This file is indexed.

/usr/lib/pypy/dist-packages/schema.py is in pypy-schema 0.6.7-1.

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
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
"""schema is a library for validating Python data structures, such as those
obtained from config-files, forms, external services or command-line
parsing, converted from JSON/YAML (or something else) to Python data-types."""

import re

__version__ = '0.6.7'
__all__ = ['Schema',
           'And', 'Or', 'Regex', 'Optional', 'Use', 'Forbidden', 'Const',
           'SchemaError',
           'SchemaWrongKeyError',
           'SchemaMissingKeyError',
           'SchemaForbiddenKeyError',
           'SchemaUnexpectedTypeError']


class SchemaError(Exception):
    """Error during Schema validation."""

    def __init__(self, autos, errors=None):
        self.autos = autos if type(autos) is list else [autos]
        self.errors = errors if type(errors) is list else [errors]
        Exception.__init__(self, self.code)

    @property
    def code(self):
        """
        Removes duplicates values in auto and error list.
        parameters.
        """
        def uniq(seq):
            """
            Utility function that removes duplicate.
            """
            seen = set()
            seen_add = seen.add
            # This way removes duplicates while preserving the order.
            return [x for x in seq if x not in seen and not seen_add(x)]
        data_set = uniq(i for i in self.autos if i is not None)
        error_list = uniq(i for i in self.errors if i is not None)
        if error_list:
            return '\n'.join(error_list)
        return '\n'.join(data_set)


class SchemaWrongKeyError(SchemaError):
    """Error Should be raised when an unexpected key is detected within the
    data set being."""
    pass


class SchemaMissingKeyError(SchemaError):
    """Error should be raised when a mandatory key is not found within the
    data set being vaidated"""
    pass


class SchemaForbiddenKeyError(SchemaError):
    """Error should be raised when a forbidden key is found within the
    data set being validated, and its value matches the value that was specified"""
    pass


class SchemaUnexpectedTypeError(SchemaError):
    """Error should be raised when a type mismatch is detected within the
    data set being validated."""
    pass


class And(object):
    """
    Utility function to combine validation directives in AND Boolean fashion.
    """
    def __init__(self, *args, **kw):
        self._args = args
        assert set(kw).issubset(['error', 'schema', 'ignore_extra_keys'])
        self._error = kw.get('error')
        self._ignore_extra_keys = kw.get('ignore_extra_keys', False)
        # You can pass your inherited Schema class.
        self._schema = kw.get('schema', Schema)

    def __repr__(self):
        return '%s(%s)' % (self.__class__.__name__,
                           ', '.join(repr(a) for a in self._args))

    def validate(self, data):
        """
        Validate data using defined sub schema/expressions ensuring all
        values are valid.
        :param data: to be validated with sub defined schemas.
        :return: returns validated data
        """
        for s in [self._schema(s, error=self._error,
                               ignore_extra_keys=self._ignore_extra_keys)
                  for s in self._args]:
            data = s.validate(data)
        return data


class Or(And):
    """Utility function to combine validation directives in a OR Boolean
    fashion."""
    def validate(self, data):
        """
        Validate data using sub defined schema/expressions ensuring at least
        one value is valid.
        :param data: data to be validated by provided schema.
        :return: return validated data if not validation
        """
        x = SchemaError([], [])
        for s in [self._schema(s, error=self._error,
                               ignore_extra_keys=self._ignore_extra_keys)
                  for s in self._args]:
            try:
                return s.validate(data)
            except SchemaError as _x:
                x = _x
        raise SchemaError(['%r did not validate %r' % (self, data)] + x.autos,
                          [self._error.format(data) if self._error else None] +
                          x.errors)


class Regex(object):
    """
    Enables schema.py to validate string using regular expressions.
    """
    # Map all flags bits to a more readable description
    NAMES = ['re.ASCII', 're.DEBUG', 're.VERBOSE', 're.UNICODE', 're.DOTALL',
             're.MULTILINE', 're.LOCALE', 're.IGNORECASE', 're.TEMPLATE']

