mirror of https://github.com/python/cpython
2027 lines
79 KiB
Python
2027 lines
79 KiB
Python
#! /usr/bin/env python3
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"""
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Module difflib -- helpers for computing deltas between objects.
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Function get_close_matches(word, possibilities, n=3, cutoff=0.6):
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Use SequenceMatcher to return list of the best "good enough" matches.
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Function context_diff(a, b):
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For two lists of strings, return a delta in context diff format.
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Function ndiff(a, b):
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Return a delta: the difference between `a` and `b` (lists of strings).
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Function restore(delta, which):
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Return one of the two sequences that generated an ndiff delta.
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Function unified_diff(a, b):
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For two lists of strings, return a delta in unified diff format.
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Class SequenceMatcher:
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A flexible class for comparing pairs of sequences of any type.
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Class Differ:
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For producing human-readable deltas from sequences of lines of text.
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Class HtmlDiff:
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For producing HTML side by side comparison with change highlights.
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"""
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__all__ = ['get_close_matches', 'ndiff', 'restore', 'SequenceMatcher',
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'Differ','IS_CHARACTER_JUNK', 'IS_LINE_JUNK', 'context_diff',
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'unified_diff', 'HtmlDiff', 'Match']
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import heapq
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from collections import namedtuple as _namedtuple
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Match = _namedtuple('Match', 'a b size')
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def _calculate_ratio(matches, length):
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if length:
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return 2.0 * matches / length
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return 1.0
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class SequenceMatcher:
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"""
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SequenceMatcher is a flexible class for comparing pairs of sequences of
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any type, so long as the sequence elements are hashable. The basic
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algorithm predates, and is a little fancier than, an algorithm
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published in the late 1980's by Ratcliff and Obershelp under the
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hyperbolic name "gestalt pattern matching". The basic idea is to find
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the longest contiguous matching subsequence that contains no "junk"
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elements (R-O doesn't address junk). The same idea is then applied
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recursively to the pieces of the sequences to the left and to the right
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of the matching subsequence. This does not yield minimal edit
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sequences, but does tend to yield matches that "look right" to people.
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SequenceMatcher tries to compute a "human-friendly diff" between two
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sequences. Unlike e.g. UNIX(tm) diff, the fundamental notion is the
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longest *contiguous* & junk-free matching subsequence. That's what
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catches peoples' eyes. The Windows(tm) windiff has another interesting
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notion, pairing up elements that appear uniquely in each sequence.
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That, and the method here, appear to yield more intuitive difference
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reports than does diff. This method appears to be the least vulnerable
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to synching up on blocks of "junk lines", though (like blank lines in
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ordinary text files, or maybe "<P>" lines in HTML files). That may be
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because this is the only method of the 3 that has a *concept* of
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"junk" <wink>.
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Example, comparing two strings, and considering blanks to be "junk":
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>>> s = SequenceMatcher(lambda x: x == " ",
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... "private Thread currentThread;",
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... "private volatile Thread currentThread;")
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>>>
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.ratio() returns a float in [0, 1], measuring the "similarity" of the
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sequences. As a rule of thumb, a .ratio() value over 0.6 means the
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sequences are close matches:
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>>> print(round(s.ratio(), 3))
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0.866
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>>>
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If you're only interested in where the sequences match,
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.get_matching_blocks() is handy:
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>>> for block in s.get_matching_blocks():
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... print("a[%d] and b[%d] match for %d elements" % block)
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a[0] and b[0] match for 8 elements
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a[8] and b[17] match for 21 elements
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a[29] and b[38] match for 0 elements
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Note that the last tuple returned by .get_matching_blocks() is always a
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dummy, (len(a), len(b), 0), and this is the only case in which the last
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tuple element (number of elements matched) is 0.
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If you want to know how to change the first sequence into the second,
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use .get_opcodes():
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>>> for opcode in s.get_opcodes():
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... print("%6s a[%d:%d] b[%d:%d]" % opcode)
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equal a[0:8] b[0:8]
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insert a[8:8] b[8:17]
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equal a[8:29] b[17:38]
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See the Differ class for a fancy human-friendly file differencer, which
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uses SequenceMatcher both to compare sequences of lines, and to compare
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sequences of characters within similar (near-matching) lines.
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See also function get_close_matches() in this module, which shows how
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simple code building on SequenceMatcher can be used to do useful work.
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Timing: Basic R-O is cubic time worst case and quadratic time expected
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case. SequenceMatcher is quadratic time for the worst case and has
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expected-case behavior dependent in a complicated way on how many
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elements the sequences have in common; best case time is linear.
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Methods:
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__init__(isjunk=None, a='', b='')
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Construct a SequenceMatcher.
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set_seqs(a, b)
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Set the two sequences to be compared.
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set_seq1(a)
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Set the first sequence to be compared.
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set_seq2(b)
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Set the second sequence to be compared.
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find_longest_match(alo, ahi, blo, bhi)
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Find longest matching block in a[alo:ahi] and b[blo:bhi].
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get_matching_blocks()
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Return list of triples describing matching subsequences.
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get_opcodes()
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Return list of 5-tuples describing how to turn a into b.
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ratio()
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Return a measure of the sequences' similarity (float in [0,1]).
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quick_ratio()
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Return an upper bound on .ratio() relatively quickly.
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real_quick_ratio()
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Return an upper bound on ratio() very quickly.
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"""
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def __init__(self, isjunk=None, a='', b='', autojunk=True):
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"""Construct a SequenceMatcher.
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Optional arg isjunk is None (the default), or a one-argument
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function that takes a sequence element and returns true iff the
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element is junk. None is equivalent to passing "lambda x: 0", i.e.
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no elements are considered to be junk. For example, pass
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lambda x: x in " \\t"
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if you're comparing lines as sequences of characters, and don't
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want to synch up on blanks or hard tabs.
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Optional arg a is the first of two sequences to be compared. By
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default, an empty string. The elements of a must be hashable. See
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also .set_seqs() and .set_seq1().
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Optional arg b is the second of two sequences to be compared. By
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default, an empty string. The elements of b must be hashable. See
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also .set_seqs() and .set_seq2().
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Optional arg autojunk should be set to False to disable the
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"automatic junk heuristic" that treats popular elements as junk
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(see module documentation for more information).
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"""
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# Members:
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# a
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# first sequence
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# b
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# second sequence; differences are computed as "what do
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# we need to do to 'a' to change it into 'b'?"
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# b2j
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# for x in b, b2j[x] is a list of the indices (into b)
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# at which x appears; junk elements do not appear
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# fullbcount
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# for x in b, fullbcount[x] == the number of times x
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# appears in b; only materialized if really needed (used
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# only for computing quick_ratio())
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# matching_blocks
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# a list of (i, j, k) triples, where a[i:i+k] == b[j:j+k];
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# ascending & non-overlapping in i and in j; terminated by
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# a dummy (len(a), len(b), 0) sentinel
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# opcodes
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# a list of (tag, i1, i2, j1, j2) tuples, where tag is
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# one of
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# 'replace' a[i1:i2] should be replaced by b[j1:j2]
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# 'delete' a[i1:i2] should be deleted
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# 'insert' b[j1:j2] should be inserted
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# 'equal' a[i1:i2] == b[j1:j2]
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# isjunk
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# a user-supplied function taking a sequence element and
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# returning true iff the element is "junk" -- this has
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# subtle but helpful effects on the algorithm, which I'll
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# get around to writing up someday <0.9 wink>.
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# DON'T USE! Only __chain_b uses this. Use isbjunk.
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# isbjunk
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# for x in b, isbjunk(x) == isjunk(x) but much faster;
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# it's really the __contains__ method of a hidden dict.
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# DOES NOT WORK for x in a!
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# isbpopular
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# for x in b, isbpopular(x) is true iff b is reasonably long
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# (at least 200 elements) and x accounts for more than 1 + 1% of
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# its elements (when autojunk is enabled).
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# DOES NOT WORK for x in a!
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self.isjunk = isjunk
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self.a = self.b = None
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self.autojunk = autojunk
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self.set_seqs(a, b)
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def set_seqs(self, a, b):
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"""Set the two sequences to be compared.
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>>> s = SequenceMatcher()
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>>> s.set_seqs("abcd", "bcde")
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>>> s.ratio()
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0.75
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"""
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self.set_seq1(a)
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self.set_seq2(b)
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def set_seq1(self, a):
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"""Set the first sequence to be compared.
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The second sequence to be compared is not changed.
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>>> s = SequenceMatcher(None, "abcd", "bcde")
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>>> s.ratio()
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0.75
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>>> s.set_seq1("bcde")
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>>> s.ratio()
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1.0
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>>>
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SequenceMatcher computes and caches detailed information about the
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second sequence, so if you want to compare one sequence S against
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many sequences, use .set_seq2(S) once and call .set_seq1(x)
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repeatedly for each of the other sequences.
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See also set_seqs() and set_seq2().
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"""
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if a is self.a:
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return
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self.a = a
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self.matching_blocks = self.opcodes = None
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def set_seq2(self, b):
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"""Set the second sequence to be compared.
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The first sequence to be compared is not changed.
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>>> s = SequenceMatcher(None, "abcd", "bcde")
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>>> s.ratio()
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0.75
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>>> s.set_seq2("abcd")
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>>> s.ratio()
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1.0
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>>>
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SequenceMatcher computes and caches detailed information about the
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second sequence, so if you want to compare one sequence S against
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many sequences, use .set_seq2(S) once and call .set_seq1(x)
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repeatedly for each of the other sequences.
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See also set_seqs() and set_seq1().
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"""
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if b is self.b:
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return
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self.b = b
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self.matching_blocks = self.opcodes = None
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self.fullbcount = None
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self.__chain_b()
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# For each element x in b, set b2j[x] to a list of the indices in
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# b where x appears; the indices are in increasing order; note that
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# the number of times x appears in b is len(b2j[x]) ...
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# when self.isjunk is defined, junk elements don't show up in this
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# map at all, which stops the central find_longest_match method
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# from starting any matching block at a junk element ...
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# also creates the fast isbjunk function ...
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# b2j also does not contain entries for "popular" elements, meaning
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# elements that account for more than 1 + 1% of the total elements, and
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# when the sequence is reasonably large (>= 200 elements); this can
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# be viewed as an adaptive notion of semi-junk, and yields an enormous
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# speedup when, e.g., comparing program files with hundreds of
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# instances of "return NULL;" ...
