This file is indexed.

/usr/lib/python2.7/dist-packages/rdflib/compare.py is in python-rdflib 4.1.2-3.

This file is owned by root:root, with mode 0o644.

The actual contents of the file can be viewed below.

  1
  2
  3
  4
  5
  6
  7
  8
  9
 10
 11
 12
 13
 14
 15
 16
 17
 18
 19
 20
 21
 22
 23
 24
 25
 26
 27
 28
 29
 30
 31
 32
 33
 34
 35
 36
 37
 38
 39
 40
 41
 42
 43
 44
 45
 46
 47
 48
 49
 50
 51
 52
 53
 54
 55
 56
 57
 58
 59
 60
 61
 62
 63
 64
 65
 66
 67
 68
 69
 70
 71
 72
 73
 74
 75
 76
 77
 78
 79
 80
 81
 82
 83
 84
 85
 86
 87
 88
 89
 90
 91
 92
 93
 94
 95
 96
 97
 98
 99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
# -*- coding: utf-8 -*-
"""
A collection of utilities for canonicalizing and inspecting graphs.

Among other things, they solve of the problem of deterministic bnode
comparisons.

Warning: the time to canonicalize bnodes may increase exponentially on larger
graphs. Use with care!

Example of comparing two graphs::

    >>> g1 = Graph().parse(format='n3', data='''
    ...     @prefix : <http://example.org/ns#> .
    ...     <http://example.org> :rel
    ...         <http://example.org/same>,
    ...         [ :label "Same" ],
    ...         <http://example.org/a>,
    ...         [ :label "A" ] .
    ... ''')
    >>> g2 = Graph().parse(format='n3', data='''
    ...     @prefix : <http://example.org/ns#> .
    ...     <http://example.org> :rel
    ...         <http://example.org/same>,
    ...         [ :label "Same" ],
    ...         <http://example.org/b>,
    ...         [ :label "B" ] .
    ... ''')
    >>>
    >>> iso1 = to_isomorphic(g1)
    >>> iso2 = to_isomorphic(g2)

These are not isomorphic::

    >>> iso1 == iso2
    False

Diff the two graphs::

    >>> in_both, in_first, in_second = graph_diff(iso1, iso2)

Present in both::

    >>> def dump_nt_sorted(g):
    ...     for l in sorted(g.serialize(format='nt').splitlines()):
    ...         if l: print(l.decode('ascii'))

    >>> dump_nt_sorted(in_both) #doctest: +SKIP
    <http://example.org>
        <http://example.org/ns#rel> <http://example.org/same> .
    <http://example.org>
        <http://example.org/ns#rel> _:cbcaabaaba17fecbc304a64f8edee4335e .
    _:cbcaabaaba17fecbc304a64f8edee4335e
        <http://example.org/ns#label> "Same" .

Only in first::

    >>> dump_nt_sorted(in_first) #doctest: +SKIP
    <http://example.org>
        <http://example.org/ns#rel> <http://example.org/a> .
    <http://example.org>
        <http://example.org/ns#rel> _:cb124e4c6da0579f810c0ffe4eff485bd9 .
    _:cb124e4c6da0579f810c0ffe4eff485bd9
        <http://example.org/ns#label> "A" .

Only in second::

    >>> dump_nt_sorted(in_second) #doctest: +SKIP
    <http://example.org>
        <http://example.org/ns#rel> <http://example.org/b> .
    <http://example.org>
        <http://example.org/ns#rel> _:cb558f30e21ddfc05ca53108348338ade8 .
    _:cb558f30e21ddfc05ca53108348338ade8
        <http://example.org/ns#label> "B" .
"""


# TODO:
# - Doesn't handle quads.
# - Add warning and/or safety mechanism before working on large graphs?
# - use this in existing Graph.isomorphic?

__all__ = ['IsomorphicGraph', 'to_isomorphic', 'isomorphic',
           'to_canonical_graph', 'graph_diff', 'similar']

from rdflib.graph import Graph, ConjunctiveGraph, ReadOnlyGraphAggregate
from rdflib.term import BNode
try:
    import hashlib
    md = hashlib.md5
except ImportError:
    # for Python << 2.5
    import md5
    md = md5.new


class IsomorphicGraph(ConjunctiveGraph):
    """
    Ported from
    <http://www.w3.org/2001/sw/DataAccess/proto-tests/tools/rdfdiff.py>
    (Sean B Palmer's RDF Graph Isomorphism Tester).
    """

    def __init__(self, **kwargs):
        super(IsomorphicGraph, self).__init__(**kwargs)

    def __eq__(self, other):
        """Graph isomorphism testing."""
        if not isinstance(other, IsomorphicGraph):
            return False
        elif len(self) != len(other):
            return False
        elif list(self) == list(other):
            return True  # TODO: really generally cheaper?
        return self.internal_hash() == other.internal_hash()

    def __ne__(self, other):
        """Negative graph isomorphism testing."""
        return not self.__eq__(other)

