#!/usr/bin/env python

"""
<Program Name>
  schema.py

<Author>
  Geremy Condra
  Vladimir Diaz <vladimir.v.diaz@gmail.com>

<Started>
  Refactored April 30, 2012 (previously named checkjson.py). -Vlad

<Copyright>
  See LICENSE for licensing information.

<Purpose>
  Provide a variety of classes that compare objects
  based on their format and determine if they match.
  These classes, or schemas, do not simply check the
  type of the objects being compared, but inspect
  additional aspects of the objects like names and
  the number of items included.

  For example:
  >>> good = {'first': 'Marty', 'last': 'McFly'}
  >>> bad = {'sdfsfd': 'Biff', 'last': 'Tannen'} 
  >>> schema = Object(first=AnyString(), last=AnyString())
  >>> schema.matches(good)
  True
  >>> schema.matches(bad)
  False

  In the process of determining if the two objects matched the template,
  tuf.schema.Object() inspected the named keys of both dictionaries.
  In the case of the 'bad' dict, a 'first' dict key could not be found.
  As a result, 'bad' was flagged a mismatch.
  
  'schema.py' provides additional schemas for testing objects based on other
  criteria.  See 'tuf.formats.py' and the rest of this module for extensive
  examples.  Anything related to the checking of TUF objects and their formats
  can be found in 'formats.py'.
"""

# Help with Python 3 compatibility, where the print statement is a function, an
# implicit relative import is invalid, and the '/' operator performs true
# division.  Example:  print 'hello world' raises a 'SyntaxError' exception.
from __future__ import print_function
from __future__ import absolute_import
from __future__ import division
from __future__ import unicode_literals

import re
import sys

import tuf
import tuf._vendor.six as six

class Schema:
  """
  <Purpose>
    A schema matches a set of possible Python objects, of types
    that are encodable in JSON.  'Schema' is the base class for
    the other classes defined in this module.  All derived classes
    should implement check_match().
  """

  def matches(self, object):
    """
    <Purpose> 
      Return True if 'object' matches this schema, False if it doesn't.
      If the caller wishes to signal an error on a failed match, check_match()
      should be called, which will raise a 'tuf.FormatError' exception.
    """
    
    try:
      self.check_match(object)
    except tuf.FormatError:
      return False
    else:
      return True


  def check_match(self, object):
    """
    <Purpose> 
      Abstract method.  Classes that inherit from 'Schema' must
      implement check_match().  If 'object' matches the schema, check_match()
      should simply return.  If 'object' does not match the schema,
      'tuf.FormatError' should be raised.
    """
    
    raise NotImplementedError()





class Any(Schema):
  """
  <Purpose>
    Matches any single object.  Whereas other schemas explicitly state
    the required type of its argument, Any() does not. It simply does a
    'pass' when 'check_match()' is called and at the point where the schema
    is instantiated.

    Supported methods include
      matches(): returns a Boolean result.
      check_match(): passed

  <Example Use>
    
    >>> schema = Any()
    >>> schema.matches('A String')
    True
    >>> schema.matches([1, 'list'])
    True
  """

  def __init__(self):
    pass


  def check_match(self, object):
    pass





class String(Schema):
  """
  <Purpose>
    Matches a particular string.  The argument object
    must be a string and be equal to a specific string value.
    At instantiation, the string is set and any future comparisons
    are checked against this internal string value.

    Supported methods include
      matches(): returns a Boolean result.
      check_match(): raises 'tuf.FormatError' on a mismatch.

  <Example Use>
    
    >>> schema = String('Hi')
    >>> schema.matches('Hi')
    True
    >>> schema.matches('Not hi')
    False
  """

  def __init__(self, string):
    if not isinstance(string, six.string_types):
      raise tuf.FormatError('Expected a string but got '+repr(string))
    
    self._string = string


  def check_match(self, object):
    if self._string != object:
      raise tuf.FormatError('Expected '+repr(self._string)+' got '+repr(object))





class AnyString(Schema):
  """
  <Purpose>
    Matches any string, but not a non-string object.  This schema
    can be viewed as the Any() schema applied to Strings, but an
    additional check is performed to ensure only strings are considered.

    Supported methods include
      matches(): returns a Boolean result.
      check_match(): raises 'tuf.FormatError' on a mismatch.