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# note that this is only called when b changes; so for cross-product
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# kinds of matches, it's best to call set_seq2 once, then set_seq1
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# repeatedly
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def __chain_b(self):
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# Because isjunk is a user-defined (not C) function, and we test
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# for junk a LOT, it's important to minimize the number of calls.
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# Before the tricks described here, __chain_b was by far the most
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# time-consuming routine in the whole module! If anyone sees
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# Jim Roskind, thank him again for profile.py -- I never would
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# have guessed that.
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# The first trick is to build b2j ignoring the possibility
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# of junk. I.e., we don't call isjunk at all yet. Throwing
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# out the junk later is much cheaper than building b2j "right"
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# from the start.
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b = self.b
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self.b2j = b2j = {}
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for i, elt in enumerate(b):
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indices = b2j.setdefault(elt, [])
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indices.append(i)
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# Purge junk elements
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junk = set()
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isjunk = self.isjunk
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if isjunk:
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for elt in list(b2j.keys()): # using list() since b2j is modified
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if isjunk(elt):
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junk.add(elt)
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del b2j[elt]
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# Purge popular elements that are not junk
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popular = set()
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n = len(b)
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if self.autojunk and n >= 200:
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ntest = n // 100 + 1
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for elt, idxs in list(b2j.items()):
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if len(idxs) > ntest:
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popular.add(elt)
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del b2j[elt]
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# Now for x in b, isjunk(x) == x in junk, but the latter is much faster.
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# Since the number of *unique* junk elements is probably small, the
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# memory burden of keeping this set alive is likely trivial compared to
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# the size of b2j.
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self.isbjunk = junk.__contains__
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self.isbpopular = popular.__contains__
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def find_longest_match(self, alo, ahi, blo, bhi):
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"""Find longest matching block in a[alo:ahi] and b[blo:bhi].
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If isjunk is not defined:
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Return (i,j,k) such that a[i:i+k] is equal to b[j:j+k], where
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alo <= i <= i+k <= ahi
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blo <= j <= j+k <= bhi
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and for all (i',j',k') meeting those conditions,
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k >= k'
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i <= i'
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and if i == i', j <= j'
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In other words, of all maximal matching blocks, return one that
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starts earliest in a, and of all those maximal matching blocks that
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start earliest in a, return the one that starts earliest in b.
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>>> s = SequenceMatcher(None, " abcd", "abcd abcd")
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>>> s.find_longest_match(0, 5, 0, 9)
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Match(a=0, b=4, size=5)
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If isjunk is defined, first the longest matching block is
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determined as above, but with the additional restriction that no
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junk element appears in the block. Then that block is extended as
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far as possible by matching (only) junk elements on both sides. So
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the resulting block never matches on junk except as identical junk
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happens to be adjacent to an "interesting" match.
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Here's the same example as before, but considering blanks to be
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junk. That prevents " abcd" from matching the " abcd" at the tail
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end of the second sequence directly. Instead only the "abcd" can
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match, and matches the leftmost "abcd" in the second sequence:
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>>> s = SequenceMatcher(lambda x: x==" ", " abcd", "abcd abcd")
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>>> s.find_longest_match(0, 5, 0, 9)
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Match(a=1, b=0, size=4)
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If no blocks match, return (alo, blo, 0).
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>>> s = SequenceMatcher(None, "ab", "c")
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>>> s.find_longest_match(0, 2, 0, 1)
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Match(a=0, b=0, size=0)
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"""
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# CAUTION: stripping common prefix or suffix would be incorrect.
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# E.g.,
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# ab
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# acab
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# Longest matching block is "ab", but if common prefix is
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# stripped, it's "a" (tied with "b"). UNIX(tm) diff does so
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# strip, so ends up claiming that ab is changed to acab by
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# inserting "ca" in the middle. That's minimal but unintuitive:
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# "it's obvious" that someone inserted "ac" at the front.
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# Windiff ends up at the same place as diff, but by pairing up
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# the unique 'b's and then matching the first two 'a's.
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a, b, b2j, isbjunk = self.a, self.b, self.b2j, self.isbjunk
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besti, bestj, bestsize = alo, blo, 0
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# find longest junk-free match
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# during an iteration of the loop, j2len[j] = length of longest
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# junk-free match ending with a[i-1] and b[j]
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j2len = {}
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nothing = []
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for i in range(alo, ahi):
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# look at all instances of a[i] in b; note that because
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# b2j has no junk keys, the loop is skipped if a[i] is junk
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j2lenget = j2len.get
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newj2len = {}
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for j in b2j.get(a[i], nothing):
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# a[i] matches b[j]
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if j < blo:
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continue
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if j >= bhi:
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break
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k = newj2len[j] = j2lenget(j-1, 0) + 1
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if k > bestsize:
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besti, bestj, bestsize = i-k+1, j-k+1, k
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j2len = newj2len
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# Extend the best by non-junk elements on each end. In particular,
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# "popular" non-junk elements aren't in b2j, which greatly speeds
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# the inner loop above, but also means "the best" match so far
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# doesn't contain any junk *or* popular non-junk elements.
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while besti > alo and bestj > blo and \
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not isbjunk(b[bestj-1]) and \
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a[besti-1] == b[bestj-1]:
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besti, bestj, bestsize = besti-1, bestj-1, bestsize+1
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while besti+bestsize < ahi and bestj+bestsize < bhi and \
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not isbjunk(b[bestj+bestsize]) and \
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a[besti+bestsize] == b[bestj+bestsize]:
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bestsize += 1
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# Now that we have a wholly interesting match (albeit possibly
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# empty!), we may as well suck up the matching junk on each
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# side of it too. Can't think of a good reason not to, and it
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# saves post-processing the (possibly considerable) expense of
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# figuring out what to do with it. In the case of an empty
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# interesting match, this is clearly the right thing to do,
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# because no other kind of match is possible in the regions.
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while besti > alo and bestj > blo and \
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isbjunk(b[bestj-1]) and \
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a[besti-1] == b[bestj-1]:
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besti, bestj, bestsize = besti-1, bestj-1, bestsize+1
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while besti+bestsize < ahi and bestj+bestsize < bhi and \
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isbjunk(b[bestj+bestsize]) and \
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a[besti+bestsize] == b[bestj+bestsize]:
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bestsize = bestsize + 1
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return Match(besti, bestj, bestsize)
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def get_matching_blocks(self):
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"""Return list of triples describing matching subsequences.
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Each triple is of the form (i, j, n), and means that
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a[i:i+n] == b[j:j+n]. The triples are monotonically increasing in
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i and in j. New in Python 2.5, it's also guaranteed that if
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(i, j, n) and (i', j', n') are adjacent triples in the list, and
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the second is not the last triple in the list, then i+n != i' or
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j+n != j'. IOW, adjacent triples never describe adjacent equal
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blocks.
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|
|
|
The last triple is a dummy, (len(a), len(b), 0), and is the only
|
|
triple with n==0.
|
|
|
|
>>> s = SequenceMatcher(None, "abxcd", "abcd")
|
|
>>> list(s.get_matching_blocks())
|
|
[Match(a=0, b=0, size=2), Match(a=3, b=2, size=2), Match(a=5, b=4, size=0)]
|
|
"""
|
|
|
|
if self.matching_blocks is not None:
|
|
return self.matching_blocks
|
|
la, lb = len(self.a), len(self.b)
|
|
|
|
# This is most naturally expressed as a recursive algorithm, but
|
|
# at least one user bumped into extreme use cases that exceeded
|
|
# the recursion limit on their box. So, now we maintain a list
|
|
# ('queue`) of blocks we still need to look at, and append partial
|
|
# results to `matching_blocks` in a loop; the matches are sorted
|
|
# at the end.
|
|
queue = [(0, la, 0, lb)]
|
|
matching_blocks = []
|
|
while queue:
|
|
alo, ahi, blo, bhi = queue.pop()
|
|
i, j, k = x = self.find_longest_match(alo, ahi, blo, bhi)
|
|
# a[alo:i] vs b[blo:j] unknown
|
|
# a[i:i+k] same as b[j:j+k]
|
|
# a[i+k:ahi] vs b[j+k:bhi] unknown
|
|
if k: # if k is 0, there was no matching block
|
|
matching_blocks.append(x)
|
|
if alo < i and blo < j:
|
|
queue.append((alo, i, blo, j))
|
|
if i+k < ahi and j+k < bhi:
|
|
queue.append((i+k, ahi, j+k, bhi))
|
|
matching_blocks.sort()
|
|
|
|
# It's possible that we have adjacent equal blocks in the
|
|
# matching_blocks list now. Starting with 2.5, this code was added
|
|
# to collapse them.
|
|
i1 = j1 = k1 = 0
|
|
non_adjacent = []
|
|
for i2, j2, k2 in matching_blocks:
|
|
# Is this block adjacent to i1, j1, k1?
|
|
if i1 + k1 == i2 and j1 + k1 == j2:
|
|
# Yes, so collapse them -- this just increases the length of
|
|
# the first block by the length of the second, and the first
|
|
# block so lengthened remains the block to compare against.
|
|
k1 += k2
|
|
else:
|
|
# Not adjacent. Remember the first block (k1==0 means it's
|
|
# the dummy we started with), and make the second block the
|
|
# new block to compare against.
|
|
if k1:
|
|
non_adjacent.append((i1, j1, k1))
|
|
i1, j1, k1 = i2, j2, k2
|
|
if k1:
|
|
non_adjacent.append((i1, j1, k1))
|
|
|
|
non_adjacent.append( (la, lb, 0) )
|
|
self.matching_blocks = non_adjacent
|
|
return map(Match._make, self.matching_blocks)
|
|
|
|
def get_opcodes(self):
|
|
"""Return list of 5-tuples describing how to turn a into b.
|
|
|
|
Each tuple is of the form (tag, i1, i2, j1, j2). The first tuple
|
|
has i1 == j1 == 0, and remaining tuples have i1 == the i2 from the
|
|
tuple preceding it, and likewise for j1 == the previous j2.
|
|
|
|
The tags are strings, with these meanings:
|
|
|
|
'replace': a[i1:i2] should be replaced by b[j1:j2]
|
|
'delete': a[i1:i2] should be deleted.
|
|
Note that j1==j2 in this case.
|
|
'insert': b[j1:j2] should be inserted at a[i1:i1].
|
|
Note that i1==i2 in this case.