    def __init__(self, pattern_str, flags=0, error=None):
        self._pattern_str = pattern_str
        flags_list = [Regex.NAMES[i] for i, f in  # Name for each bit
                      enumerate('{0:09b}'.format(flags)) if f != '0']

        if flags_list:
            self._flags_names = ', flags=' + '|'.join(flags_list)
        else:
            self._flags_names = ''

        self._pattern = re.compile(pattern_str, flags=flags)
        self._error = error

    def __repr__(self):
        return '%s(%r%s)' % (
            self.__class__.__name__, self._pattern_str, self._flags_names
        )

    def validate(self, data):
        """
        Validated data using defined regex.
        :param data: data to be validated
        :return: return validated data.
        """
        e = self._error

        try:
            if self._pattern.search(data):
                return data
            else:
                raise SchemaError('%r does not match %r' % (self, data), e)
        except TypeError:
            raise SchemaError('%r is not string nor buffer' % data, e)


class Use(object):
    """
    For more general use cases, you can use the Use class to transform
    the data while it is being validate.
    """
    def __init__(self, callable_, error=None):
        assert callable(callable_)
        self._callable = callable_
        self._error = error

    def __repr__(self):
        return '%s(%r)' % (self.__class__.__name__, self._callable)

    def validate(self, data):
        try:
            return self._callable(data)
        except SchemaError as x:
            raise SchemaError([None] + x.autos,
                              [self._error.format(data)
                               if self._error else None] + x.errors)
        except BaseException as x:
            f = _callable_str(self._callable)
            raise SchemaError('%s(%r) raised %r' % (f, data, x),
                              self._error.format(data)
                              if self._error else None)


COMPARABLE, CALLABLE, VALIDATOR, TYPE, DICT, ITERABLE = range(6)


def _priority(s):
    """Return priority for a given object."""
    if type(s) in (list, tuple, set, frozenset):
        return ITERABLE
    if type(s) is dict:
        return DICT
    if issubclass(type(s), type):
        return TYPE
    if hasattr(s, 'validate'):
        return VALIDATOR
    if callable(s):
        return CALLABLE
    else:
        return COMPARABLE


class Schema(object):
    """
    Entry point of the library, use this class to instantiate validation
    schema for the data that will be validated.
    """
    def __init__(self, schema, error=None, ignore_extra_keys=False):
        self._schema = schema
        self._error = error
        self._ignore_extra_keys = ignore_extra_keys

    def __repr__(self):
        return '%s(%r)' % (self.__class__.__name__, self._schema)

    @staticmethod
    def _dict_key_priority(s):
        """Return priority for a given key object."""
        if isinstance(s, Forbidden):
            return _priority(s._schema) - 0.5
        if isinstance(s, Optional):
            return _priority(s._schema) + 0.5
        return _priority(s)