  <Example Use>
    
    >>> schema = AnyString()
    >>> schema.matches('')
    True
    >>> schema.matches('a string')
    True
    >>> schema.matches(['a'])
    False
    >>> schema.matches(3)
    False
    >>> schema.matches(u'a unicode string')
    True
    >>> schema.matches({})
    False
  """

  def __init__(self):
    pass


  def check_match(self, object):
    if not isinstance(object, six.string_types):
      raise tuf.FormatError('Expected a string but got '+repr(object))





class AnyBytes(Schema):
  """
  <Purpose>
    Matches any byte string, but not a non-byte object.  This schema
    can be viewed as the Any() schema applied to byte strings, but an
    additional check is performed to ensure only strings are considered.

    Supported methods include
      matches(): returns a Boolean result.
      check_match(): raises 'tuf.FormatError' on a mismatch.

  <Example Use>
    
    >>> schema = AnyBytes()
    >>> schema.matches(b'')
    True
    >>> schema.matches(b'a string')
    True
    >>> schema.matches(['a'])
    False
    >>> schema.matches(3)
    False
    >>> schema.matches({})
    False
  """

  def __init__(self):
    pass


  def check_match(self, object):
    if not isinstance(object, six.binary_type):
      raise tuf.FormatError('Expected a byte string but got '+repr(object))





class LengthString(Schema):
  """
  <Purpose>
    Matches any string of a specified length.  The argument object
    must be a string.  At instantiation, the string length is set
    and any future comparisons are checked against this internal
    string value length.

    Supported methods include
      matches(): returns a Boolean result.
      check_match(): raises 'tuf.FormatError' on a mismatch.

  <Example Use>
    
    >>> schema = LengthString(5)
    >>> schema.matches('Hello')
    True
    >>> schema.matches('Hi')
    False
  """

  def __init__(self, length):
    if isinstance(length, bool) or not isinstance(length, six.integer_types):
      # We need to check for bool as a special case, since bool
      # is for historical reasons a subtype of int.
      raise tuf.FormatError('Got ' + repr(length) + ' instead of an integer.')
    
    self._string_length = length 


  def check_match(self, object):
    if not isinstance(object, six.string_types):
      raise tuf.FormatError('Expected a string but got ' + repr(object))

    if len(object) != self._string_length:
      raise tuf.FormatError('Expected a string of length ' + \
                            repr(self._string_length))





class LengthBytes(Schema):
  """
  <Purpose>
    Matches any Bytes of a specified length.  The argument object must be either
    a str() in Python 2, or bytes() in Python 3.  At instantiation, the bytes
    length is set and any future comparisons are checked against this internal
    bytes value length.

    Supported methods include
      matches(): returns a Boolean result.
      check_match(): raises 'tuf.FormatError' on a mismatch.

  <Example Use>
    
    >>> schema = LengthBytes(5)
    >>> schema.matches(b'Hello')
    True
    >>> schema.matches(b'Hi')
    False
  """

  def __init__(self, length):
    if isinstance(length, bool) or not isinstance(length, six.integer_types):
      # We need to check for bool as a special case, since bool
      # is for historical reasons a subtype of int.
      raise tuf.FormatError('Got ' + repr(length) + ' instead of an integer.')
    
    self._bytes_length = length 


  def check_match(self, object):
    if not isinstance(object, six.binary_type):
      raise tuf.FormatError('Expected a byte but got ' + repr(object))

    if len(object) != self._bytes_length:
      raise tuf.FormatError('Expected a byte of length ' + \
                            repr(self._bytes_length))





class OneOf(Schema):
  """
  <Purpose>
    Matches an object that matches any one of several schemas.  OneOf()
    returns a result as soon as one of its recognized sub-schemas is encountered
    in the object argument.  When OneOf() is instantiated, its supported
    sub-schemas are specified by a sequence type (e.g., a list, tuple, etc.).
    A mismatch is returned after checking all sub-schemas and not finding
    a supported type.

    Supported methods include
      matches(): returns a Boolean result.
      check_match(): raises 'tuf.FormatError' on a mismatch.

