Junk heuristic¶

difflib uses a junk heuristic: some items are deemed to be junk, and ignored when searching for similarities. Ideally, these are uninteresting or common items, such as blank lines or whitespace.

This heuristic can speed the algorithm up (because it reduces the number of possible combinations) and it can produce results that are more understandable for humans (typically breaking on whitespace). But it can also cause pathological cases:

• Inappropriately chosen junk items can cause an unexpectedly large (but still correct) result.

• The default heuristic is asymmetric: only the second sequence is inspected when determining what is considered junk, so comparing A to B can give different results than comparing B to A and reversing the result.

By default, if the second input sequence is at least 200 items long, items that account for more than 1% it are considered junk.

Depending on your data, you should consider turning this heuristic off (setting SequenceMatcher’s autojunk argument to False) or tuning it (using the isjunk argument, perhaps to one of the predefined functions).

The difflib algorithm¶

The algorithm used in SequenceMatcher predates, and is a little fancier than, an algorithm published in the late 1980s by Ratcliff and Obershelp under the hyperbolic name “gestalt pattern matching.” The idea is to find the longest contiguous subsequence common to both inputs, then recursively handle the pieces of the sequences to the left and to the right of the matching subsequence.

As an extension to the Ratcliff and Obershelp algorithm, difflib searches for the longest junk-free contiguous subsequence. See the Junk heuristic section for details.

Diff generation¶

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 whitespace characters, such as spaces, tabs or line breaks.

Note that Differ-generated deltas make no claim to be minimal diffs. To the contrary, minimal diffs are often counter-intuitive for humans, because they synch up anywhere possible, sometimes at 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.

The Differ class has this constructor:

__init__(linejunk=None, charjunk=None, autojunk=True)¶

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. The default is None, meaning that no line is considered junk.

charjunk: A function that accepts a single character argument (a string of length 1), and returns true if the character is junk. The default is None, meaning that no character is considered junk.

These junk-filtering functions speed up matching to find differences and do not cause any differing lines or characters to be ignored. Read the description of the find_longest_match() method’s isjunk parameter for an explanation.

Setting the optional autojunk argument to False will turn automatic junk heuristic off.

Changed in version 3.16: Added keyword-only autojunk parameter.

Differ objects are used (deltas generated) via a single method:

compare(a, b)¶

Compare two sequences of lines, and generate the delta (a sequence of lines).

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 generated delta also consists of newline-terminated strings, ready to be printed as-is via the writelines() method of a file-like object.

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.

Warning

The trailing newlines get stripped before the diff, so the result can be incomplete. See gh-71896 for details.

The constructor for this class is:

__init__(tabsize=8, wrapcolumn=None, linejunk=None, charjunk=IS_CHARACTER_JUNK, *, autojunk=True)¶

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.

Setting the optional autojunk argument to False will turn automatic junk heuristic off.

Changed in version 3.16: Added keyword-only autojunk parameter.

The following methods are public:

make_file(fromlines, tolines, fromdesc='', todesc='', context=False, numlines=5, *, charset='utf-8')¶

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).

Note

fromdesc and todesc are interpreted as unescaped HTML and should be properly escaped while receiving input from untrusted sources.

Changed in version 3.5: charset keyword-only argument was added. The default charset of HTML document changed from 'ISO-8859-1' to 'utf-8'.

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.

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

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 io.IOBase.readlines() result in diffs that are suitable for use with io.IOBase.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.

>>> import sys
>>> from difflib import *
>>> s1 = ['bacon\n', 'eggs\n', 'ham\n', 'guido\n']
>>> s2 = ['python\n', 'eggy\n', 'hamster\n', 'guido\n']
>>> sys.stdout.writelines(context_diff(s1, s2, fromfile='before.py',
...                        tofile='after.py'))
*** 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.

Setting the optional autojunk argument to False will turn automatic junk heuristic off.

Changed in version 3.16: Added keyword-only autojunk parameter.

difflib.get_close_matches(word, possibilities, n=3, cutoff=0.6, *, autojunk=True)¶

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.

