def getParametersList(cls):
parameters = super(RandomWordProvider, cls).getParametersList()[:]
parameters += [
DataProviderParameter('choices', 'Choices',
'A comma separated list of word choices',
False),
DataProviderParameter('prefix', 'Prefix',
'A prefix to apply to the words.', False)
]
return parameters
def getParametersList(cls):
parameters = super(RandomPhraseProvider, cls).getParametersList()[:]
parameters += [
DataProviderParameter('min_words', 'Minimum words',
('The minimum number of words to'
' include in the phrase')),
DataProviderParameter('max_words', 'Maximum words',
('The maximum number of words to'
' include in the phrase')),
]
return parameters
def getParametersList(cls):
parameters = super(FixedDateTimeProvider, cls).getParametersList()[:]
parameters += [
DataProviderParameter('year', 'Year',
'Defaults to the current year', False),
DataProviderParameter('month', 'Month',
'Defaults to the current month', False),
DataProviderParameter('day', 'Day', 'Defaults to the current day',
False)
]
return parameters
def getParametersList(cls):
parameters = (super(RandomUniformDistributionFloatProvider,
cls).getParametersList()[:])
parameters += [
DataProviderParameter('min', 'Minimum value',
'A minimum value to be sampled, inclusive.',
False),
DataProviderParameter('max', 'Maximum value',
'A maximum value to be sampled, inclusive.',
False)
]
return parameters
def getParametersList(cls):
parameters = (super(RandomNormalDistributionFloatProvider,
cls).getParametersList()[:])
parameters += [
DataProviderParameter('mean', 'Mean',
'The mean for the normal distribution.',
False),
DataProviderParameter(
'stdev', 'Standard deviation',
'The standard deviation for the '
'normal distribution.', False)
]
return parameters
def getParametersList(cls):
parameters = super(SequenceIntegerProvider, cls).getParametersList()[:]
parameters += [
DataProviderParameter(
'name', 'The sequence name',
'The name of the sequence. By providing a name, '
'multiple providers can extract values from the '
'same sequence.', True),
DataProviderParameter('start', 'Start value',
'The first value to return.', False),
DataProviderParameter('step', 'Step',
'The increment step for the sequence.',
False)
]
return parameters
def getParametersList(cls):
parameters = (super(RandomNormalDistributionDateTimeProvider,
cls).getParametersList()[:])
parameters += [
DataProviderParameter('mean_year', 'Mean year',
'Defaults to the current year', False),
DataProviderParameter('mean_month', 'Mean month',
'Defaults to the current month', False),
DataProviderParameter('mean_day', 'Mean day',
'Defaults to the current day', False),
DataProviderParameter(
'stdev', 'Standard deviation',
'Standard deviation expressed in days. Defaults '
'to approximately 6 monhts', False)
]
return parameters
def getParametersList(cls):
parameters = (super(FixedReferenceProvider,
cls).getParametersList()[:])
parameters += [
DataProviderParameter('key', 'Model key',
'The key for the referenced model.', True),
]
return parameters
def getParametersList(cls):
parameters = (super(RandomReferenceProvider,
cls).getParametersList()[:])
parameters += [
DataProviderParameter('model_name', 'Model name',
'Choose the model type of the reference.',
True),
]
return parameters
def getParametersList(cls):
parameters = super(RandomBooleanProvider, cls).getParametersList()[:]
parameters += [
DataProviderParameter(
'chance', 'Chance for True',
'Chance (between 0 and 1) that True will be '
'returned.', False)
]
return parameters
def getParametersList(cls):
parameters = (super(RandomUniformDistributionDateProvider, cls).
getParametersList()[:])
parameters += [
DataProviderParameter('min_year',
'Minimum year',
'Defaults to the current year',
False),
DataProviderParameter('max_year',
'Maximum year',
'Defaults to the current year',
False),
DataProviderParameter('min_month',
'Minimum month',
'Defaults to the current month',
False),
DataProviderParameter('max_month',
'Maximum month',
'Defaults to the current month',
False),
DataProviderParameter('min_day',
'Minimum day',
'Defaults to the current day',
False),
DataProviderParameter('max_day',
'Maximum day',
'Defaults to the current day',
False)]
return parameters