  <Example Use>

    >>> schema = OneOf([ListOf(Integer()), String('Hello'), String('bye')])
    >>> schema.matches(3)
    False
    >>> schema.matches('bye')
    True
    >>> schema.matches([])
    True
    >>> schema.matches([1,2])
    True
    >>> schema.matches(['Hi'])
    False
  """

  def __init__(self, alternatives):
    # Ensure each item of the list contains the expected object type.
    if not isinstance(alternatives, list):
      raise tuf.FormatError('Expected a list but got ' + repr(alternatives))
    for alternative in alternatives:
      if not isinstance(alternative, Schema):
        raise tuf.FormatError('List contains an invalid item ' + repr(alternative))
    
    self._alternatives = alternatives


  def check_match(self, object):
    # Simply return as soon as we find a match.
    # Raise 'tuf.FormatError' if no matches are found.
    for alternative in self._alternatives:
      if alternative.matches(object):
        return
    raise tuf.FormatError('Object did not match a recognized alternative.')





class AllOf(Schema):
  """
  <Purpose>  
    Matches the intersection of a list of schemas.  The object being tested
    must match all of the required sub-schemas.  Unlike OneOf(), which can
    return a result as soon as a match is found in one of its supported
    sub-schemas, AllOf() must verify each sub-schema before returning a 
    result.

    Supported methods include
      matches(): returns a Boolean result.
      check_match(): raises 'tuf.FormatError' on a mismatch.

  <Example Use>

    >>> schema = AllOf([Any(), AnyString(), String('a')])
    >>> schema.matches('b')
    False
    >>> schema.matches('a')
    True
  """

  def __init__(self, required_schemas):
    # Ensure each item of the list contains the expected object type.
    if not isinstance(required_schemas, list):
      raise tuf.FormatError('Expected a list but got'+repr(required_schemas))
    for schema in required_schemas:
      if not isinstance(schema, Schema):
        raise tuf.FormatError('List contains an invalid item '+repr(schema))
    
    self._required_schemas = required_schemas[:]


  def check_match(self, object):
    for required_schema in self._required_schemas:
      required_schema.check_match(object)





class Boolean(Schema):
  """
  <Purpose>
    Matches a boolean.  The object argument must be one
    of True or False.  All other types are flagged as mismatches.

    Supported methods include
      matches(): returns a Boolean result.
      check_match(): raises 'tuf.FormatError' on a mismatch.

  <Example Use>

    >>> schema = Boolean()
    >>> schema.matches(True) and schema.matches(False)
    True
    >>> schema.matches(11)
    False
 """

  def __init__(self):
    pass


  def check_match(self, object):
    if not isinstance(object, bool):
      raise tuf.FormatError('Got '+repr(object)+' instead of a boolean.')





class ListOf(Schema):
  """
  <Purpose>
    Matches a homogeneous list of some sub-schema.  That is, all the
    sub-schema must be of the same type.  The object argument must
    be a sequence type (e.g., a list, tuple, etc.).  When ListOf()
    is instantiated, a minimum and maximum count can be specified
    for the homogeneous sub-schema list.  If min_count is set to
    'n', the object argument sequence must contain 'n' items.  See
    ListOf()'s __init__ method for the expected arguments.

    Supported methods include
      matches(): returns a Boolean result.
      check_match(): raises 'tuf.FormatError' on a mismatch.

  <Example Use>

    >>> schema = ListOf(RegularExpression('(?:..)*'))
    >>> schema.matches('hi')
    False
    >>> schema.matches([])
    True
    >>> schema.matches({})
    False
    >>> schema.matches(['Hi', 'this', 'list', 'is', 'full', 'of', 'even', 'strs'])
    True
    >>> schema.matches(['This', 'one', 'is not'])
    False

    >>> schema = ListOf(Integer(), min_count=3, max_count=10)
    >>> schema.matches([3]*2)
    False
    >>> schema.matches([3]*3)
    True
    >>> schema.matches([3]*10)
    True
    >>> schema.matches([3]*11)
    False
  """

  def __init__(self, schema, min_count=0, max_count=sys.maxsize, list_name='list'):
    """
    <Purpose> 
      Create a new ListOf schema.