Setting the optional autojunk argument to False will turn automatic junk heuristic off.

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('pineapple', keyword.kwlist)
[]
>>> get_close_matches('accept', keyword.kwlist)
['except']

Changed in version 3.16: Added keyword-only autojunk parameter.

difflib.ndiff(a, b, linejunk=None, charjunk=IS_CHARACTER_JUNK, *, autojunk=True)¶

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 filtering 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 hash 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; it’s a bad idea to include newline in this!).

Setting the optional autojunk argument to False will turn automatic junk heuristic off.

Example:

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

Changed in version 3.16: Added keyword-only autojunk parameter.

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(keepends=True),
...              'ore\ntree\nemu\n'.splitlines(keepends=True))
>>> 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', *, autojunk=True, color=False)¶

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 an 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 io.IOBase.readlines() result in diffs that are suitable for use with io.IOBase.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.

Set color to True to enable output in color, similar to git diff --color. Even if enabled, it can be controlled using environment variables.

The unified 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']
>>> sys.stdout.writelines(unified_diff(s1, s2, fromfile='before.py', tofile='after.py'))
--- 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.

Changed in version 3.15: Added the color parameter.

Setting the optional autojunk argument to False will turn automatic junk heuristic off.

Changed in version 3.16: Added keyword-only autojunk parameter.

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

Compare a and b (lists of bytes objects) using dfunc; yield a sequence of delta lines (also bytes) in the format returned by dfunc. dfunc must be a callable, typically either unified_diff() or context_diff().

Allows you to compare data with unknown or inconsistent encoding. All inputs except n must be bytes objects, not str. Works by losslessly converting all inputs (except n) to str, and calling dfunc(a, b, fromfile, tofile, fromfiledate, tofiledate, n, lineterm). The output of dfunc is then converted back to bytes, so the delta lines that you receive have the same unknown/inconsistent encodings as a and b.

Added in version 3.5.

Junk definition functions¶

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().

SequenceMatcher objects¶

class difflib.SequenceMatcher(isjunk=None, a='', b='', autojunk=True)¶

Optional argument isjunk must be None (the default) or a one-argument function that takes a sequence element and returns true if and only if the element is “junk” and should be ignored. Passing None for isjunk is equivalent to passing lambda x: False; in other words, no elements are ignored. For example, pass:

lambda x: x in " \t"

if you’re comparing lines as sequences of characters, and don’t want to synch up on blanks or hard tabs.

The optional arguments a and b are sequences to be compared; both default to empty strings. The elements of both sequences must be hashable.

The optional argument autojunk can be used to disable the automatic junk heuristic.

Changed in version 3.2: Added the autojunk parameter.

SequenceMatcher objects get three data attributes: bjunk is the set of elements of b for which isjunk is True; bpopular is the set of non-junk elements considered popular by the heuristic (if it is not disabled); b2j is a dict mapping the remaining elements of b to a list of positions where they occur. All three are reset whenever b is reset with set_seqs() or set_seq2().

Added in version 3.2: The bjunk and bpopular attributes.

SequenceMatcher objects have the following methods:

set_seqs(a, b)¶

Set the two sequences to be compared.

SequenceMatcher computes and caches detailed information about the second sequence, so if you want to compare one sequence against many sequences, use set_seq2() to set the commonly used sequence once and call set_seq1() repeatedly, once for each of the other sequences.

set_seq1(a)¶

Set the first sequence to be compared. The second sequence to be compared is not changed.

set_seq2(b)¶

Set the second sequence to be compared. The first sequence to be compared is not changed.

find_longest_match(alo=0, ahi=None, blo=0, bhi=None)¶

Find longest matching block in a[alo:ahi] and b[blo:bhi].

If isjunk was omitted or None, find_longest_match() returns (i, j, k) such that a[i:i+k] is equal to b[j:j+k], where alo <= i <= i+k <= ahi and blo <= j <= j+k <= bhi. For all (i', j', k') meeting those conditions, the additional conditions k >= k', i <= i', and if i == i', j <= j' are also met. In other words, of all maximal matching blocks, return one that starts earliest in a, and of all those maximal matching blocks that start earliest in a, return the one that starts earliest in b.