|
|
'equal': a[i1:i2] == b[j1:j2]
|
|
|
|
>>> a = "qabxcd"
|
|
>>> b = "abycdf"
|
|
>>> s = SequenceMatcher(None, a, b)
|
|
>>> for tag, i1, i2, j1, j2 in s.get_opcodes():
|
|
... print(("%7s a[%d:%d] (%s) b[%d:%d] (%s)" %
|
|
... (tag, i1, i2, a[i1:i2], j1, j2, b[j1:j2])))
|
|
delete a[0:1] (q) b[0:0] ()
|
|
equal a[1:3] (ab) b[0:2] (ab)
|
|
replace a[3:4] (x) b[2:3] (y)
|
|
equal a[4:6] (cd) b[3:5] (cd)
|
|
insert a[6:6] () b[5:6] (f)
|
|
"""
|
|
|
|
if self.opcodes is not None:
|
|
return self.opcodes
|
|
i = j = 0
|
|
self.opcodes = answer = []
|
|
for ai, bj, size in self.get_matching_blocks():
|
|
# invariant: we've pumped out correct diffs to change
|
|
# a[:i] into b[:j], and the next matching block is
|
|
# a[ai:ai+size] == b[bj:bj+size]. So we need to pump
|
|
# out a diff to change a[i:ai] into b[j:bj], pump out
|
|
# the matching block, and move (i,j) beyond the match
|
|
tag = ''
|
|
if i < ai and j < bj:
|
|
tag = 'replace'
|
|
elif i < ai:
|
|
tag = 'delete'
|
|
elif j < bj:
|
|
tag = 'insert'
|
|
if tag:
|
|
answer.append( (tag, i, ai, j, bj) )
|
|
i, j = ai+size, bj+size
|
|
# the list of matching blocks is terminated by a
|
|
# sentinel with size 0
|
|
if size:
|
|
answer.append( ('equal', ai, i, bj, j) )
|
|
return answer
|
|
|
|
def get_grouped_opcodes(self, n=3):
|
|
""" Isolate change clusters by eliminating ranges with no changes.
|
|
|
|
Return a generator of groups with upto n lines of context.
|
|
Each group is in the same format as returned by get_opcodes().
|
|
|
|
>>> from pprint import pprint
|
|
>>> a = list(map(str, range(1,40)))
|
|
>>> b = a[:]
|
|
>>> b[8:8] = ['i'] # Make an insertion
|
|
>>> b[20] += 'x' # Make a replacement
|
|
>>> b[23:28] = [] # Make a deletion
|
|
>>> b[30] += 'y' # Make another replacement
|
|
>>> pprint(list(SequenceMatcher(None,a,b).get_grouped_opcodes()))
|
|
[[('equal', 5, 8, 5, 8), ('insert', 8, 8, 8, 9), ('equal', 8, 11, 9, 12)],
|
|
[('equal', 16, 19, 17, 20),
|
|
('replace', 19, 20, 20, 21),
|
|
('equal', 20, 22, 21, 23),
|
|
('delete', 22, 27, 23, 23),
|
|
('equal', 27, 30, 23, 26)],
|
|
[('equal', 31, 34, 27, 30),
|
|
('replace', 34, 35, 30, 31),
|
|
('equal', 35, 38, 31, 34)]]
|
|
"""
|
|
|
|
codes = self.get_opcodes()
|
|
if not codes:
|
|
codes = [("equal", 0, 1, 0, 1)]
|
|
# Fixup leading and trailing groups if they show no changes.
|
|
if codes[0][0] == 'equal':
|
|
tag, i1, i2, j1, j2 = codes[0]
|
|
codes[0] = tag, max(i1, i2-n), i2, max(j1, j2-n), j2
|
|
if codes[-1][0] == 'equal':
|
|
tag, i1, i2, j1, j2 = codes[-1]
|
|
codes[-1] = tag, i1, min(i2, i1+n), j1, min(j2, j1+n)
|
|
|
|
nn = n + n
|
|
group = []
|
|
for tag, i1, i2, j1, j2 in codes:
|
|
# End the current group and start a new one whenever
|
|
# there is a large range with no changes.
|
|
if tag == 'equal' and i2-i1 > nn:
|
|
group.append((tag, i1, min(i2, i1+n), j1, min(j2, j1+n)))
|
|
yield group
|
|
group = []
|
|
i1, j1 = max(i1, i2-n), max(j1, j2-n)
|
|
group.append((tag, i1, i2, j1 ,j2))
|
|
if group and not (len(group)==1 and group[0][0] == 'equal'):
|
|
yield group
|
|
|
|
def ratio(self):
|
|
"""Return a measure of the sequences' similarity (float in [0,1]).
|
|
|
|
Where T is the total number of elements in both sequences, and
|
|
M is the number of matches, this is 2.0*M / T.
|
|
Note that this is 1 if the sequences are identical, and 0 if
|
|
they have nothing in common.
|
|
|
|
.ratio() is expensive to compute if you haven't already computed
|
|
.get_matching_blocks() or .get_opcodes(), in which case you may
|
|
want to try .quick_ratio() or .real_quick_ratio() first to get an
|
|
upper bound.
|
|
|
|
>>> s = SequenceMatcher(None, "abcd", "bcde")
|
|
>>> s.ratio()
|
|
0.75
|
|
>>> s.quick_ratio()
|
|
0.75
|
|
>>> s.real_quick_ratio()
|
|
1.0
|
|
"""
|
|
|
|
matches = sum(triple[-1] for triple in self.get_matching_blocks())
|
|
return _calculate_ratio(matches, len(self.a) + len(self.b))
|
|
|
|
def quick_ratio(self):
|
|
"""Return an upper bound on ratio() relatively quickly.
|
|
|
|
This isn't defined beyond that it is an upper bound on .ratio(), and
|
|
is faster to compute.
|
|
"""
|
|
|
|
# viewing a and b as multisets, set matches to the cardinality
|
|
# of their intersection; this counts the number of matches
|
|
# without regard to order, so is clearly an upper bound
|
|
if self.fullbcount is None:
|
|
self.fullbcount = fullbcount = {}
|
|
for elt in self.b:
|
|
fullbcount[elt] = fullbcount.get(elt, 0) + 1
|
|
fullbcount = self.fullbcount
|
|
# avail[x] is the number of times x appears in 'b' less the
|
|
# number of times we've seen it in 'a' so far ... kinda
|
|
avail = {}
|
|
availhas, matches = avail.__contains__, 0
|
|
for elt in self.a:
|
|
if availhas(elt):
|
|
numb = avail[elt]
|
|
else:
|
|
numb = fullbcount.get(elt, 0)
|
|
avail[elt] = numb - 1
|
|
if numb > 0:
|
|
matches = matches + 1
|
|
return _calculate_ratio(matches, len(self.a) + len(self.b))
|
|
|
|
def real_quick_ratio(self):
|
|
"""Return an upper bound on ratio() very quickly.
|
|
|
|
This isn't defined beyond that it is an upper bound on .ratio(), and
|
|
is faster to compute than either .ratio() or .quick_ratio().
|
|
"""
|
|
|
|
la, lb = len(self.a), len(self.b)
|
|
# can't have more matches than the number of elements in the
|
|
# shorter sequence
|
|
return _calculate_ratio(min(la, lb), la + lb)
|
|
|
|
def get_close_matches(word, possibilities, n=3, cutoff=0.6):
|
|
"""Use SequenceMatcher to return list of the best "good enough" matches.
|
|
|
|
word is a sequence for which close matches are desired (typically a
|
|
string).
|
|
|
|
possibilities is a list of sequences against which to match word
|
|
(typically a list of strings).
|
|
|
|
Optional arg n (default 3) is the maximum number of close matches to
|
|
return. n must be > 0.
|
|
|
|
Optional arg cutoff (default 0.6) is a float in [0, 1]. Possibilities
|
|
that don't score at least that similar to word are ignored.
|
|
|
|
The best (no more than n) matches among the possibilities are returned
|
|
in a list, sorted by similarity score, most similar first.
|
|
|
|
>>> get_close_matches("appel", ["ape", "apple", "peach", "puppy"])
|
|
['apple', 'ape']
|
|
>>> import keyword as _keyword
|
|
>>> get_close_matches("wheel", _keyword.kwlist)
|
|
['while']
|
|
>>> get_close_matches("Apple", _keyword.kwlist)
|
|
[]
|
|
>>> get_close_matches("accept", _keyword.kwlist)
|
|
['except']
|
|
"""
|
|
|
|
if not n > 0:
|
|
raise ValueError("n must be > 0: %r" % (n,))
|
|
if not 0.0 <= cutoff <= 1.0:
|
|
raise ValueError("cutoff must be in [0.0, 1.0]: %r" % (cutoff,))
|
|
result = []
|
|
s = SequenceMatcher()
|
|
s.set_seq2(word)
|
|
for x in possibilities:
|
|
s.set_seq1(x)
|
|
if s.real_quick_ratio() >= cutoff and \
|
|
s.quick_ratio() >= cutoff and \
|
|
s.ratio() >= cutoff:
|
|
result.append((s.ratio(), x))
|
|
|
|
# Move the best scorers to head of list
|
|
result = heapq.nlargest(n, result)
|
|
# Strip scores for the best n matches
|
|
return [x for score, x in result]
|
|
|
|
def _count_leading(line, ch):
|
|
"""
|
|
Return number of `ch` characters at the start of `line`.
|
|
|
|
Example:
|
|
|
|
>>> _count_leading(' abc', ' ')
|
|
3
|
|
"""
|
|
|
|
i, n = 0, len(line)
|
|
while i < n and line[i] == ch:
|
|
i += 1
|
|
return i
|
|
|
|
class Differ:
|
|
r"""
|
|
Differ is a class for comparing sequences of lines of text, and
|
|
producing human-readable differences or deltas. Differ uses
|
|
SequenceMatcher both to compare sequences of lines, and to compare
|
|
sequences of characters within similar (near-matching) lines.
|
|
|
|
Each line of a Differ delta begins with a two-letter code:
|
|
|
|
'- ' line unique to sequence 1
|
|
'+ ' line unique to sequence 2
|
|
' ' line common to both sequences
|
|
'? ' line not present in either input sequence
|
|
|
|
Lines beginning with '? ' attempt to guide the eye to intraline
|
|
differences, and were not present in either input sequence. These lines
|
|
can be confusing if the sequences contain tab characters.
|
|
|
|
Note that Differ makes no claim to produce a *minimal* diff. To the
|
|
contrary, minimal diffs are often counter-intuitive, because they synch
|
|
up anywhere possible, sometimes accidental matches 100 pages apart.