    <Arguments>
      schema:  The pattern to match.
      min_count: The minimum number of sub-schema in 'schema'.
      max_count: The maximum number of sub-schema in 'schema'.
      list_name: A string identifier for the ListOf object.
    """
    
    if not isinstance(schema, Schema):
      message = 'Expected Schema type but got '+repr(schema)
      raise tuf.FormatError(message)
    
    self._schema = schema
    self._min_count = min_count
    self._max_count = max_count
    self._list_name = list_name

  
  def check_match(self, object):
    if not isinstance(object, (list, tuple)):
      message = 'Expected '+repr(self._list_name)+' but got '+repr(object)
      raise tuf.FormatError(message)

    # Check if all the items in the 'object' list
    # match 'schema'.
    for item in object:
      try:
        self._schema.check_match(item)
      except tuf.FormatError as e:
        raise tuf.FormatError(str(e)+' in '+repr(self._list_name))

    # Raise exception if the number of items in the list is
    # not within the expected range.
    if not (self._min_count <= len(object) <= self._max_count):
        raise tuf.FormatError('Length of '+repr(self._list_name)+' out of range')





class Integer(Schema):
  """
  <Purpose>
    Matches an integer.  A range can be specified.
    For example, only integers between 8 and 42 can be set as
    a requirement.  The object argument is also checked against
    a Boolean type, since booleans have historically been considered
    a sub-type of integer.

    Supported methods include
      matches(): returns a Boolean result.
      check_match(): raises 'tuf.FormatError' on a mismatch.

  <Example Use>

    >>> schema = Integer()
    >>> schema.matches(99)
    True
    >>> schema.matches(False)
    False
    >>> schema.matches('a string')
    False
    >>> Integer(lo=10, hi=30).matches(25)
    True
    >>> Integer(lo=10, hi=30).matches(5)
    False
  """

  def __init__(self, lo = -2147483648, hi = 2147483647):
    """
    <Purpose> 
      Create a new Integer schema.

    <Arguments>
      lo: The minimum value the int object argument can be.
      hi: The maximum value the int object argument can be.
    """
    
    self._lo = lo
    self._hi = hi


  def check_match(self, object):
    if isinstance(object, bool) or not isinstance(object, six.integer_types):
      # We need to check for bool as a special case, since bool
      # is for historical reasons a subtype of int.
      raise tuf.FormatError('Got '+repr(object)+' instead of an integer.')
    
    elif not (self._lo <= object <= self._hi):
      int_range = '['+repr(self._lo)+', '+repr(self._hi)+'].'
      raise tuf.FormatError(repr(object)+' not in range '+int_range)





class DictOf(Schema):
  """
  <Purpose>
    Matches a mapping from items matching a particular key-schema
    to items matching a value-schema (i.e., the object being checked
    must be a dict).  Note that in JSON, keys must be strings.  In the
    example below, the keys of the dict must be one of the letters
    contained in 'aeiou' and the value must be a structure containing
    any two strings.

    Supported methods include
      matches(): returns a Boolean result.
      check_match(): raises 'tuf.FormatError' on a mismatch.

  <Example Use>

    >>> schema = DictOf(RegularExpression(r'[aeiou]+'), Struct([AnyString(), AnyString()]))
    >>> schema.matches('')
    False
    >>> schema.matches({})
    True
    >>> schema.matches({'a': ['x', 'y'], 'e' : ['', '']})
    True
    >>> schema.matches({'a': ['x', 3], 'e' : ['', '']})
    False
    >>> schema.matches({'a': ['x', 'y'], 'e' : ['', ''], 'd' : ['a', 'b']})
    False
  """

  def __init__(self, key_schema, value_schema):
    """
    <Purpose> 
      Create a new DictOf schema.

    <Arguments>
      key_schema:  The dictionary's key.
      value_schema: The dictionary's value.
    """
    
    if not isinstance(key_schema, Schema):
      raise tuf.FormatError('Expected Schema but got '+repr(key_schema))
   
    if not isinstance(value_schema, Schema):
      raise tuf.FormatError('Expected Schema but got '+repr(value_schema))
    
    self._key_schema = key_schema
    self._value_schema = value_schema


  def check_match(self, object):
    if not isinstance(object, dict): 
      raise tuf.FormatError('Expected a dict but got '+repr(object))

    for key, value in six.iteritems(object):
      self._key_schema.check_match(key)
      self._value_schema.check_match(value)





class Optional(Schema):
  """
  <Purpose> 
    Provide a way for the Object() schema to accept optional
    dictionary keys.  The Object() schema outlines how a dictionary
    should look, such as the names for dict keys and the object type
    of the dict values.  Optional()'s intended use is as a sub-schema
    to Object().  Object() flags an object as a mismatch if a required
    key is not encountered, however, dictionary keys labeled Optional()
    are not required to appear in the object's list of required keys.
    If an Optional() key IS found, Optional()'s sub-schemas are
    then verified.
    
