Module difflib

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']

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 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

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 format returned by time.ctime().

Example:

>>> for line in unified_diff('one two three four'.split(),
...             'zero one tree four'.split(), 'Original', 'Current',
...             'Sat Jan 26 23:30:50 1991', 'Fri Jun 06 10:20:52 2003',
...             lineterm=''):
...     print line
--- Original Sat Jan 26 23:30:50 1991
+++ Current Fri Jun 06 10:20:52 2003
@@ -1,4 +1,4 @@
+zero
 one
-two
-three
+tree
 four

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 format returned by time.ctime(). 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',
...       'Sat Jan 26 23:30:50 1991', 'Fri Jun 06 10:22:46 2003')),
*** Original Sat Jan 26 23:30:50 1991
--- Current Fri Jun 06 10:22:46 2003
***************
*** 1,4 ****
  one
! two
! three
  four
--- 1,4 ----
+ zero
  one
! tree
  four

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),
- one
?  ^
+ ore
?  ^
- two
- three
?  -
+ tree
+ emu

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)),
one
two
three
>>> print ''.join(restore(diff, 2)),
ore
tree
emu