|
|
Restricting synch points to contiguous matches preserves some notion of
|
|
locality, at the occasional cost of producing a longer diff.
|
|
|
|
Example: Comparing two texts.
|
|
|
|
First we set up the texts, sequences of individual single-line strings
|
|
ending with newlines (such sequences can also be obtained from the
|
|
`readlines()` method of file-like objects):
|
|
|
|
>>> text1 = ''' 1. Beautiful is better than ugly.
|
|
... 2. Explicit is better than implicit.
|
|
... 3. Simple is better than complex.
|
|
... 4. Complex is better than complicated.
|
|
... '''.splitlines(1)
|
|
>>> len(text1)
|
|
4
|
|
>>> text1[0][-1]
|
|
'\n'
|
|
>>> text2 = ''' 1. Beautiful is better than ugly.
|
|
... 3. Simple is better than complex.
|
|
... 4. Complicated is better than complex.
|
|
... 5. Flat is better than nested.
|
|
... '''.splitlines(1)
|
|
|
|
Next we instantiate a Differ object:
|
|
|
|
>>> d = Differ()
|
|
|
|
Note that when instantiating a Differ object we may pass functions to
|
|
filter out line and character 'junk'. See Differ.__init__ for details.
|
|
|
|
Finally, we compare the two:
|
|
|
|
>>> result = list(d.compare(text1, text2))
|
|
|
|
'result' is a list of strings, so let's pretty-print it:
|
|
|
|
>>> from pprint import pprint as _pprint
|
|
>>> _pprint(result)
|
|
[' 1. Beautiful is better than ugly.\n',
|
|
'- 2. Explicit is better than implicit.\n',
|
|
'- 3. Simple is better than complex.\n',
|
|
'+ 3. Simple is better than complex.\n',
|
|
'? ++\n',
|
|
'- 4. Complex is better than complicated.\n',
|
|
'? ^ ---- ^\n',
|
|
'+ 4. Complicated is better than complex.\n',
|
|
'? ++++ ^ ^\n',
|
|
'+ 5. Flat is better than nested.\n']
|
|
|
|
As a single multi-line string it looks like this:
|
|
|
|
>>> print(''.join(result), end="")
|
|
1. Beautiful is better than ugly.
|
|
- 2. Explicit is better than implicit.
|
|
- 3. Simple is better than complex.
|
|
+ 3. Simple is better than complex.
|
|
? ++
|
|
- 4. Complex is better than complicated.
|
|
? ^ ---- ^
|
|
+ 4. Complicated is better than complex.
|
|
? ++++ ^ ^
|
|
+ 5. Flat is better than nested.
|
|
|
|
Methods:
|
|
|
|
__init__(linejunk=None, charjunk=None)
|
|
Construct a text differencer, with optional filters.
|
|
|
|
compare(a, b)
|
|
Compare two sequences of lines; generate the resulting delta.
|
|
"""
|
|
|
|
def __init__(self, linejunk=None, charjunk=None):
|
|
"""
|
|
Construct a text differencer, with optional filters.
|
|
|
|
The two optional keyword parameters are for filter functions:
|
|
|
|
- `linejunk`: A function that should accept a single string argument,
|
|
and return true iff the string is junk. The module-level function
|
|
`IS_LINE_JUNK` may be used to filter out lines without visible
|
|
characters, except for at most one splat ('#'). It is recommended
|
|
to leave linejunk None; as of Python 2.3, the underlying
|
|
SequenceMatcher class has grown an adaptive notion of "noise" lines
|
|
that's better than any static definition the author has ever been
|
|
able to craft.
|
|
|
|
- `charjunk`: A function that should accept a string of length 1. The
|
|
module-level function `IS_CHARACTER_JUNK` may be used to filter out
|
|
whitespace characters (a blank or tab; **note**: bad idea to include
|
|
newline in this!). Use of IS_CHARACTER_JUNK is recommended.
|
|
"""
|
|
|
|
self.linejunk = linejunk
|
|
self.charjunk = charjunk
|
|
|
|
def compare(self, a, b):
|
|
r"""
|
|
Compare two sequences of lines; generate the resulting delta.
|
|
|
|
Each sequence must contain individual single-line strings ending with
|
|
newlines. Such sequences can be obtained from the `readlines()` method
|
|
of file-like objects. The delta generated also consists of newline-
|
|
terminated strings, ready to be printed as-is via the writeline()
|
|
method of a file-like object.
|
|
|
|
Example:
|
|
|
|
>>> print(''.join(Differ().compare('one\ntwo\nthree\n'.splitlines(1),
|
|
... 'ore\ntree\nemu\n'.splitlines(1))),
|
|
... end="")
|
|
- one
|
|
? ^
|
|
+ ore
|
|
? ^
|
|
- two
|
|
- three
|
|
? -
|
|
+ tree
|
|
+ emu
|
|
"""
|
|
|
|
cruncher = SequenceMatcher(self.linejunk, a, b)
|
|
for tag, alo, ahi, blo, bhi in cruncher.get_opcodes():
|
|
if tag == 'replace':
|
|
g = self._fancy_replace(a, alo, ahi, b, blo, bhi)
|
|
elif tag == 'delete':
|
|
g = self._dump('-', a, alo, ahi)
|
|
elif tag == 'insert':
|
|
g = self._dump('+', b, blo, bhi)
|
|
elif tag == 'equal':
|
|
g = self._dump(' ', a, alo, ahi)
|
|
else:
|
|
raise ValueError('unknown tag %r' % (tag,))
|
|
|
|
for line in g:
|
|
yield line
|
|
|
|
def _dump(self, tag, x, lo, hi):
|
|
"""Generate comparison results for a same-tagged range."""
|
|
for i in range(lo, hi):
|
|
yield '%s %s' % (tag, x[i])
|
|
|
|
def _plain_replace(self, a, alo, ahi, b, blo, bhi):
|
|
assert alo < ahi and blo < bhi
|
|
# dump the shorter block first -- reduces the burden on short-term
|
|
# memory if the blocks are of very different sizes
|
|
if bhi - blo < ahi - alo:
|
|
first = self._dump('+', b, blo, bhi)
|
|
second = self._dump('-', a, alo, ahi)
|
|
else:
|
|
first = self._dump('-', a, alo, ahi)
|
|
second = self._dump('+', b, blo, bhi)
|
|
|
|
for g in first, second:
|
|
for line in g:
|
|
yield line
|
|
|
|
def _fancy_replace(self, a, alo, ahi, b, blo, bhi):
|
|
r"""
|
|
When replacing one block of lines with another, search the blocks
|
|
for *similar* lines; the best-matching pair (if any) is used as a
|
|
synch point, and intraline difference marking is done on the
|
|
similar pair. Lots of work, but often worth it.
|
|
|
|
Example:
|
|
|
|
>>> d = Differ()
|
|
>>> results = d._fancy_replace(['abcDefghiJkl\n'], 0, 1,
|
|
... ['abcdefGhijkl\n'], 0, 1)
|
|
>>> print(''.join(results), end="")
|
|
- abcDefghiJkl
|
|
? ^ ^ ^
|
|
+ abcdefGhijkl
|
|
? ^ ^ ^
|
|
"""
|
|
|
|
# don't synch up unless the lines have a similarity score of at
|
|
# least cutoff; best_ratio tracks the best score seen so far
|
|
best_ratio, cutoff = 0.74, 0.75
|
|
cruncher = SequenceMatcher(self.charjunk)
|
|
eqi, eqj = None, None # 1st indices of equal lines (if any)
|
|
|
|
# search for the pair that matches best without being identical
|
|
# (identical lines must be junk lines, & we don't want to synch up
|
|
# on junk -- unless we have to)
|
|
for j in range(blo, bhi):
|
|
bj = b[j]
|
|
cruncher.set_seq2(bj)
|
|
for i in range(alo, ahi):
|
|
ai = a[i]
|
|
if ai == bj:
|
|
if eqi is None:
|
|
eqi, eqj = i, j
|
|
continue
|
|
cruncher.set_seq1(ai)
|
|
# computing similarity is expensive, so use the quick
|
|
# upper bounds first -- have seen this speed up messy
|
|
# compares by a factor of 3.
|
|
# note that ratio() is only expensive to compute the first
|
|
# time it's called on a sequence pair; the expensive part
|
|
# of the computation is cached by cruncher
|
|
if cruncher.real_quick_ratio() > best_ratio and \
|
|
cruncher.quick_ratio() > best_ratio and \
|
|
cruncher.ratio() > best_ratio:
|
|
best_ratio, best_i, best_j = cruncher.ratio(), i, j
|
|
if best_ratio < cutoff:
|
|
# no non-identical "pretty close" pair
|
|
if eqi is None:
|
|
# no identical pair either -- treat it as a straight replace
|
|
for line in self._plain_replace(a, alo, ahi, b, blo, bhi):
|
|
yield line
|
|
return
|
|
# no close pair, but an identical pair -- synch up on that
|
|
best_i, best_j, best_ratio = eqi, eqj, 1.0
|
|
else:
|
|
# there's a close pair, so forget the identical pair (if any)
|
|
eqi = None
|
|
|
|
# a[best_i] very similar to b[best_j]; eqi is None iff they're not
|
|
# identical
|
|
|
|
# pump out diffs from before the synch point
|
|
for line in self._fancy_helper(a, alo, best_i, b, blo, best_j):
|
|
yield line
|
|
|
|
# do intraline marking on the synch pair
|
|
aelt, belt = a[best_i], b[best_j]
|
|
if eqi is None:
|
|
# pump out a '-', '?', '+', '?' quad for the synched lines
|
|
atags = btags = ""
|
|
cruncher.set_seqs(aelt, belt)
|
|
for tag, ai1, ai2, bj1, bj2 in cruncher.get_opcodes():
|
|
la, lb = ai2 - ai1, bj2 - bj1
|
|
if tag == 'replace':
|
|
atags += '^' * la
|
|
btags += '^' * lb
|
|
elif tag == 'delete':
|
|
atags += '-' * la
|
|
elif tag == 'insert':
|
|
btags += '+' * lb
|
|
elif tag == 'equal':
|
|
atags += ' ' * la
|
|
btags += ' ' * lb
|
|
else:
|
|
raise ValueError('unknown tag %r' % (tag,))
|
|
for line in self._qformat(aelt, belt, atags, btags):
|
|
yield line
|
|
else:
|
|
# the synch pair is identical
|
|
yield ' ' + aelt
|
|
|
|
# pump out diffs from after the synch point
|
|
for line in self._fancy_helper(a, best_i+1, ahi, b, best_j+1, bhi):
|
|
yield line
|
|
|
|
def _fancy_helper(self, a, alo, ahi, b, blo, bhi):
|
|
g = []
|
|
if alo < ahi:
|
|
if blo < bhi:
|
|
g = self._fancy_replace(a, alo, ahi, b, blo, bhi)
|
|
else:
|
|
g = self._dump('-', a, alo, ahi)
|
|
elif blo < bhi:
|
|
g = self._dump('+', b, blo, bhi)
|
|
|
|
for line in g:
|
|
yield line
|
|
|
|
def _qformat(self, aline, bline, atags, btags):
|
|
r"""
|
|
Format "?" output and deal with leading tabs.