    Supported methods include
      matches(): returns a Boolean result.
      check_match(): raises 'tuf.FormatError' on a mismatch.

  <Example Use>

    >>> schema = Object(k1=String('X'), k2=Optional(String('Y')))
    >>> schema.matches({'k1': 'X', 'k2': 'Y'})
    True
    >>> schema.matches({'k1': 'X', 'k2': 'Z'})
    False
    >>> schema.matches({'k1': 'X'})
    True
  """

  def __init__(self, schema):
    if not isinstance(schema, Schema):
      raise tuf.FormatError('Expected Schema, but got '+repr(schema))
    self._schema = schema

  
  def check_match(self, object):
    self._schema.check_match(object)





class Object(Schema):
  """
  <Purpose>
    Matches a dict from specified keys to key-specific types.  Unrecognized
    keys are allowed.  The Object() schema outlines how a dictionary
    should look, such as the names for dict keys and the object type of the
    dict values.  See schema.Optional() to learn how Object() incorporates
    optional sub-schemas.
    
    Supported methods include
      matches(): returns a Boolean result.
      check_match(): raises 'tuf.FormatError' on a mismatch.

  <Example Use>

    >>> schema = Object(a=AnyString(), bc=Struct([Integer(), Integer()]))
    >>> schema.matches({'a':'ZYYY', 'bc':[5,9]})
    True
    >>> schema.matches({'a':'ZYYY', 'bc':[5,9], 'xx':5})
    True
    >>> schema.matches({'a':'ZYYY', 'bc':[5,9,3]})
    False
    >>> schema.matches({'a':'ZYYY'})
    False
  """

  def __init__(self, object_name='object', **required):
    """
    <Purpose> 
      Create a new Object schema.

    <Arguments>
      object_name: A string identifier for the object argument.
      
      A variable number of keyword arguments is accepted.
    """
  
    # Ensure valid arguments. 
    for key, schema in six.iteritems(required):
      if not isinstance(schema, Schema):
        raise tuf.FormatError('Expected Schema but got '+repr(schema))

    self._object_name = object_name
    self._required = list(required.items())


  def check_match(self, object):
    if not isinstance(object, dict):
      message = 'Wanted a '+repr(self._object_name)+'.'
      raise tuf.FormatError(message)
    
    # (key, schema) = (a, AnyString()) = (a=AnyString())
    for key, schema in self._required:
      # Check if 'object' has all the required dict keys.
      # If not one of the required keys, check if it is an Optional().
      try:
        item = object[key]
      except KeyError:
        # If not an Optional schema, raise an exception.
        if not isinstance(schema, Optional):
          message = 'Missing key ' + repr(key) + ' in ' + repr(self._object_name)
          raise tuf.FormatError(message)
      # Check that 'object's schema matches Object()'s schema for this
      # particular 'key'.
      else:
        try:
          schema.check_match(item)
        except tuf.FormatError as e:
          raise tuf.FormatError(str(e) + ' in ' + self._object_name + '.' + key)





class Struct(Schema):
  """
  <Purpose>
    Matches a non-homogeneous list of items.  The sub-schemas
    are allowed to vary.  The object argument must be a sequence type
    (e.g., a list, tuple, etc.).  There is also an option to specify
    that additional schemas not explicitly defined at instantiation
    are allowed.  See __init__() for the complete list of arguments
    accepted.

    Supported methods include
      matches(): returns a Boolean result.
      check_match(): raises 'tuf.FormatError' on a mismatch.

  <Example Use>

    >>> schema = Struct([ListOf(AnyString()), AnyString(), String('X')])
    >>> schema.matches(False)
    False
    >>> schema.matches('Foo')
    False
    >>> schema.matches([[], 'Q', 'X'])
    True
    >>> schema.matches([[], 'Q', 'D'])
    False
    >>> schema.matches([[3], 'Q', 'X'])
    False
    >>> schema.matches([[], 'Q', 'X', 'Y'])
    False

    >>> schema = Struct([String('X')], allow_more=True)
    >>> schema.matches([])
    False
    >>> schema.matches(['X'])
    True
    >>> schema.matches(['X', 'Y'])
    True
    >>> schema.matches(['X', ['Y', 'Z']])
    True
    >>> schema.matches([['X']])
    False

    >>> schema = Struct([String('X'), Integer()], [Integer()])
    >>> schema.matches([])
    False
    >>> schema.matches({})
    False
    >>> schema.matches(['X'])
    False
    >>> schema.matches(['X', 3])
    True
    >>> schema.matches(['X', 3, 9])
    True
    >>> schema.matches(['X', 3, 9, 11])
    False
    >>> schema.matches(['X', 3, 'A'])
    False
  """

  def __init__(self, sub_schemas, optional_schemas=[], allow_more=False,
               struct_name='list'):
    """
    <Purpose> 
      Create a new Struct schema.

