def __init__(
self,
name='all_steps',
model_dump=None,
execution_time_in_minutes=0.0,
endpoint='all_assignation/',
query_string='',
query_string_parameters=AssignationStepQueryStringParameters()):
if model_dump is None:
model_dump = [ModelDumpParameters()]
super().__init__(name, model_dump, execution_time_in_minutes, endpoint,
query_string)
self.query_string_parameters = query_string_parameters
def __init__(
self,
name='vectorizer',
model_dump=None,
execution_time_in_minutes=0.0,
endpoint='vectorizer/',
query_string='',
query_string_parameters=VectorizerStepQueryStringParameters()
):
if model_dump is None:
model_dump = [ModelDumpParameters()]
super().__init__(name, model_dump, execution_time_in_minutes, endpoint, query_string)
self.query_string_parameters = query_string_parameters
def __init__(self,
name='nlp',
model_dump=None,
execution_time_in_minutes=0.0,
endpoint='nlp/',
query_string=''):
self.name = name
self.model_dump = []
if model_dump is None:
model_dump = []
for dump in model_dump:
if isinstance(dump, ModelDumpParameters):
self.model_dump.append(dump)
continue
if isinstance(dump, dict):
self.model_dump.append(
ModelDumpParameters(dump['_id'], dump['_type']))
self.execution_time_in_minutes = execution_time_in_minutes
self.endpoint = endpoint
self.query_string = query_string