|
|
|
|
Example:
|
|
|
|
>>> d = Differ()
|
|
>>> results = d._qformat('\tabcDefghiJkl\n', '\tabcdefGhijkl\n',
|
|
... ' ^ ^ ^ ', ' ^ ^ ^ ')
|
|
>>> for line in results: print(repr(line))
|
|
...
|
|
'- \tabcDefghiJkl\n'
|
|
'? \t ^ ^ ^\n'
|
|
'+ \tabcdefGhijkl\n'
|
|
'? \t ^ ^ ^\n'
|
|
"""
|
|
|
|
# Can hurt, but will probably help most of the time.
|
|
common = min(_count_leading(aline, "\t"),
|
|
_count_leading(bline, "\t"))
|
|
common = min(common, _count_leading(atags[:common], " "))
|
|
common = min(common, _count_leading(btags[:common], " "))
|
|
atags = atags[common:].rstrip()
|
|
btags = btags[common:].rstrip()
|
|
|
|
yield "- " + aline
|
|
if atags:
|
|
yield "? %s%s\n" % ("\t" * common, atags)
|
|
|
|
yield "+ " + bline
|
|
if btags:
|
|
yield "? %s%s\n" % ("\t" * common, btags)
|
|
|
|
# With respect to junk, an earlier version of ndiff simply refused to
|
|
# *start* a match with a junk element. The result was cases like this:
|
|
# before: private Thread currentThread;
|
|
# after: private volatile Thread currentThread;
|
|
# If you consider whitespace to be junk, the longest contiguous match
|
|
# not starting with junk is "e Thread currentThread". So ndiff reported
|
|
# that "e volatil" was inserted between the 't' and the 'e' in "private".
|
|
# While an accurate view, to people that's absurd. The current version
|
|
# looks for matching blocks that are entirely junk-free, then extends the
|
|
# longest one of those as far as possible but only with matching junk.
|
|
# So now "currentThread" is matched, then extended to suck up the
|
|
# preceding blank; then "private" is matched, and extended to suck up the
|
|
# following blank; then "Thread" is matched; and finally ndiff reports
|
|
# that "volatile " was inserted before "Thread". The only quibble
|
|
# remaining is that perhaps it was really the case that " volatile"
|
|
# was inserted after "private". I can live with that <wink>.
|
|
|
|
import re
|
|
|
|
def IS_LINE_JUNK(line, pat=re.compile(r"\s*#?\s*$").match):
|
|
r"""
|
|
Return 1 for ignorable line: iff `line` is blank or contains a single '#'.
|
|
|
|
Examples:
|
|
|
|
>>> IS_LINE_JUNK('\n')
|
|
True
|
|
>>> IS_LINE_JUNK(' # \n')
|
|
True
|
|
>>> IS_LINE_JUNK('hello\n')
|
|
False
|
|
"""
|
|
|
|
return pat(line) is not None
|
|
|
|
def IS_CHARACTER_JUNK(ch, ws=" \t"):
|
|
r"""
|
|
Return 1 for ignorable character: iff `ch` is a space or tab.
|
|
|
|
Examples:
|
|
|
|
>>> IS_CHARACTER_JUNK(' ')
|
|
True
|
|
>>> IS_CHARACTER_JUNK('\t')
|
|
True
|
|
>>> IS_CHARACTER_JUNK('\n')
|
|
False
|
|
>>> IS_CHARACTER_JUNK('x')
|
|
False
|
|
"""
|
|
|
|
return ch in ws
|
|
|
|
|
|
def unified_diff(a, b, fromfile='', tofile='', fromfiledate='',
|
|
tofiledate='', n=3, lineterm='\n'):
|
|
r"""
|
|
Compare two sequences of lines; generate the delta as a unified diff.
|
|
|
|
Unified diffs are a compact way of showing line changes and a few
|
|
lines of context. The number of context lines is set by 'n' which
|
|
defaults to three.
|
|
|
|
By default, the diff control lines (those with ---, +++, or @@) are
|
|
created with a trailing newline. This is helpful so that inputs
|
|
created from file.readlines() result in diffs that are suitable for
|
|
file.writelines() since both the inputs and outputs have trailing
|
|
newlines.
|
|
|
|
For inputs that do not have trailing newlines, set the lineterm
|
|
argument to "" so that the output will be uniformly newline free.
|
|
|
|
The unidiff format normally has a header for filenames and modification
|
|
times. Any or all of these may be specified using strings for
|
|
'fromfile', 'tofile', 'fromfiledate', and 'tofiledate'.
|
|
The modification times are normally expressed in the ISO 8601 format.
|
|
|
|
Example:
|
|
|
|
>>> for line in unified_diff('one two three four'.split(),
|
|
... 'zero one tree four'.split(), 'Original', 'Current',
|
|
... '2005-01-26 23:30:50', '2010-04-02 10:20:52',
|
|
... lineterm=''):
|
|
... print(line) # doctest: +NORMALIZE_WHITESPACE
|
|
--- Original 2005-01-26 23:30:50
|
|
+++ Current 2010-04-02 10:20:52
|
|
@@ -1,4 +1,4 @@
|
|
+zero
|
|
one
|
|
-two
|
|
-three
|
|
+tree
|
|
four
|
|
"""
|
|
|
|
started = False
|
|
for group in SequenceMatcher(None,a,b).get_grouped_opcodes(n):
|
|
if not started:
|
|
fromdate = '\t%s' % fromfiledate if fromfiledate else ''
|
|
todate = '\t%s' % tofiledate if tofiledate else ''
|
|
yield '--- %s%s%s' % (fromfile, fromdate, lineterm)
|
|
yield '+++ %s%s%s' % (tofile, todate, lineterm)
|
|
started = True
|
|
i1, i2, j1, j2 = group[0][1], group[-1][2], group[0][3], group[-1][4]
|
|
yield "@@ -%d,%d +%d,%d @@%s" % (i1+1, i2-i1, j1+1, j2-j1, lineterm)
|
|
for tag, i1, i2, j1, j2 in group:
|
|
if tag == 'equal':
|
|
for line in a[i1:i2]:
|
|
yield ' ' + line
|
|
continue
|
|
if tag == 'replace' or tag == 'delete':
|
|
for line in a[i1:i2]:
|
|
yield '-' + line
|
|
if tag == 'replace' or tag == 'insert':
|
|
for line in b[j1:j2]:
|
|
yield '+' + line
|
|
|
|
# See http://www.unix.org/single_unix_specification/
|
|
def context_diff(a, b, fromfile='', tofile='',
|
|
fromfiledate='', tofiledate='', n=3, lineterm='\n'):
|
|
r"""
|
|
Compare two sequences of lines; generate the delta as a context diff.
|
|
|
|
Context diffs are a compact way of showing line changes and a few
|
|
lines of context. The number of context lines is set by 'n' which
|
|
defaults to three.
|
|
|
|
By default, the diff control lines (those with *** or ---) are
|
|
created with a trailing newline. This is helpful so that inputs
|
|
created from file.readlines() result in diffs that are suitable for
|
|
file.writelines() since both the inputs and outputs have trailing
|
|
newlines.
|
|
|
|
For inputs that do not have trailing newlines, set the lineterm
|
|
argument to "" so that the output will be uniformly newline free.
|
|
|
|
The context diff format normally has a header for filenames and
|
|
modification times. Any or all of these may be specified using
|
|
strings for 'fromfile', 'tofile', 'fromfiledate', and 'tofiledate'.
|
|
The modification times are normally expressed in the ISO 8601 format.
|
|
If not specified, the strings default to blanks.
|
|
|
|
Example:
|
|
|
|
>>> print(''.join(context_diff('one\ntwo\nthree\nfour\n'.splitlines(1),
|
|
... 'zero\none\ntree\nfour\n'.splitlines(1), 'Original', 'Current')),
|
|
... end="")
|
|
*** Original
|
|
--- Current
|
|
***************
|
|
*** 1,4 ****
|
|
one
|
|
! two
|
|
! three
|
|
four
|
|
--- 1,4 ----
|
|
+ zero
|
|
one
|
|
! tree
|
|
four
|
|
"""
|
|
|
|
started = False
|
|
prefixmap = {'insert':'+ ', 'delete':'- ', 'replace':'! ', 'equal':' '}
|
|
for group in SequenceMatcher(None,a,b).get_grouped_opcodes(n):
|
|
if not started:
|
|
fromdate = '\t%s' % fromfiledate if fromfiledate else ''
|
|
todate = '\t%s' % tofiledate if tofiledate else ''
|
|
yield '*** %s%s%s' % (fromfile, fromdate, lineterm)
|
|
yield '--- %s%s%s' % (tofile, todate, lineterm)
|
|
started = True
|
|
|
|
yield '***************%s' % (lineterm,)
|
|
if group[-1][2] - group[0][1] >= 2:
|
|
yield '*** %d,%d ****%s' % (group[0][1]+1, group[-1][2], lineterm)
|
|
else:
|
|
yield '*** %d ****%s' % (group[-1][2], lineterm)
|
|
visiblechanges = [e for e in group if e[0] in ('replace', 'delete')]
|
|
if visiblechanges:
|
|
for tag, i1, i2, _, _ in group:
|
|
if tag != 'insert':
|
|
for line in a[i1:i2]:
|
|
yield prefixmap[tag] + line
|
|
|
|
if group[-1][4] - group[0][3] >= 2:
|
|
yield '--- %d,%d ----%s' % (group[0][3]+1, group[-1][4], lineterm)
|
|
else:
|
|
yield '--- %d ----%s' % (group[-1][4], lineterm)
|
|
visiblechanges = [e for e in group if e[0] in ('replace', 'insert')]
|
|
if visiblechanges:
|
|
for tag, _, _, j1, j2 in group:
|
|
if tag != 'delete':
|
|
for line in b[j1:j2]:
|
|
yield prefixmap[tag] + line
|
|
|
|
def ndiff(a, b, linejunk=None, charjunk=IS_CHARACTER_JUNK):
|
|
r"""
|
|
Compare `a` and `b` (lists of strings); return a `Differ`-style delta.
