from typing import Any, Dict, List, Optional, Union
from enum import Enum
from pydantic import BaseModel, Field
[docs]class ScreeningHitAnalysis(BaseModel):
documents: Optional[str] = None
"""An enum indicating the match type between data provided by user and data checked against an external data source.
`match` indicates that the provided input data was a strong match against external data.
`partial_match` indicates the data approximately matched against external data. For example, "Knope" vs. "Knope-Wyatt" for last name.
`no_match` indicates that Plaid was able to perform a check against an external data source and it did not match the provided input data.
`no_data` indicates that Plaid was unable to find external data to compare against the provided input data.
`no_input` indicates that Plaid was unable to perform a check because no information was provided for this field by the end user."""
dates_of_birth: Optional[str] = None
"""An enum indicating the match type between data provided by user and data checked against an external data source.
`match` indicates that the provided input data was a strong match against external data.
`partial_match` indicates the data approximately matched against external data. For example, "Knope" vs. "Knope-Wyatt" for last name.
`no_match` indicates that Plaid was able to perform a check against an external data source and it did not match the provided input data.
`no_data` indicates that Plaid was unable to find external data to compare against the provided input data.
`no_input` indicates that Plaid was unable to perform a check because no information was provided for this field by the end user."""
locations: Optional[str] = None
"""An enum indicating the match type between data provided by user and data checked against an external data source.
`match` indicates that the provided input data was a strong match against external data.
`partial_match` indicates the data approximately matched against external data. For example, "Knope" vs. "Knope-Wyatt" for last name.
`no_match` indicates that Plaid was able to perform a check against an external data source and it did not match the provided input data.
`no_data` indicates that Plaid was unable to find external data to compare against the provided input data.
`no_input` indicates that Plaid was unable to perform a check because no information was provided for this field by the end user."""
names: Optional[str] = None
"""An enum indicating the match type between data provided by user and data checked against an external data source.
`match` indicates that the provided input data was a strong match against external data.
`partial_match` indicates the data approximately matched against external data. For example, "Knope" vs. "Knope-Wyatt" for last name.
`no_match` indicates that Plaid was able to perform a check against an external data source and it did not match the provided input data.
`no_data` indicates that Plaid was unable to find external data to compare against the provided input data.
`no_input` indicates that Plaid was unable to perform a check because no information was provided for this field by the end user."""
search_terms_version: float
"""The version of the screening's `search_terms` that were compared when the screening hit was added. screening hits are immutable once they have been reviewed. If changes are detected due to updates to the screening's `search_terms`, the associated program, or the list's source data prior to review, the screening hit will be updated to reflect those changes."""
[docs] def json(self, **kwargs: Any) -> str:
"""Return a json string representation of the object. Takes same keyword arguments as pydantic.BaseModel.json"""
kwargs.setdefault("by_alias", True)
return super().json(**kwargs)
[docs] def dict(self, **kwargs: Any) -> Dict[str, Any]:
"""Return a dict representation of the object. Takes same keyword arguments as pydantic.BaseModel.dict"""
kwargs.setdefault("by_alias", True)
return super().dict(**kwargs)
[docs] @classmethod
def parse_obj(cls, data: Any) -> "ScreeningHitAnalysis":
"""Parse a dict into the object. Takes same keyword arguments as pydantic.BaseModel.parse_obj"""
return super().parse_obj(data)
[docs] @classmethod
def parse_raw(cls, b: Union[bytes, str], **kwargs: Any) -> "ScreeningHitAnalysis":
"""Parse a json string into the object. Takes same keyword arguments as pydantic.BaseModel.parse_raw"""
return super().parse_raw(b, **kwargs)