == self.DIFF_DELETE: # Deletion
|
|
|
text = text[:start_loc + index2] + text[start_loc +
|
|
|
self.diff_xIndex(diffs, index1 + len(data)):]
|
|
|
if op != self.DIFF_DELETE:
|
|
|
index1 += len(data)
|
|
|
# Strip the padding off.
|
|
|
text = text[len(nullPadding):-len(nullPadding)]
|
|
|
return (text, results)
|
|
|
|
|
|
def patch_addPadding(self, patches):
|
|
|
"""Add some padding on text start and end so that edges can match
|
|
|
something. Intended to be called only from within patch_apply.
|
|
|
|
|
|
Args:
|
|
|
patches: Array of Patch objects.
|
|
|
|
|
|
Returns:
|
|
|
The padding string added to each side.
|
|
|
"""
|
|
|
paddingLength = self.Patch_Margin
|
|
|
nullPadding = ""
|
|
|
for x in xrange(1, paddingLength + 1):
|
|
|
nullPadding += chr(x)
|
|
|
|
|
|
# Bump all the patches forward.
|
|
|
for patch in patches:
|
|
|
patch.start1 += paddingLength
|
|
|
patch.start2 += paddingLength
|
|
|
|
|
|
# Add some padding on start of first diff.
|
|
|
patch = patches[0]
|
|
|
diffs = patch.diffs
|
|
|
if not diffs or diffs[0][0] != self.DIFF_EQUAL:
|
|
|
# Add nullPadding equality.
|
|
|
diffs.insert(0, (self.DIFF_EQUAL, nullPadding))
|
|
|
patch.start1 -= paddingLength # Should be 0.
|
|
|
patch.start2 -= paddingLength # Should be 0.
|
|
|
patch.length1 += paddingLength
|
|
|
patch.length2 += paddingLength
|
|
|
elif paddingLength > len(diffs[0][1]):
|
|
|
# Grow first equality.
|
|
|
extraLength = paddingLength - len(diffs[0][1])
|
|
|
newText = nullPadding[len(diffs[0][1]):] + diffs[0][1]
|
|
|
diffs[0] = (diffs[0][0], newText)
|
|
|
patch.start1 -= extraLength
|
|
|
patch.start2 -= extraLength
|
|
|
patch.length1 += extraLength
|
|
|
patch.length2 += extraLength
|
|
|
|
|
|
# Add some padding on end of last diff.
|
|
|
patch = patches[-1]
|
|
|
diffs = patch.diffs
|
|
|
if not diffs or diffs[-1][0] != self.DIFF_EQUAL:
|
|
|
# Add nullPadding equality.
|
|
|
diffs.append((self.DIFF_EQUAL, nullPadding))
|
|
|
patch.length1 += paddingLength
|
|
|
patch.length2 += paddingLength
|
|
|
elif paddingLength > len(diffs[-1][1]):
|
|
|
# Grow last equality.
|
|
|
extraLength = paddingLength - len(diffs[-1][1])
|
|
|
newText = diffs[-1][1] + nullPadding[:extraLength]
|
|
|
diffs[-1] = (diffs[-1][0], newText)
|
|
|
patch.length1 += extraLength
|
|
|
patch.length2 += extraLength
|
|
|
|
|
|
return nullPadding
|
|
|
|
|
|
def patch_splitMax(self, patches):
|
|
|
"""Look through the patches and break up any which are longer than the
|
|
|
maximum limit of the match algorithm.
|
|
|
Intended to be called only from within patch_apply.
|
|
|
|
|
|
Args:
|
|
|
patches: Array of Patch objects.
|
|
|
"""
|
|
|
patch_size = self.Match_MaxBits
|
|
|
if patch_size == 0:
|
|
|
# Python has the option of not splitting strings due to its ability
|
|
|
# to handle integers of arbitrary precision.
|
|
|
return
|
|
|
for x in xrange(len(patches)):
|
|
|
if patches[x].length1 <= patch_size:
|
|
|
continue
|
|
|
bigpatch = patches[x]
|
|
|
# Remove the big old patch.
|
|
|
del patches[x]
|
|
|
x -= 1
|
|
|
start1 = bigpatch.start1
|
|
|
start2 = bigpatch.start2
|
|
|
precontext = ''
|
|
|
while len(bigpatch.diffs) != 0:
|
|
|
# Create one of several smaller patches.
|
|
|
patch = patch_obj()
|
|
|
empty = True
|
|
|
patch.start1 = start1 - len(precontext)
|
|
|
patch.start2 = start2 - len(precontext)
|
|
|
if precontext:
|
|
|
patch.length1 = patch.length2 = len(precontext)
|
|
|
patch.diffs.append((self.DIFF_EQUAL, precontext))
|
|
|
|
|
|
while (len(bigpatch.diffs) != 0 and
|
|
|
patch.length1 < patch_size - self.Patch_Margin):
|
|
|
(diff_type, diff_text) = bigpatch.diffs[0]
|
|
|
if diff_type == self.DIFF_INSERT:
|
|
|
# Insertions are harmless.
|
|
|
patch.length2 += len(diff_text)
|
|
|
start2 += len(diff_text)
|
|
|
patch.diffs.append(bigpatch.diffs.pop(0))
|
|
|
empty = False
|
|
|
elif (diff_type == self.DIFF_DELETE and len(patch.diffs) == 1 and
|
|
|
patch.diffs[0][0] == self.DIFF_EQUAL and
|
|
|
len(diff_text) > 2 * patch_size):
|
|
|
# This is a large deletion. Let it pass in one chunk.
|
|
|
patch.length1 += len(diff_text)
|
|
|
start1 += len(diff_text)
|
|
|
empty = False
|
|
|
patch.diffs.append((diff_type, diff_text))
|
|
|
del bigpatch.diffs[0]
|
|
|
else:
|
|
|
# Deletion or equality. Only take as much as we can stomach.
|
|
|
diff_text = diff_text[:patch_size - patch.length1 -
|
|
|
self.Patch_Margin]
|
|
|
patch.length1 += len(diff_text)
|
|
|
start1 += len(diff_text)
|
|
|
if diff_type == self.DIFF_EQUAL:
|
|
|
patch.length2 += len(diff_text)
|
|
|
start2 += len(diff_text)
|
|
|
else:
|
|
|
empty = False
|
|
|
|
|
|
patch.diffs.append((diff_type, diff_text))
|
|
|
if diff_text == bigpatch.diffs[0][1]:
|
|
|
del bigpatch.diffs[0]
|
|
|
else:
|
|
|
bigpatch.diffs[0] = (bigpatch.diffs[0][0],
|
|
|
bigpatch.diffs[0][1][len(diff_text):])
|
|
|
|
|
|
# Compute the head context for the next patch.
|
|
|
precontext = self.diff_text2(patch.diffs)
|
|
|
precontext = precontext[-self.Patch_Margin:]
|
|
|
# Append the end context for this patch.
|
|
|
postcontext = self.diff_text1(bigpatch.diffs)[:self.Patch_Margin]
|
|
|
if postcontext:
|
|
|
patch.length1 += len(postcontext)
|
|
|
patch.length2 += len(postcontext)
|
|
|
if len(patch.diffs) != 0 and patch.diffs[-1][0] == self.DIFF_EQUAL:
|
|
|
patch.diffs[-1] = (self.DIFF_EQUAL, patch.diffs[-1][1] +
|
|
|
postcontext)
|
|
|
else:
|
|
|
patch.diffs.append((self.DIFF_EQUAL, postcontext))
|
|
|
|
|
|
if not empty:
|
|
|
x += 1
|
|
|
patches.insert(x, patch)
|
|
|
|
|
|
def patch_toText(self, patches):
|
|
|
"""Take a list of patches and return a textual representation.
|
|
|
|
|
|
Args:
|
|
|
patches: Array of Patch objects.
|
|
|
|
|
|
Returns:
|
|
|
Text representation of patches.
|
|
|
"""
|
|
|
text = []
|
|
|
for patch in patches:
|
|
|
text.append(str(patch))
|
|
|
return "".join(text)
|
|
|
|
|
|
def patch_fromText(self, textline):
|
|
|
"""Parse a textual representation of patches and return a list of patch
|
|
|
objects.
|
|
|
|
|
|
Args:
|
|
|
textline: Text representation of patches.
|
|
|
|
|
|
Returns:
|
|
|
Array of Patch objects.
|
|
|
|
|
|
Raises:
|
|
|
ValueError: If invalid input.
