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# -*- coding: utf-8 -*-
import finicityapi.models.net_monthly
import finicityapi.models.report_income_estimate
class ReportIncomeStreamSummary(object):
"""Implementation of the 'Report Income Stream Summary' model.
ReportIncomeStreamSummary
Attributes:
confidence_type (EstimateInclusionEnum): TODO: type description here.
net_monthly (list of NetMonthly): TODO: type description here.
income_estimate (ReportIncomeEstimate): TODO: type description here.
"""
# Create a mapping from Model property names to API property names
_names = {
"confidence_type":'confidenceType',
"net_monthly":'netMonthly',
"income_estimate":'incomeEstimate'
}
def __init__(self,
confidence_type=None,
net_monthly=None,
income_estimate=None,
additional_properties = {}):
"""Constructor for the ReportIncomeStreamSummary class"""
# Initialize members of the class
self.confidence_type = confidence_type
self.net_monthly = net_monthly
self.income_estimate = income_estimate
# Add additional model properties to the instance
self.additional_properties = additional_properties
@classmethod
def from_dictionary(cls,
dictionary):
"""Creates an instance of this model from a dictionary
Args:
dictionary (dictionary): A dictionary representation of the object as
obtained from the deserialization of the server's response. The keys
MUST match property names in the API description.
Returns:
object: An instance of this structure class.
"""
if dictionary is None:
return None
# Extract variables from the dictionary
confidence_type = dictionary.get('confidenceType')
net_monthly = None
if dictionary.get('netMonthly') != None:
net_monthly = list()
for structure in dictionary.get('netMonthly'):
net_monthly.append(finicityapi.models.net_monthly.NetMonthly.from_dictionary(structure))
income_estimate = finicityapi.models.report_income_estimate.ReportIncomeEstimate.from_dictionary(dictionary.get('incomeEstimate')) if dictionary.get('incomeEstimate') else None
# Clean out expected properties from dictionary
for key in cls._names.values():
if key in dictionary:
del dictionary[key]
# Return an object of this model
return cls(confidence_type,
net_monthly,
income_estimate,
dictionary)