    def validate(self, data):
        Schema = self.__class__
        s = self._schema
        e = self._error
        i = self._ignore_extra_keys
        flavor = _priority(s)
        if flavor == ITERABLE:
            data = Schema(type(s), error=e).validate(data)
            o = Or(*s, error=e, schema=Schema, ignore_extra_keys=i)
            return type(data)(o.validate(d) for d in data)
        if flavor == DICT:
            data = Schema(dict, error=e).validate(data)
            new = type(data)()  # new - is a dict of the validated values
            coverage = set()  # matched schema keys
            # for each key and value find a schema entry matching them, if any
            sorted_skeys = sorted(s, key=self._dict_key_priority)
            for key, value in data.items():
                for skey in sorted_skeys:
                    svalue = s[skey]
                    try:
                        nkey = Schema(skey, error=e).validate(key)
                    except SchemaError:
                        pass
                    else:
                        if isinstance(skey, Forbidden):
                            # As the content of the value makes little sense for
                            # forbidden keys, we reverse its meaning:
                            # we will only raise the SchemaErrorForbiddenKey
                            # exception if the value does match, allowing for
                            # excluding a key only if its value has a certain type,
                            # and allowing Forbidden to work well in combination
                            # with Optional.
                            try:
                                nvalue = Schema(svalue, error=e).validate(value)
                            except SchemaError:
                                continue
                            raise SchemaForbiddenKeyError(
                                    'Forbidden key encountered: %r in %r' %
                                    (nkey, data), e)
                        else:
                            try:
                                nvalue = Schema(svalue, error=e,
                                                ignore_extra_keys=i).validate(value)
                            except SchemaError as x:
                                k = "Key '%s' error:" % nkey
                                raise SchemaError([k] + x.autos, [e] + x.errors)
                            else:
                                new[nkey] = nvalue
                                coverage.add(skey)
                                break
            required = set(k for k in s if type(k) not in [Optional, Forbidden])
            if not required.issubset(coverage):
                missing_keys = required - coverage
                s_missing_keys = \
                    ', '.join(repr(k) for k in sorted(missing_keys, key=repr))
                raise \
                    SchemaMissingKeyError('Missing keys: ' + s_missing_keys, e)
            if not self._ignore_extra_keys and (len(new) != len(data)):
                wrong_keys = set(data.keys()) - set(new.keys())
                s_wrong_keys = \
                    ', '.join(repr(k) for k in sorted(wrong_keys, key=repr))
                raise \
                    SchemaWrongKeyError(
                        'Wrong keys %s in %r' % (s_wrong_keys, data),
                        e.format(data) if e else None)

            # Apply default-having optionals that haven't been used:
            defaults = set(k for k in s if type(k) is Optional and
                           hasattr(k, 'default')) - coverage
            for default in defaults:
                new[default.key] = default.default

            return new
        if flavor == TYPE:
            if isinstance(data, s):
                return data
            else:
                raise SchemaUnexpectedTypeError(
                    '%r should be instance of %r' % (data, s.__name__),
                    e.format(data) if e else None)
        if flavor == VALIDATOR:
            try:
                return s.validate(data)
            except SchemaError as x:
                raise SchemaError([None] + x.autos, [e] + x.errors)
            except BaseException as x:
                raise SchemaError(
                    '%r.validate(%r) raised %r' % (s, data, x),
                    self._error.format(data) if self._error else None)
        if flavor == CALLABLE:
            f = _callable_str(s)
            try:
                if s(data):
                    return data
            except SchemaError as x:
                raise SchemaError([None] + x.autos, [e] + x.errors)
            except BaseException as x:
                raise SchemaError(
                    '%s(%r) raised %r' % (f, data, x),
                    self._error.format(data) if self._error else None)
            raise SchemaError('%s(%r) should evaluate to True' % (f, data), e)
        if s == data:
            return data
        else:
            raise SchemaError('%r does not match %r' % (s, data),
                              e.format(data) if e else None)


class Optional(Schema):
    """Marker for an optional part of the validation Schema."""
    _MARKER = object()

    def __init__(self, *args, **kwargs):
        default = kwargs.pop('default', self._MARKER)
        super(Optional, self).__init__(*args, **kwargs)
        if default is not self._MARKER:
            # See if I can come up with a static key to use for myself:
            if _priority(self._schema) != COMPARABLE:
                raise TypeError(
                    'Optional keys with defaults must have simple, '
                    'predictable values, like literal strings or ints. '
                    '"%r" is too complex.' % (self._schema,))
            self.default = default
            self.key = self._schema

    def __hash__(self):
        return hash(self._schema)

    def __eq__(self, other):
        return (self.__class__ is other.__class__ and
                getattr(self, 'default', self._MARKER) ==
                getattr(other, 'default', self._MARKER) and
                self._schema == other._schema)


class Forbidden(Schema):
    def __init__(self, *args, **kwargs):
        super(Forbidden, self).__init__(*args, **kwargs)
        self.key = self._schema


class Const(Schema):
    def validate(self, data):
        super(Const, self).validate(data)
        return data


def _callable_str(callable_):
    if hasattr(callable_, '__name__'):
        return callable_.__name__
    return str(callable_)