|
|
|
"""
|
|
|
if type(textline) == unicode:
|
|
|
# Patches should be composed of a subset of ascii chars, Unicode not
|
|
|
# required. If this encode raises UnicodeEncodeError, patch is invalid.
|
|
|
textline = textline.encode("ascii")
|
|
|
patches = []
|
|
|
if not textline:
|
|
|
return patches
|
|
|
text = textline.split('\n')
|
|
|
while len(text) != 0:
|
|
|
m = re.match("^@@ -(\d+),?(\d*) \+(\d+),?(\d*) @@$", text[0])
|
|
|
if not m:
|
|
|
raise ValueError("Invalid patch string: " + text[0])
|
|
|
patch = patch_obj()
|
|
|
patches.append(patch)
|
|
|
patch.start1 = int(m.group(1))
|
|
|
if m.group(2) == '':
|
|
|
patch.start1 -= 1
|
|
|
patch.length1 = 1
|
|
|
elif m.group(2) == '0':
|
|
|
patch.length1 = 0
|
|
|
else:
|
|
|
patch.start1 -= 1
|
|
|
patch.length1 = int(m.group(2))
|
|
|
|
|
|
patch.start2 = int(m.group(3))
|
|
|
if m.group(4) == '':
|
|
|
patch.start2 -= 1
|
|
|
patch.length2 = 1
|
|
|
elif m.group(4) == '0':
|
|
|
patch.length2 = 0
|
|
|
else:
|
|
|
patch.start2 -= 1
|
|
|
patch.length2 = int(m.group(4))
|
|
|
|
|
|
del text[0]
|
|
|
|
|
|
while len(text) != 0:
|
|
|
if text[0]:
|
|
|
sign = text[0][0]
|
|
|
else:
|
|
|
sign = ''
|
|
|
line = urllib.unquote(text[0][1:])
|
|
|
line = line.decode("utf-8")
|
|
|
if sign == '+':
|
|
|
# Insertion.
|
|
|
patch.diffs.append((self.DIFF_INSERT, line))
|
|
|
elif sign == '-':
|
|
|
# Deletion.
|
|
|
patch.diffs.append((self.DIFF_DELETE, line))
|
|
|
elif sign == ' ':
|
|
|
# Minor equality.
|
|
|
patch.diffs.append((self.DIFF_EQUAL, line))
|
|
|
elif sign == '@':
|
|
|
# Start of next patch.
|
|
|
break
|
|
|
elif sign == '':
|
|
|
# Blank line? Whatever.
|
|
|
pass
|
|
|
else:
|
|
|
# WTF?
|
|
|
raise ValueError("Invalid patch mode: '%s'\n%s" % (sign, line))
|
|
|
del text[0]
|
|
|
return patches
|
|
|
|
|
|
|
|
|
class patch_obj:
|
|
|
"""Class representing one patch operation.
|
|
|
"""
|
|
|
|
|
|
def __init__(self):
|
|
|
"""Initializes with an empty list of diffs.
|
|
|
"""
|
|
|
self.diffs = []
|
|
|
self.start1 = None
|
|
|
self.start2 = None
|
|
|
self.length1 = 0
|
|
|
self.length2 = 0
|
|
|
|
|
|
def __str__(self):
|
|
|
"""Emmulate GNU diff's format.
|
|
|
Header: @@ -382,8 +481,9 @@
|
|
|
Indicies are printed as 1-based, not 0-based.
|
|
|
|
|
|
Returns:
|
|
|
The GNU diff string.
|
|
|
"""
|
|
|
if self.length1 == 0:
|
|
|
coords1 = str(self.start1) + ",0"
|
|
|
elif self.length1 == 1:
|
|
|
coords1 = str(self.start1 + 1)
|
|
|
else:
|
|
|
coords1 = str(self.start1 + 1) + "," + str(self.length1)
|
|
|
if self.length2 == 0:
|
|
|
coords2 = str(self.start2) + ",0"
|
|
|
elif self.length2 == 1:
|
|
|
coords2 = str(self.start2 + 1)
|
|
|
else:
|
|
|
coords2 = str(self.start2 + 1) + "," + str(self.length2)
|
|
|
text = ["@@ -", coords1, " +", coords2, " @@\n"]
|
|
|
# Escape the body of the patch with %xx notation.
|
|
|
for (op, data) in self.diffs:
|
|
|
if op == diff_match_patch.DIFF_INSERT:
|
|
|
text.append("+")
|
|
|
elif op == diff_match_patch.DIFF_DELETE:
|
|
|
text.append("-")
|
|
|
elif op == diff_match_patch.DIFF_EQUAL:
|
|
|
text.append(" ")
|
|
|
# High ascii will raise UnicodeDecodeError. Use Unicode instead.
|
|
|
data = data.encode("utf-8")
|
|
|
text.append(urllib.quote(data, "!~*'();/?:@&=+$,# ") + "\n")
|
|
|
return "".join(text)
|