    def internal_hash(self):
        """
        This is defined instead of __hash__ to avoid a circular recursion
        scenario with the Memory store for rdflib which requires a hash lookup
        in order to return a generator of triples.
        """
        return _TripleCanonicalizer(self).to_hash()


class _TripleCanonicalizer(object):

    def __init__(self, graph, hashfunc=hash):
        self.graph = graph
        self.hashfunc = hashfunc

    def to_hash(self):
        return self.hashfunc(tuple(sorted(
            map(self.hashfunc, self.canonical_triples()))))

    def canonical_triples(self):
        for triple in self.graph:
            yield tuple(self._canonicalize_bnodes(triple))

    def _canonicalize_bnodes(self, triple):
        for term in triple:
            if isinstance(term, BNode):
                yield BNode(value="cb%s" % self._canonicalize(term))
            else:
                yield term

    def _canonicalize(self, term, done=False):
        return self.hashfunc(tuple(sorted(self._vhashtriples(term, done),
                                          key=_hetero_tuple_key)))

    def _vhashtriples(self, term, done):
        for triple in self.graph:
            if term in triple:
                yield tuple(self._vhashtriple(triple, term, done))

    def _vhashtriple(self, triple, target_term, done):
        for i, term in enumerate(triple):
            if not isinstance(term, BNode):
                yield term
            elif done or (term == target_term):
                yield i
            else:
                yield self._canonicalize(term, done=True)


def _hetero_tuple_key(x):
    "Sort like Python 2 - by name of type, then by value. Expects tuples."
    return tuple((type(a).__name__, a) for a in x)


def to_isomorphic(graph):
    if isinstance(graph, IsomorphicGraph):
        return graph
    return IsomorphicGraph(store=graph.store)


def isomorphic(graph1, graph2):
    """
    Compare graph for equality. Uses an algorithm to compute unique hashes
    which takes bnodes into account.

    Examples::

        >>> g1 = Graph().parse(format='n3', data='''
        ...     @prefix : <http://example.org/ns#> .
        ...     <http://example.org> :rel <http://example.org/a> .
        ...     <http://example.org> :rel <http://example.org/b> .
        ...     <http://example.org> :rel [ :label "A bnode." ] .
        ... ''')
        >>> g2 = Graph().parse(format='n3', data='''
        ...     @prefix ns: <http://example.org/ns#> .
        ...     <http://example.org> ns:rel [ ns:label "A bnode." ] .
        ...     <http://example.org> ns:rel <http://example.org/b>,
        ...             <http://example.org/a> .
        ... ''')
        >>> isomorphic(g1, g2)
        True

        >>> g3 = Graph().parse(format='n3', data='''
        ...     @prefix : <http://example.org/ns#> .
        ...     <http://example.org> :rel <http://example.org/a> .
        ...     <http://example.org> :rel <http://example.org/b> .
        ...     <http://example.org> :rel <http://example.org/c> .
        ... ''')
        >>> isomorphic(g1, g3)
        False
    """
    return _TripleCanonicalizer(graph1).to_hash() == \
        _TripleCanonicalizer(graph2).to_hash()


def to_canonical_graph(g1):
    """
    Creates a canonical, read-only graph where all bnode id:s are based on
    deterministical MD5 checksums, correlated with the graph contents.
    """
    graph = Graph()
    graph += _TripleCanonicalizer(g1, _md5_hash).canonical_triples()
    return ReadOnlyGraphAggregate([graph])


def graph_diff(g1, g2):
    """
    Returns three sets of triples: "in both", "in first" and "in second".
    """
    # bnodes have deterministic values in canonical graphs:
    cg1 = to_canonical_graph(g1)
    cg2 = to_canonical_graph(g2)
    in_both = cg1 * cg2
    in_first = cg1 - cg2
    in_second = cg2 - cg1
    return (in_both, in_first, in_second)


def _md5_hash(t):
    h = md()
    for i in t:
        if isinstance(i, tuple):
            h.update(_md5_hash(i).encode('ascii'))
        else:
            h.update(unicode(i).encode("utf8"))
    return h.hexdigest()


_MOCK_BNODE = BNode()


def similar(g1, g2):
    """
    Checks if the two graphs are "similar", by comparing sorted triples where
    all bnodes have been replaced by a singular mock bnode (the
    ``_MOCK_BNODE``).

    This is a much cheaper, but less reliable, alternative to the comparison
    algorithm in ``isomorphic``.
    """
    return all(t1 == t2 for (t1, t2) in _squashed_graphs_triples(g1, g2))


def _squashed_graphs_triples(g1, g2):
    for (t1, t2) in zip(sorted(_squash_graph(g1)), sorted(_squash_graph(g2))):
        yield t1, t2


def _squash_graph(graph):
    return (_squash_bnodes(triple) for triple in graph)


def _squash_bnodes(triple):
    return tuple((isinstance(t, BNode) and _MOCK_BNODE) or t for t in triple)