6.4. difflib — Helpers for computing deltas

This module provides classes and functions for comparing sequences. It can be used for example, for comparing files, and can produce difference information in various formats, including HTML and context and unified diffs. For comparing directories and files, see also, the filecmp module.

class difflib.SequenceMatcher

This is a flexible class for comparing pairs of sequences of any type, so long as the sequence elements are hashable. The basic algorithm predates, and is a little fancier than, an algorithm published in the late 1980’s by Ratcliff and Obershelp under the hyperbolic name “gestalt pattern matching.” The idea is to find the longest contiguous matching subsequence that contains no “junk” elements (the Ratcliff and Obershelp algorithm doesn’t address junk). The same idea is then applied recursively to the pieces of the sequences to the left and to the right of the matching subsequence. This does not yield minimal edit sequences, but does tend to yield matches that “look right” to people.

Timing: The basic Ratcliff-Obershelp algorithm is cubic time in the worst case and quadratic time in the expected case. SequenceMatcher is quadratic time for the worst case and has expected-case behavior dependent in a complicated way on how many elements the sequences have in common; best case time is linear.

Automatic junk heuristic: SequenceMatcher supports a heuristic that automatically treats certain sequence items as junk. The heuristic counts how many times each individual item appears in the sequence. If an item’s duplicates (after the first one) account for more than 1% of the sequence and the sequence is at least 200 items long, this item is marked as “popular” and is treated as junk for the purpose of sequence matching. This heuristic can be turned off by setting the autojunk argument to False when creating the SequenceMatcher.

New in version 3.2: The autojunk parameter.

class difflib.Differ

This 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:

Code	Meaning
'- '	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.

class difflib.HtmlDiff

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 constructor for this class is:

__init__(tabsize=8, wrapcolumn=None, linejunk=None, charjunk=IS_CHARACTER_JUNK)

Initializes instance of HtmlDiff.

tabsize is an optional keyword argument to specify tab stop spacing and defaults to 8.

wrapcolumn is an optional keyword to specify column number where lines are broken and wrapped, defaults to None where lines are not wrapped.

linejunk and charjunk are optional keyword arguments passed into ndiff() (used by HtmlDiff to generate the side by side HTML differences). See ndiff() documentation for argument default values and descriptions.

The following methods are public:

make_file(fromlines, tolines, fromdesc='', todesc='', context=False, numlines=5)

Compares fromlines and tolines (lists of strings) and returns a string which is a complete HTML file containing a table showing line by line differences with inter-line and intra-line changes highlighted.

fromdesc and todesc are optional keyword arguments to specify from/to file column header strings (both default to an empty string).

context and numlines are both optional keyword arguments. Set context to True when contextual differences are to be shown, else the default is False to show the full files. numlines defaults to 5. When context is True numlines controls the number of context lines which surround the difference highlights. When context is False numlines controls the number of lines which are shown before a difference highlight when using the “next” hyperlinks (setting to zero would cause the “next” hyperlinks to place the next difference highlight at the top of the browser without any leading context).

make_table(fromlines, tolines, fromdesc='', todesc='', context=False, numlines=5)

Compares fromlines and tolines (lists of strings) and returns a string which is a complete HTML table showing line by line differences with inter-line and intra-line changes highlighted.

The arguments for this method are the same as those for the make_file() method.

Tools/scripts/diff.py is a command-line front-end to this class and contains a good example of its use.

difflib.context_diff(a, b, fromfile='', tofile='', fromfiledate='', tofiledate='', n=3, lineterm='\n')

Compare a and b (lists of strings); return a delta (a generator generating the delta lines) in context diff format.

Context diffs are a compact way of showing just the lines that have changed plus a few lines of context. The changes are shown in a before/after style. 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 use with 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.

>>> s1 = ['bacon\n', 'eggs\n', 'ham\n', 'guido\n']
>>> s2 = ['python\n', 'eggy\n', 'hamster\n', 'guido\n']
>>> for line in context_diff(s1, s2, fromfile='before.py', tofile='after.py'):
...     sys.stdout.write(line)  
*** before.py
--- after.py
***************
*** 1,4 ****
! bacon
! eggs
! ham
  guido
--- 1,4 ----
! python
! eggy
! hamster
  guido

See A command-line interface to difflib for a more detailed example.

difflib.get_close_matches(word, possibilities, n=3, cutoff=0.6)

Return a list of the best “good enough” matches. word is a sequence for which close matches are desired (typically a string), and possibilities is a list of sequences against which to match word (typically a list of strings).

Optional argument n (default 3) is the maximum number of close matches to return; n must be greater than 0.

Optional argument cutoff (default 0.6) is a float in the range [0, 1]. Possibilities that don’t score at least that similar to word are ignored.

The best (no more than n) matches among the possibilities are returned in a list, sorted by similarity score, most similar first.

>>> get_close_matches('appel', ['ape', 'apple', 'peach', 'puppy'])
['apple', 'ape']
>>> import keyword
>>> get_close_matches('wheel', keyword.kwlist)
['while']
>>> get_close_matches('apple', keyword.kwlist)
[]
>>> get_close_matches('accept', keyword.kwlist)
['except']

difflib.ndiff(a, b, linejunk=None, charjunk=IS_CHARACTER_JUNK)

Compare a and b (lists of strings); return a Differ-style delta (a generator generating the delta lines).

Optional keyword parameters linejunk and charjunk are for filter functions (or None):

linejunk: A function that accepts a single string argument, and returns true if the string is junk, or false if not. The default is None. There is also a module-level function IS_LINE_JUNK(), which filters out lines without visible characters, except for at most one pound character ('#') – however the underlying SequenceMatcher class does a dynamic analysis of which lines are so frequent as to constitute noise, and this usually works better than using this function.

charjunk: A function that accepts a character (a string of length 1), and returns if the character is junk, or false if not. 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.