>>> s = SequenceMatcher(None, " abcd", "abcd abcd")
>>> s.find_longest_match(0, 5, 0, 9)
Match(a=0, b=4, size=5)

If isjunk was provided, first the longest matching block is determined as above, but with the additional restriction that no junk element appears in the block. Then that block is extended as far as possible by matching (only) junk elements on both sides. So the resulting block never matches on junk except as identical junk happens to be adjacent to an interesting match.

Here’s the same example as before, but considering blanks to be junk. That prevents ' abcd' from matching the ' abcd' at the tail end of the second sequence directly. Instead only the 'abcd' can match, and matches the leftmost 'abcd' in the second sequence:

>>> s = SequenceMatcher(lambda x: x==" ", " abcd", "abcd abcd")
>>> s.find_longest_match(0, 5, 0, 9)
Match(a=1, b=0, size=4)

If no blocks match, this returns (alo, blo, 0).

This method returns a named tuple Match(a, b, size).

Changed in version 3.9: Added default arguments.

get_matching_blocks()¶

Return list of triples describing non-overlapping matching subsequences. Each triple is of the form (i, j, n), and means that a[i:i+n] == b[j:j+n]. The triples are monotonically increasing in i and j.

The last triple is a dummy, and has the value (len(a), len(b), 0). It is the only triple with n == 0. If (i, j, n) and (i', j', n') are adjacent triples in the list, and the second is not the last triple in the list, then i+n < i' or j+n < j'; in other words, adjacent triples always describe non-adjacent equal blocks.

>>> s = SequenceMatcher(None, "abxcd", "abcd")
>>> 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)]

get_opcodes()¶

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 equal to the i2 from the preceding tuple, and, likewise, j1 equal to the previous j2.

The tag values are strings, with these meanings:

Value	Meaning
'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] (the sub-sequences are equal).

For example:

>>> a = "qabxcd"
>>> b = "abycdf"
>>> s = SequenceMatcher(None, a, b)
>>> for tag, i1, i2, j1, j2 in s.get_opcodes():
...     print('{:7}   a[{}:{}] --> b[{}:{}] {!r:>8} --> {!r}'.format(
...         tag, i1, i2, j1, j2, a[i1:i2], b[j1:j2]))
delete    a[0:1] --> b[0:0]      'q' --> ''
equal     a[1:3] --> b[0:2]     'ab' --> 'ab'
replace   a[3:4] --> b[2:3]      'x' --> 'y'
equal     a[4:6] --> b[3:5]     'cd' --> 'cd'
insert    a[6:6] --> b[5:6]       '' --> 'f'

get_grouped_opcodes(n=3)¶

Return a generator of groups with up to n lines of context.

Starting with the groups returned by get_opcodes(), this method splits out smaller change clusters and eliminates intervening ranges which have no changes.

The groups are returned in the same format as get_opcodes().

ratio()¶

Return a measure of the sequences’ similarity as a float in the range [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 1.0 if the sequences are identical, and 0.0 if they have nothing in common.

This is expensive to compute if get_matching_blocks() or get_opcodes() hasn’t already been called, in which case you may want to try quick_ratio() or real_quick_ratio() first to get an upper bound.

quick_ratio()¶

Return an upper bound on ratio() relatively quickly.

real_quick_ratio()¶

Return an upper bound on ratio() very quickly.