    <Arguments>
      sub_schemas: The sub-schemas recognized.
      optional_schemas: The optional list of schemas.
      allow_more: Specifies that an optional list of types is allowed.
      struct_name: A string identifier for the Struct object.
    """
    
    # Ensure each item of the list contains the expected object type.
    if not isinstance(sub_schemas, (list, tuple)):
      message = 'Expected Schema but got ' + repr(sub_schemas)
      raise tuf.FormatError(message)
    for schema in sub_schemas:
      if not isinstance(schema, Schema):
        raise tuf.FormatError('Expected Schema but got ' + repr(schema))
    
    self._sub_schemas = sub_schemas + optional_schemas
    self._min = len(sub_schemas)
    self._allow_more = allow_more
    self._struct_name = struct_name


  def check_match(self, object):
    if not isinstance(object, (list, tuple)):
      raise tuf.FormatError('Expected ' + repr(self._struct_name) + '; got ' + repr(object))
    elif len(object) < self._min:
      raise tuf.FormatError('Too few fields in ' + self._struct_name)
    elif len(object) > len(self._sub_schemas) and not self._allow_more:
      raise tuf.FormatError('Too many fields in ' + self._struct_name)
    
    # Iterate through the items of 'object', checking against each schema
    # in the list of schemas allowed (i.e., the sub-schemas and also
    # any optional schemas.  The lenth of 'object' must be less than
    # the length of the required schemas + the optional schemas.  However,
    # 'object' is allowed to be only as large as the length of the required
    # schemas.  In the while loop below, we check against these two cases.
    index = 0
    while index < len(object) and index < len(self._sub_schemas):
      item = object[index]
      schema = self._sub_schemas[index]
      schema.check_match(item)
      index = index + 1





class RegularExpression(Schema):
  """
  <Purpose> 
    Matches any string that matches a given regular expression.
    The RE pattern set when RegularExpression is instantiated
    must not be None.  See __init__() for a complete list of
    accepted arguments.

    Supported methods include
      matches(): returns a Boolean result.
      check_match(): raises 'tuf.FormatError' on a mismatch.

  <Example Use>

    >>> schema = RegularExpression('h.*d')
    >>> schema.matches('hello world')
    True
    >>> schema.matches('Hello World')
    False
    >>> schema.matches('hello world!')
    False
    >>> schema.matches([33, 'Hello'])
    False
  """

  def __init__(self, pattern=None, modifiers=0, re_object=None, re_name=None):
    """
    <Purpose> 
      Create a new regular expression schema.

    <Arguments>
      pattern:  The pattern to match, or None if re_object is provided.
      modifiers:  Flags to use when compiling the pattern.
      re_object:  A compiled regular expression object.
      re_name: Identifier for the regular expression object.
    """

    if not isinstance(pattern, six.string_types):
      if pattern is not None:
        raise tuf.FormatError(repr(pattern) + ' is not a string.')
        
    if re_object is None:
      if pattern is None:
        error = 'Cannot compare against an unset regular expression'
        raise tuf.FormatError(error)
      if not pattern.endswith('$'):
        pattern += '$'
      re_object = re.compile(pattern, modifiers)
    self._re_object = re_object
        
    if re_name is None:
      if pattern is not None:
        re_name = 'pattern /' + pattern + '/'
      else:
        re_name = 'pattern'
    self._re_name = re_name


  def check_match(self, object):
    if not isinstance(object, six.string_types) or not self._re_object.match(object):
      raise tuf.FormatError(repr(object) + ' did not match ' + repr(self._re_name))



if __name__ == '__main__':
  # The interactive sessions of the documentation strings can
  # be tested by running schema.py as a standalone module.
  # python -B schema.py.
  import doctest
  doctest.testmod()