|
|
|
|
Optional keyword parameters `linejunk` and `charjunk` are for filter
|
|
functions (or None):
|
|
|
|
- linejunk: A function that should accept a single string argument, and
|
|
return true iff the string is junk. The default is None, and is
|
|
recommended; as of Python 2.3, an adaptive notion of "noise" lines is
|
|
used that does a good job on its own.
|
|
|
|
- charjunk: A function that should accept a string of length 1. The
|
|
default is module-level function IS_CHARACTER_JUNK, which filters out
|
|
whitespace characters (a blank or tab; note: bad idea to include newline
|
|
in this!).
|
|
|
|
Tools/scripts/ndiff.py is a command-line front-end to this function.
|
|
|
|
Example:
|
|
|
|
>>> diff = ndiff('one\ntwo\nthree\n'.splitlines(1),
|
|
... 'ore\ntree\nemu\n'.splitlines(1))
|
|
>>> print(''.join(diff), end="")
|
|
- one
|
|
? ^
|
|
+ ore
|
|
? ^
|
|
- two
|
|
- three
|
|
? -
|
|
+ tree
|
|
+ emu
|
|
"""
|
|
return Differ(linejunk, charjunk).compare(a, b)
|
|
|
|
def _mdiff(fromlines, tolines, context=None, linejunk=None,
|
|
charjunk=IS_CHARACTER_JUNK):
|
|
r"""Returns generator yielding marked up from/to side by side differences.
|
|
|
|
Arguments:
|
|
fromlines -- list of text lines to compared to tolines
|
|
tolines -- list of text lines to be compared to fromlines
|
|
context -- number of context lines to display on each side of difference,
|
|
if None, all from/to text lines will be generated.
|
|
linejunk -- passed on to ndiff (see ndiff documentation)
|
|
charjunk -- passed on to ndiff (see ndiff documentation)
|
|
|
|
This function returns an interator which returns a tuple:
|
|
(from line tuple, to line tuple, boolean flag)
|
|
|
|
from/to line tuple -- (line num, line text)
|
|
line num -- integer or None (to indicate a context separation)
|
|
line text -- original line text with following markers inserted:
|
|
'\0+' -- marks start of added text
|
|
'\0-' -- marks start of deleted text
|
|
'\0^' -- marks start of changed text
|
|
'\1' -- marks end of added/deleted/changed text
|
|
|
|
boolean flag -- None indicates context separation, True indicates
|
|
either "from" or "to" line contains a change, otherwise False.
|
|
|
|
This function/iterator was originally developed to generate side by side
|
|
file difference for making HTML pages (see HtmlDiff class for example
|
|
usage).
|
|
|
|
Note, this function utilizes the ndiff function to generate the side by
|
|
side difference markup. Optional ndiff arguments may be passed to this
|
|
function and they in turn will be passed to ndiff.
|
|
"""
|
|
import re
|
|
|
|
# regular expression for finding intraline change indices
|
|
change_re = re.compile('(\++|\-+|\^+)')
|
|
|
|
# create the difference iterator to generate the differences
|
|
diff_lines_iterator = ndiff(fromlines,tolines,linejunk,charjunk)
|
|
|
|
def _make_line(lines, format_key, side, num_lines=[0,0]):
|
|
"""Returns line of text with user's change markup and line formatting.
|
|
|
|
lines -- list of lines from the ndiff generator to produce a line of
|
|
text from. When producing the line of text to return, the
|
|
lines used are removed from this list.
|
|
format_key -- '+' return first line in list with "add" markup around
|
|
the entire line.
|
|
'-' return first line in list with "delete" markup around
|
|
the entire line.
|
|
'?' return first line in list with add/delete/change
|
|
intraline markup (indices obtained from second line)
|
|
None return first line in list with no markup
|
|
side -- indice into the num_lines list (0=from,1=to)
|
|
num_lines -- from/to current line number. This is NOT intended to be a
|
|
passed parameter. It is present as a keyword argument to
|
|
maintain memory of the current line numbers between calls
|
|
of this function.
|
|
|
|
Note, this function is purposefully not defined at the module scope so
|
|
that data it needs from its parent function (within whose context it
|
|
is defined) does not need to be of module scope.
|
|
"""
|
|
num_lines[side] += 1
|
|
# Handle case where no user markup is to be added, just return line of
|
|
# text with user's line format to allow for usage of the line number.
|
|
if format_key is None:
|
|
return (num_lines[side],lines.pop(0)[2:])
|
|
# Handle case of intraline changes
|
|
if format_key == '?':
|
|
text, markers = lines.pop(0), lines.pop(0)
|
|
# find intraline changes (store change type and indices in tuples)
|
|
sub_info = []
|
|
def record_sub_info(match_object,sub_info=sub_info):
|
|
sub_info.append([match_object.group(1)[0],match_object.span()])
|
|
return match_object.group(1)
|
|
change_re.sub(record_sub_info,markers)
|
|
# process each tuple inserting our special marks that won't be
|
|
# noticed by an xml/html escaper.
|
|
for key,(begin,end) in sub_info[::-1]:
|
|
text = text[0:begin]+'\0'+key+text[begin:end]+'\1'+text[end:]
|
|
text = text[2:]
|
|
# Handle case of add/delete entire line
|
|
else:
|
|
text = lines.pop(0)[2:]
|
|
# if line of text is just a newline, insert a space so there is
|
|
# something for the user to highlight and see.
|
|
if not text:
|
|
text = ' '
|
|
# insert marks that won't be noticed by an xml/html escaper.
|
|
text = '\0' + format_key + text + '\1'
|
|
# Return line of text, first allow user's line formatter to do its
|
|
# thing (such as adding the line number) then replace the special
|
|
# marks with what the user's change markup.
|
|
return (num_lines[side],text)
|
|
|
|
def _line_iterator():
|
|
"""Yields from/to lines of text with a change indication.
|
|
|
|
This function is an iterator. It itself pulls lines from a
|
|
differencing iterator, processes them and yields them. When it can
|
|
it yields both a "from" and a "to" line, otherwise it will yield one
|
|
or the other. In addition to yielding the lines of from/to text, a
|
|
boolean flag is yielded to indicate if the text line(s) have
|
|
differences in them.
|
|
|
|
Note, this function is purposefully not defined at the module scope so
|
|
that data it needs from its parent function (within whose context it
|
|
is defined) does not need to be of module scope.
|
|
"""
|
|
lines = []
|
|
num_blanks_pending, num_blanks_to_yield = 0, 0
|
|
while True:
|
|
# Load up next 4 lines so we can look ahead, create strings which
|
|
# are a concatenation of the first character of each of the 4 lines
|
|
# so we can do some very readable comparisons.
|
|
while len(lines) < 4:
|
|
try:
|
|
lines.append(next(diff_lines_iterator))
|
|
except StopIteration:
|
|
lines.append('X')
|
|
s = ''.join([line[0] for line in lines])
|
|
if s.startswith('X'):
|
|
# When no more lines, pump out any remaining blank lines so the
|
|
# corresponding add/delete lines get a matching blank line so
|
|
# all line pairs get yielded at the next level.
|
|
num_blanks_to_yield = num_blanks_pending
|
|
elif s.startswith('-?+?'):
|
|
# simple intraline change
|
|
yield _make_line(lines,'?',0), _make_line(lines,'?',1), True
|
|
continue
|
|
elif s.startswith('--++'):
|
|
# in delete block, add block coming: we do NOT want to get
|
|
# caught up on blank lines yet, just process the delete line
|
|
num_blanks_pending -= 1
|
|
yield _make_line(lines,'-',0), None, True
|
|
continue
|
|
elif s.startswith(('--?+', '--+', '- ')):
|
|
# in delete block and see a intraline change or unchanged line
|
|
# coming: yield the delete line and then blanks
|
|
from_line,to_line = _make_line(lines,'-',0), None
|
|
num_blanks_to_yield,num_blanks_pending = num_blanks_pending-1,0
|
|
elif s.startswith('-+?'):
|
|
# intraline change
|
|
yield _make_line(lines,None,0), _make_line(lines,'?',1), True
|
|
continue
|
|
elif s.startswith('-?+'):
|
|
# intraline change
|
|
yield _make_line(lines,'?',0), _make_line(lines,None,1), True
|
|
continue
|
|
elif s.startswith('-'):
|
|
# delete FROM line
|
|
num_blanks_pending -= 1
|
|
yield _make_line(lines,'-',0), None, True
|
|
continue
|
|
elif s.startswith('+--'):
|
|
# in add block, delete block coming: we do NOT want to get
|
|
# caught up on blank lines yet, just process the add line
|
|
num_blanks_pending += 1
|
|
yield None, _make_line(lines,'+',1), True
|
|
continue
|
|
elif s.startswith(('+ ', '+-')):
|
|
# will be leaving an add block: yield blanks then add line
|
|
from_line, to_line = None, _make_line(lines,'+',1)
|
|
num_blanks_to_yield,num_blanks_pending = num_blanks_pending+1,0
|
|
elif s.startswith('+'):
|
|
# inside an add block, yield the add line
|
|
num_blanks_pending += 1
|
|
yield None, _make_line(lines,'+',1), True
|
|
continue
|
|
elif s.startswith(' '):
|
|
# unchanged text, yield it to both sides
|
|
yield _make_line(lines[:],None,0),_make_line(lines,None,1),False
|
|
continue
|
|
# Catch up on the blank lines so when we yield the next from/to
|
|
# pair, they are lined up.
|
|
while(num_blanks_to_yield < 0):
|
|
num_blanks_to_yield += 1
|
|
yield None,('','\n'),True
|
|
while(num_blanks_to_yield > 0):
|
|
num_blanks_to_yield -= 1
|
|
yield ('','\n'),None,True
|
|
if s.startswith('X'):
|
|
raise StopIteration
|
|
else:
|
|
yield from_line,to_line,True
|
|
|
|
def _line_pair_iterator():
|
|
"""Yields from/to lines of text with a change indication.