>>> diff = ndiff('one\ntwo\nthree\n'.splitlines(1),
...              'ore\ntree\nemu\n'.splitlines(1))
>>> print(''.join(diff), end="")
- one
?  ^
+ ore
?  ^
- two
- three
?  -
+ tree
+ emu

difflib.restore(sequence, which)

Return one of the two sequences that generated a delta.

Given a sequence produced by Differ.compare() or ndiff(), extract lines originating from file 1 or 2 (parameter which), stripping off line prefixes.

Example:

>>> diff = ndiff('one\ntwo\nthree\n'.splitlines(1),
...              'ore\ntree\nemu\n'.splitlines(1))
>>> diff = list(diff) # materialize the generated delta into a list
>>> print(''.join(restore(diff, 1)), end="")
one
two
three
>>> print(''.join(restore(diff, 2)), end="")
ore
tree
emu

difflib.unified_diff(a, b, fromfile='', tofile='', fromfiledate='', tofiledate='', n=3, lineterm='\n')

Compare a and b (lists of strings); return a delta (a generator generating the delta lines) in unified diff format.

Unified diffs are a compact way of showing just the lines that have changed plus a few lines of context. The changes are shown in a inline style (instead of separate before/after blocks). 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 use with 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.

>>> s1 = ['bacon\n', 'eggs\n', 'ham\n', 'guido\n']
>>> s2 = ['python\n', 'eggy\n', 'hamster\n', 'guido\n']
>>> for line in unified_diff(s1, s2, fromfile='before.py', tofile='after.py'):
...     sys.stdout.write(line)   
--- before.py
+++ after.py
@@ -1,4 +1,4 @@
-bacon
-eggs
-ham
+python
+eggy
+hamster
 guido

See A command-line interface to difflib for a more detailed example.

difflib.IS_LINE_JUNK(line)

Return true for ignorable lines. The line line is ignorable if line is blank or contains a single '#', otherwise it is not ignorable. Used as a default for parameter linejunk in ndiff() in older versions.

difflib.IS_CHARACTER_JUNK(ch)

Return true for ignorable characters. The character ch is ignorable if ch is a space or tab, otherwise it is not ignorable. Used as a default for parameter charjunk in ndiff().

>>> s = SequenceMatcher(None, "abcd", "bcde")
>>> s.ratio()
0.75
>>> s.quick_ratio()
0.75
>>> s.real_quick_ratio()
1.0

>>> s = SequenceMatcher(lambda x: x == " ",
...                     "private Thread currentThread;",
...                     "private volatile Thread currentThread;")

>>> print(round(s.ratio(), 3))
0.866

>>> for block in s.get_matching_blocks():
...     print("a[%d] and b[%d] match for %d elements" % block)
a[0] and b[0] match for 8 elements
a[8] and b[17] match for 21 elements
a[29] and b[38] match for 0 elements

>>> for opcode in s.get_opcodes():
...     print("%6s a[%d:%d] b[%d:%d]" % opcode)
 equal a[0:8] b[0:8]
insert a[8:8] b[8:17]
 equal a[8:29] b[17:38]

>>> 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)

>>> d = Differ()

>>> result = list(d.compare(text1, text2))

>>> from pprint import 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']

>>> import sys
>>> sys.stdout.writelines(result)
    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.

""" Command line interface to difflib.py providing diffs in four formats:

* ndiff:    lists every line and highlights interline changes.
* context:  highlights clusters of changes in a before/after format.
* unified:  highlights clusters of changes in an inline format.
* html:     generates side by side comparison with change highlights.

"""

import sys, os, time, difflib, optparse

def main():
     # Configure the option parser
    usage = "usage: %prog [options] fromfile tofile"
    parser = optparse.OptionParser(usage)
    parser.add_option("-c", action="store_true", default=False,
                      help='Produce a context format diff (default)')
    parser.add_option("-u", action="store_true", default=False,
                      help='Produce a unified format diff')
    hlp = 'Produce HTML side by side diff (can use -c and -l in conjunction)'
    parser.add_option("-m", action="store_true", default=False, help=hlp)
    parser.add_option("-n", action="store_true", default=False,
                      help='Produce a ndiff format diff')
    parser.add_option("-l", "--lines", type="int", default=3,
                      help='Set number of context lines (default 3)')
    (options, args) = parser.parse_args()

    if len(args) == 0:
        parser.print_help()
        sys.exit(1)
    if len(args) != 2:
        parser.error("need to specify both a fromfile and tofile")

    n = options.lines
    fromfile, tofile = args # as specified in the usage string

    # we're passing these as arguments to the diff function
    fromdate = time.ctime(os.stat(fromfile).st_mtime)
    todate = time.ctime(os.stat(tofile).st_mtime)
    fromlines = open(fromfile, 'U').readlines()
    tolines = open(tofile, 'U').readlines()

    if options.u:
        diff = difflib.unified_diff(fromlines, tolines, fromfile, tofile,
                                    fromdate, todate, n=n)
    elif options.n:
        diff = difflib.ndiff(fromlines, tolines)
    elif options.m:
        diff = difflib.HtmlDiff().make_file(fromlines, tolines, fromfile,
                                            tofile, context=options.c,
                                            numlines=n)
    else:
        diff = difflib.context_diff(fromlines, tolines, fromfile, tofile,
                                    fromdate, todate, n=n)

    # we're using writelines because diff is a generator
    sys.stdout.writelines(diff)

if __name__ == '__main__':
    main()