The three methods that return the ratio of matching to total characters can give different results due to differing levels of approximation, although quick_ratio() and real_quick_ratio() are always at least as large as ratio():

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

Examples¶

>>> 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(keepends=True)
>>> 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(keepends=True)

>>> 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, difflib, argparse
import datetime as dt

def file_mtime(path):
    t = dt.datetime.fromtimestamp(os.stat(path).st_mtime,
                                  dt.timezone.utc)
    return t.astimezone().isoformat()

def main():

    parser = argparse.ArgumentParser()
    parser.add_argument('-c', action='store_true', default=False,
                        help='Produce a context format diff (default)')
    parser.add_argument('-u', action='store_true', default=False,
                        help='Produce a unified format diff')
    parser.add_argument('-m', action='store_true', default=False,
                        help='Produce HTML side by side diff '
                             '(can use -c and -l in conjunction)')
    parser.add_argument('-n', action='store_true', default=False,
                        help='Produce a ndiff format diff')
    parser.add_argument('-l', '--lines', type=int, default=3,
                        help='Set number of context lines (default 3)')
    parser.add_argument('fromfile')
    parser.add_argument('tofile')
    options = parser.parse_args()

    n = options.lines
    fromfile = options.fromfile
    tofile = options.tofile

    fromdate = file_mtime(fromfile)
    todate = file_mtime(tofile)
    with open(fromfile) as ff:
        fromlines = ff.readlines()
    with open(tofile) as tf:
        tolines = tf.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)

    sys.stdout.writelines(diff)

if __name__ == '__main__':
    main()

"""ndiff [-q] file1 file2
    or
ndiff (-r1 | -r2) < ndiff_output > file1_or_file2

Print a human-friendly file difference report to stdout.  Both inter-
and intra-line differences are noted.  In the second form, recreate file1
(-r1) or file2 (-r2) on stdout, from an ndiff report on stdin.

In the first form, if -q ("quiet") is not specified, the first two lines
of output are

-: file1
+: file2

Each remaining line begins with a two-letter code:

    "- "    line unique to file1
    "+ "    line unique to file2
    "  "    line common to both files
    "? "    line not present in either input file

Lines beginning with "? " attempt to guide the eye to intraline
differences, and were not present in either input file.  These lines can be
confusing if the source files contain tab characters.

The first file can be recovered by retaining only lines that begin with
"  " or "- ", and deleting those 2-character prefixes; use ndiff with -r1.

The second file can be recovered similarly, but by retaining only "  " and
"+ " lines; use ndiff with -r2; or, on Unix, the second file can be
recovered by piping the output through

    sed -n '/^[+ ] /s/^..//p'
"""

__version__ = 1, 7, 0

import difflib, sys

def fail(msg):
    out = sys.stderr.write
    out(msg + "\n\n")
    out(__doc__)
    return 0

# open a file & return the file object; gripe and return 0 if it
# couldn't be opened
def fopen(fname):
    try:
        return open(fname)
    except IOError as detail:
        return fail("couldn't open " + fname + ": " + str(detail))

# open two files & spray the diff to stdout; return false iff a problem
def fcompare(f1name, f2name):
    f1 = fopen(f1name)
    f2 = fopen(f2name)
    if not f1 or not f2:
        return 0

    a = f1.readlines(); f1.close()
    b = f2.readlines(); f2.close()
    for line in difflib.ndiff(a, b):
        print(line, end=' ')

    return 1

# crack args (sys.argv[1:] is normal) & compare;
# return false iff a problem

def main(args):
    import getopt
    try:
        opts, args = getopt.getopt(args, "qr:")
    except getopt.error as detail:
        return fail(str(detail))
    noisy = 1
    qseen = rseen = 0
    for opt, val in opts:
        if opt == "-q":
            qseen = 1
            noisy = 0
        elif opt == "-r":
            rseen = 1
            whichfile = val
    if qseen and rseen:
        return fail("can't specify both -q and -r")
    if rseen:
        if args:
            return fail("no args allowed with -r option")
        if whichfile in ("1", "2"):
            restore(whichfile)
            return 1
        return fail("-r value must be 1 or 2")
    if len(args) != 2:
        return fail("need 2 filename args")
    f1name, f2name = args
    if noisy:
        print('-:', f1name)
        print('+:', f2name)
    return fcompare(f1name, f2name)

# read ndiff output from stdin, and print file1 (which=='1') or
# file2 (which=='2') to stdout

def restore(which):
    restored = difflib.restore(sys.stdin.readlines(), which)
    sys.stdout.writelines(restored)

if __name__ == '__main__':
    main(sys.argv[1:])