|
|
|
|
This function is an iterator. It itself pulls lines from the line
|
|
iterator. Its difference from that iterator is that this function
|
|
always yields a pair of from/to text lines (with the change
|
|
indication). If necessary it will collect single from/to lines
|
|
until it has a matching pair from/to pair to yield.
|
|
|
|
Note, this function is purposefully not defined at the module scope so
|
|
that data it needs from its parent function (within whose context it
|
|
is defined) does not need to be of module scope.
|
|
"""
|
|
line_iterator = _line_iterator()
|
|
fromlines,tolines=[],[]
|
|
while True:
|
|
# Collecting lines of text until we have a from/to pair
|
|
while (len(fromlines)==0 or len(tolines)==0):
|
|
from_line, to_line, found_diff = next(line_iterator)
|
|
if from_line is not None:
|
|
fromlines.append((from_line,found_diff))
|
|
if to_line is not None:
|
|
tolines.append((to_line,found_diff))
|
|
# Once we have a pair, remove them from the collection and yield it
|
|
from_line, fromDiff = fromlines.pop(0)
|
|
to_line, to_diff = tolines.pop(0)
|
|
yield (from_line,to_line,fromDiff or to_diff)
|
|
|
|
# Handle case where user does not want context differencing, just yield
|
|
# them up without doing anything else with them.
|
|
line_pair_iterator = _line_pair_iterator()
|
|
if context is None:
|
|
while True:
|
|
yield next(line_pair_iterator)
|
|
# Handle case where user wants context differencing. We must do some
|
|
# storage of lines until we know for sure that they are to be yielded.
|
|
else:
|
|
context += 1
|
|
lines_to_write = 0
|
|
while True:
|
|
# Store lines up until we find a difference, note use of a
|
|
# circular queue because we only need to keep around what
|
|
# we need for context.
|
|
index, contextLines = 0, [None]*(context)
|
|
found_diff = False
|
|
while(found_diff is False):
|
|
from_line, to_line, found_diff = next(line_pair_iterator)
|
|
i = index % context
|
|
contextLines[i] = (from_line, to_line, found_diff)
|
|
index += 1
|
|
# Yield lines that we have collected so far, but first yield
|
|
# the user's separator.
|
|
if index > context:
|
|
yield None, None, None
|
|
lines_to_write = context
|
|
else:
|
|
lines_to_write = index
|
|
index = 0
|
|
while(lines_to_write):
|
|
i = index % context
|
|
index += 1
|
|
yield contextLines[i]
|
|
lines_to_write -= 1
|
|
# Now yield the context lines after the change
|
|
lines_to_write = context-1
|
|
while(lines_to_write):
|
|
from_line, to_line, found_diff = next(line_pair_iterator)
|
|
# If another change within the context, extend the context
|
|
if found_diff:
|
|
lines_to_write = context-1
|
|
else:
|
|
lines_to_write -= 1
|
|
yield from_line, to_line, found_diff
|
|
|
|
|
|
_file_template = """
|
|
<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN"
|
|
"http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd">
|
|
|
|
<html>
|
|
|
|
<head>
|
|
<meta http-equiv="Content-Type"
|
|
content="text/html; charset=ISO-8859-1" />
|
|
<title></title>
|
|
<style type="text/css">%(styles)s
|
|
</style>
|
|
</head>
|
|
|
|
<body>
|
|
%(table)s%(legend)s
|
|
</body>
|
|
|
|
</html>"""
|
|
|
|
_styles = """
|
|
table.diff {font-family:Courier; border:medium;}
|
|
.diff_header {background-color:#e0e0e0}
|
|
td.diff_header {text-align:right}
|
|
.diff_next {background-color:#c0c0c0}
|
|
.diff_add {background-color:#aaffaa}
|
|
.diff_chg {background-color:#ffff77}
|
|
.diff_sub {background-color:#ffaaaa}"""
|
|
|
|
_table_template = """
|
|
<table class="diff" id="difflib_chg_%(prefix)s_top"
|
|
cellspacing="0" cellpadding="0" rules="groups" >
|
|
<colgroup></colgroup> <colgroup></colgroup> <colgroup></colgroup>
|
|
<colgroup></colgroup> <colgroup></colgroup> <colgroup></colgroup>
|
|
%(header_row)s
|
|
<tbody>
|
|
%(data_rows)s </tbody>
|
|
</table>"""
|
|
|
|
_legend = """
|
|
<table class="diff" summary="Legends">
|
|
<tr> <th colspan="2"> Legends </th> </tr>
|
|
<tr> <td> <table border="" summary="Colors">
|
|
<tr><th> Colors </th> </tr>
|
|
<tr><td class="diff_add"> Added </td></tr>
|
|
<tr><td class="diff_chg">Changed</td> </tr>
|
|
<tr><td class="diff_sub">Deleted</td> </tr>
|
|
</table></td>
|
|
<td> <table border="" summary="Links">
|
|
<tr><th colspan="2"> Links </th> </tr>
|
|
<tr><td>(f)irst change</td> </tr>
|
|
<tr><td>(n)ext change</td> </tr>
|
|
<tr><td>(t)op</td> </tr>
|
|
</table></td> </tr>
|
|
</table>"""
|
|
|
|
class HtmlDiff(object):
|
|
"""For producing HTML side by side comparison with change highlights.
|
|
|
|
This class can be used to create an HTML table (or a complete HTML file
|
|
containing the table) showing a side by side, line by line comparison
|
|
of text with inter-line and intra-line change highlights. The table can
|
|
be generated in either full or contextual difference mode.
|
|
|
|
The following methods are provided for HTML generation:
|
|
|
|
make_table -- generates HTML for a single side by side table
|
|
make_file -- generates complete HTML file with a single side by side table
|
|
|
|
See tools/scripts/diff.py for an example usage of this class.
|
|
"""
|
|
|
|
_file_template = _file_template
|
|
_styles = _styles
|
|
_table_template = _table_template
|
|
_legend = _legend
|
|
_default_prefix = 0
|
|
|
|
def __init__(self,tabsize=8,wrapcolumn=None,linejunk=None,
|
|
charjunk=IS_CHARACTER_JUNK):
|
|
"""HtmlDiff instance initializer
|
|
|
|
Arguments:
|
|
tabsize -- tab stop spacing, defaults to 8.
|
|
wrapcolumn -- column number where lines are broken and wrapped,
|
|
defaults to None where lines are not wrapped.
|
|
linejunk,charjunk -- keyword arguments passed into ndiff() (used to by
|
|
HtmlDiff() to generate the side by side HTML differences). See
|
|
ndiff() documentation for argument default values and descriptions.
|
|
"""
|
|
self._tabsize = tabsize
|
|
self._wrapcolumn = wrapcolumn
|
|
self._linejunk = linejunk
|
|
self._charjunk = charjunk
|
|
|
|
def make_file(self,fromlines,tolines,fromdesc='',todesc='',context=False,
|
|
numlines=5):
|
|
"""Returns HTML file of side by side comparison with change highlights
|
|
|
|
Arguments:
|
|
fromlines -- list of "from" lines
|
|
tolines -- list of "to" lines
|
|
fromdesc -- "from" file column header string
|
|
todesc -- "to" file column header string
|
|
context -- set to True for contextual differences (defaults to False
|
|
which shows full differences).
|
|
numlines -- number of context lines. When context is set True,
|
|
controls number of lines displayed before and after the change.
|
|
When context is False, controls the number of lines to place
|
|
the "next" link anchors before the next change (so click of
|
|
"next" link jumps to just before the change).
|
|
"""
|
|
|
|
return self._file_template % dict(
|
|
styles = self._styles,
|
|
legend = self._legend,
|
|
table = self.make_table(fromlines,tolines,fromdesc,todesc,
|
|
context=context,numlines=numlines))
|
|
|
|
def _tab_newline_replace(self,fromlines,tolines):
|
|
"""Returns from/to line lists with tabs expanded and newlines removed.
|
|
|
|
Instead of tab characters being replaced by the number of spaces
|
|
needed to fill in to the next tab stop, this function will fill
|
|
the space with tab characters. This is done so that the difference
|
|
algorithms can identify changes in a file when tabs are replaced by
|
|
spaces and vice versa. At the end of the HTML generation, the tab
|
|
characters will be replaced with a nonbreakable space.
|
|
"""
|
|
def expand_tabs(line):
|
|
# hide real spaces
|
|
line = line.replace(' ','\0')
|
|
# expand tabs into spaces
|
|
line = line.expandtabs(self._tabsize)
|
|
# relace spaces from expanded tabs back into tab characters
|
|
# (we'll replace them with markup after we do differencing)
|
|
line = line.replace(' ','\t')
|
|
return line.replace('\0',' ').rstrip('\n')
|
|
fromlines = [expand_tabs(line) for line in fromlines]
|
|
tolines = [expand_tabs(line) for line in tolines]
|
|
return fromlines,tolines
|
|
|
|
def _split_line(self,data_list,line_num,text):
|
|
"""Builds list of text lines by splitting text lines at wrap point
|
|
|
|
This function will determine if the input text line needs to be
|
|
wrapped (split) into separate lines. If so, the first wrap point
|
|
will be determined and the first line appended to the output
|
|
text line list. This function is used recursively to handle
|
|
the second part of the split line to further split it.
|
|
"""
|
|
# if blank line or context separator, just add it to the output list
|
|
if not line_num:
|
|
data_list.append((line_num,text))
|
|
return
|
|
|
|
# if line text doesn't need wrapping, just add it to the output list
|
|
size = len(text)
|
|
max = self._wrapcolumn
|
|
if (size <= max) or ((size -(text.count('\0')*3)) <= max):
|
|
data_list.append((line_num,text))
|
|
return
|
|
|
|
# scan text looking for the wrap point, keeping track if the wrap
|
|
# point is inside markers
|
|
i = 0
|
|
n = 0
|
|
mark = ''
|
|
while n < max and i < size:
|
|
if text[i] == '\0':
|
|
i += 1
|
|
mark = text[i]
|
|
i += 1
|
|
elif text[i] == '\1':
|
|
i += 1
|
|
mark = ''
|
|
else:
|
|
i += 1
|
|
n += 1
|
|
|
|
# wrap point is inside text, break it up into separate lines
|
|
line1 = text[:i]
|
|
line2 = text[i:]
|
|
|
|
# if wrap point is inside markers, place end marker at end of first
|
|
# line and start marker at beginning of second line because each
|
|
# line will have its own table tag markup around it.
|
|
if mark:
|
|
line1 = line1 + '\1'
|
|
line2 = '\0' + mark + line2
|
|
|
|
# tack on first line onto the output list
|
|
data_list.append((line_num,line1))
|
|
|
|
# use this routine again to wrap the remaining text
|
|
self._split_line(data_list,'>',line2)
|
|
|
|
def _line_wrapper(self,diffs):
|
|
"""Returns iterator that splits (wraps) mdiff text lines"""
|
|
|
|
# pull from/to data and flags from mdiff iterator
|
|
for fromdata,todata,flag in diffs:
|
|
# check for context separators and pass them through
|
|
if flag is None:
|
|
yield fromdata,todata,flag
|
|
continue
|
|
(fromline,fromtext),(toline,totext) = fromdata,todata
|
|
# for each from/to line split it at the wrap column to form
|
|
# list of text lines.
|
|
fromlist,tolist = [],[]
|
|
self._split_line(fromlist,fromline,fromtext)
|
|
self._split_line(tolist,toline,totext)
|
|
# yield from/to line in pairs inserting blank lines as
|
|
# necessary when one side has more wrapped lines
|
|
while fromlist or tolist:
|
|
if fromlist:
|
|
fromdata = fromlist.pop(0)
|
|
else:
|
|
fromdata = ('',' ')
|
|
if tolist:
|
|
todata = tolist.pop(0)
|
|
else:
|
|
todata = ('',' ')
|
|
yield fromdata,todata,flag
|
|
|
|
def _collect_lines(self,diffs):
|
|
"""Collects mdiff output into separate lists
|
|
|
|
Before storing the mdiff from/to data into a list, it is converted
|
|
into a single line of text with HTML markup.
|
|
"""
|
|
|
|
fromlist,tolist,flaglist = [],[],[]
|
|
# pull from/to data and flags from mdiff style iterator
|
|
for fromdata,todata,flag in diffs:
|
|
try:
|
|
# store HTML markup of the lines into the lists
|
|
fromlist.append(self._format_line(0,flag,*fromdata))
|
|
tolist.append(self._format_line(1,flag,*todata))
|
|
except TypeError:
|
|
# exceptions occur for lines where context separators go
|
|
fromlist.append(None)
|
|
tolist.append(None)
|
|
flaglist.append(flag)
|
|
return fromlist,tolist,flaglist
|
|
|
|
def _format_line(self,side,flag,linenum,text):
|
|
"""Returns HTML markup of "from" / "to" text lines
|
|
|
|
side -- 0 or 1 indicating "from" or "to" text
|
|
flag -- indicates if difference on line
|
|
linenum -- line number (used for line number column)
|
|
text -- line text to be marked up
|
|
"""
|
|
try:
|
|
linenum = '%d' % linenum
|
|
id = ' id="%s%s"' % (self._prefix[side],linenum)
|
|
except TypeError:
|
|
# handle blank lines where linenum is '>' or ''
|
|
id = ''
|
|
# replace those things that would get confused with HTML symbols
|
|
text=text.replace("&","&").replace(">",">").replace("<","<")
|
|
|
|
# make space non-breakable so they don't get compressed or line wrapped
|
|
text = text.replace(' ',' ').rstrip()
|
|
|
|
return '<td class="diff_header"%s>%s</td><td nowrap="nowrap">%s</td>' \
|
|
% (id,linenum,text)
|
|
|
|
def _make_prefix(self):
|
|
"""Create unique anchor prefixes"""
|
|
|
|
# Generate a unique anchor prefix so multiple tables
|
|
# can exist on the same HTML page without conflicts.
|
|
fromprefix = "from%d_" % HtmlDiff._default_prefix
|
|
toprefix = "to%d_" % HtmlDiff._default_prefix
|
|
HtmlDiff._default_prefix += 1
|
|
# store prefixes so line format method has access
|
|
self._prefix = [fromprefix,toprefix]
|
|
|
|
def _convert_flags(self,fromlist,tolist,flaglist,context,numlines):
|
|
"""Makes list of "next" links"""
|
|
|
|
# all anchor names will be generated using the unique "to" prefix
|
|
toprefix = self._prefix[1]
|
|
|
|
# process change flags, generating middle column of next anchors/links
|
|
next_id = ['']*len(flaglist)
|
|
next_href = ['']*len(flaglist)
|
|
num_chg, in_change = 0, False
|
|
last = 0
|
|
for i,flag in enumerate(flaglist):
|
|
if flag:
|
|
if not in_change:
|
|
in_change = True
|
|
last = i
|
|
# at the beginning of a change, drop an anchor a few lines
|
|
# (the context lines) before the change for the previous
|
|
# link
|
|
i = max([0,i-numlines])
|
|
next_id[i] = ' id="difflib_chg_%s_%d"' % (toprefix,num_chg)
|
|
# at the beginning of a change, drop a link to the next
|
|
# change
|
|
num_chg += 1
|
|
next_href[last] = '<a href="#difflib_chg_%s_%d">n</a>' % (
|
|
toprefix,num_chg)
|
|
else:
|
|
in_change = False
|
|
# check for cases where there is no content to avoid exceptions
|
|
if not flaglist:
|
|
flaglist = [False]
|
|
next_id = ['']
|
|
next_href = ['']
|
|
last = 0
|
|
if context:
|
|
fromlist = ['<td></td><td> No Differences Found </td>']
|
|
tolist = fromlist
|
|
else:
|
|
fromlist = tolist = ['<td></td><td> Empty File </td>']
|
|
# if not a change on first line, drop a link
|
|
if not flaglist[0]:
|
|
next_href[0] = '<a href="#difflib_chg_%s_0">f</a>' % toprefix
|
|
# redo the last link to link to the top
|
|
next_href[last] = '<a href="#difflib_chg_%s_top">t</a>' % (toprefix)
|
|
|
|
return fromlist,tolist,flaglist,next_href,next_id
|
|
|
|
def make_table(self,fromlines,tolines,fromdesc='',todesc='',context=False,
|
|
numlines=5):
|
|
"""Returns HTML table of side by side comparison with change highlights
|
|
|
|
Arguments:
|
|
fromlines -- list of "from" lines
|
|
tolines -- list of "to" lines
|
|
fromdesc -- "from" file column header string
|
|
todesc -- "to" file column header string
|
|
context -- set to True for contextual differences (defaults to False
|
|
which shows full differences).
|
|
numlines -- number of context lines. When context is set True,
|
|
controls number of lines displayed before and after the change.
|
|
When context is False, controls the number of lines to place
|
|
the "next" link anchors before the next change (so click of
|
|
"next" link jumps to just before the change).
|
|
"""
|
|
|
|
# make unique anchor prefixes so that multiple tables may exist
|
|
# on the same page without conflict.
|
|
self._make_prefix()
|
|
|
|
# change tabs to spaces before it gets more difficult after we insert
|
|
# markkup
|
|
fromlines,tolines = self._tab_newline_replace(fromlines,tolines)
|
|
|
|
# create diffs iterator which generates side by side from/to data
|
|
if context:
|
|
context_lines = numlines
|
|
else:
|
|
context_lines = None
|
|
diffs = _mdiff(fromlines,tolines,context_lines,linejunk=self._linejunk,
|
|
charjunk=self._charjunk)
|
|
|
|
# set up iterator to wrap lines that exceed desired width
|
|
if self._wrapcolumn:
|
|
diffs = self._line_wrapper(diffs)
|
|
|
|
# collect up from/to lines and flags into lists (also format the lines)
|
|
fromlist,tolist,flaglist = self._collect_lines(diffs)
|
|
|
|
# process change flags, generating middle column of next anchors/links
|
|
fromlist,tolist,flaglist,next_href,next_id = self._convert_flags(
|
|
fromlist,tolist,flaglist,context,numlines)
|
|
|
|
s = []
|
|
fmt = ' <tr><td class="diff_next"%s>%s</td>%s' + \
|
|
'<td class="diff_next">%s</td>%s</tr>\n'
|
|
for i in range(len(flaglist)):
|
|
if flaglist[i] is None:
|
|
# mdiff yields None on separator lines skip the bogus ones
|
|
# generated for the first line
|
|
if i > 0:
|
|
s.append(' </tbody> \n <tbody>\n')
|
|
else:
|
|
s.append( fmt % (next_id[i],next_href[i],fromlist[i],
|
|
next_href[i],tolist[i]))
|
|
if fromdesc or todesc:
|
|
header_row = '<thead><tr>%s%s%s%s</tr></thead>' % (
|
|
'<th class="diff_next"><br /></th>',
|
|
'<th colspan="2" class="diff_header">%s</th>' % fromdesc,
|
|
'<th class="diff_next"><br /></th>',
|
|
'<th colspan="2" class="diff_header">%s</th>' % todesc)
|
|
else:
|
|
header_row = ''
|
|
|
|
table = self._table_template % dict(
|
|
data_rows=''.join(s),
|
|
header_row=header_row,
|
|
prefix=self._prefix[1])
|
|
|
|
return table.replace('\0+','<span class="diff_add">'). \
|
|
replace('\0-','<span class="diff_sub">'). \
|
|
replace('\0^','<span class="diff_chg">'). \
|
|
replace('\1','</span>'). \
|
|
replace('\t',' ')
|
|
|
|
del re
|
|
|
|
def restore(delta, which):
|
|
r"""
|
|
Generate one of the two sequences that generated a delta.
|
|
|
|
Given a `delta` produced by `Differ.compare()` or `ndiff()`, extract
|
|
lines originating from file 1 or 2 (parameter `which`), stripping off line
|
|
prefixes.
|
|
|
|
Examples:
|
|
|
|
>>> diff = ndiff('one\ntwo\nthree\n'.splitlines(1),
|
|
... 'ore\ntree\nemu\n'.splitlines(1))
|
|
>>> diff = list(diff)
|
|
>>> print(''.join(restore(diff, 1)), end="")
|
|
one
|
|
two
|
|
three
|
|
>>> print(''.join(restore(diff, 2)), end="")
|
|
ore
|
|
tree
|
|
emu
|
|
"""
|
|
try:
|
|
tag = {1: "- ", 2: "+ "}[int(which)]
|
|
except KeyError:
|
|
raise ValueError('unknown delta choice (must be 1 or 2): %r'
|
|
% which)
|
|
prefixes = (" ", tag)
|
|
for line in delta:
|
|
if line[:2] in prefixes:
|
|
yield line[2:]
|
|
|
|
def _test():
|
|
import doctest, difflib
|
|
return doctest.testmod(difflib)
|
|
|
|
if __name__ == "__main__":
|
|
_test()
|