def generate_supervision_violation_response_decision_entry(
person,
**kwargs) -> schema.StateSupervisionViolationResponseDecisionEntry:
args = {
"state_code": _STATE_CODE,
}
args.update(kwargs)
return schema.StateSupervisionViolationResponseDecisionEntry(person=person,
**args)
def generate_test_supervision_violation_response(person_id) -> \
state_schema.StateSupervisionViolationResponse:
instance = state_schema.StateSupervisionViolationResponse(
supervision_violation_response_id=456,
state_code='us_ca',
person_id=person_id,
supervision_violation_response_decisions=[
state_schema.StateSupervisionViolationResponseDecisionEntry(
supervision_violation_response_decision_entry_id=123,
state_code='us_ca',
decision=StateSupervisionViolationResponseDecision.REVOCATION.
value,
decision_raw_text='REV',
revocation_type=StateSupervisionViolationResponseRevocationType
.REINCARCERATION.value,
revocation_type_raw_text='REINC',
person_id=person_id,
)
])
return instance
def build_data_dict(
fake_person_id: int,
fake_supervision_violation_id: int) -> Dict[str, List[Any]]:
"""Builds a data_dict for a basic run of the pipeline."""
fake_person = schema.StatePerson(
state_code="US_XX",
person_id=fake_person_id,
gender=Gender.FEMALE,
birthdate=date(1985, 2, 1),
)
persons_data = [normalized_database_base_dict(fake_person)]
race_1 = schema.StatePersonRace(
person_race_id=111,
state_code="US_XX",
race=Race.ASIAN,
person_id=fake_person_id,
)
race_2 = schema.StatePersonRace(
person_race_id=111,
state_code="US_XX",
race=Race.AMERICAN_INDIAN_ALASKAN_NATIVE,
person_id=fake_person_id,
)
races_data = normalized_database_base_dict_list([race_1, race_2])
ethnicity = schema.StatePersonEthnicity(
person_ethnicity_id=111,
state_code="US_XX",
ethnicity=Ethnicity.NOT_HISPANIC,
person_id=fake_person_id,
)
ethnicity_data = normalized_database_base_dict_list([ethnicity])
violation_type = schema.StateSupervisionViolationTypeEntry(
state_code="US_XX",
violation_type=StateSupervisionViolationType.FELONY,
person_id=fake_person_id,
)
incomplete_response = schema.StateSupervisionViolationResponse(
state_code="US_XX",
supervision_violation_response_id=1234,
response_type=entities.StateSupervisionViolationResponseType.
VIOLATION_REPORT,
response_date=date(2021, 1, 4),
is_draft=False,
person_id=fake_person_id,
)
violation = schema.StateSupervisionViolation(
state_code="US_XX",
supervision_violation_id=fake_supervision_violation_id,
violation_date=date(2021, 1, 1),
is_violent=False,
is_sex_offense=False,
supervision_violation_types=[violation_type],
supervision_violation_responses=[incomplete_response],
person_id=fake_person_id,
)
incomplete_response.supervision_violation_id = fake_supervision_violation_id
violation_type.supervision_violation_id = fake_supervision_violation_id
violation_decision = schema.StateSupervisionViolationResponseDecisionEntry(
state_code="US_XX",
decision=StateSupervisionViolationResponseDecision.
SHOCK_INCARCERATION,
person_id=fake_person_id,
supervision_violation_response_decision_entry_id=234,
supervision_violation_response_id=1234,
)
complete_violation_response = schema.StateSupervisionViolationResponse(
state_code="US_XX",
supervision_violation_response_id=1234,
response_type=entities.StateSupervisionViolationResponseType.
VIOLATION_REPORT,
response_date=date(2021, 1, 4),
is_draft=False,
supervision_violation_response_decisions=[violation_decision],
person_id=fake_person_id,
)
complete_violation_response.supervision_violation_id = (
fake_supervision_violation_id)
violations_data = [normalized_database_base_dict(violation)]
violation_responses_data = [
normalized_database_base_dict(complete_violation_response)
]
violation_types_data = [normalized_database_base_dict(violation_type)]
violation_decisions_data = [
normalized_database_base_dict(violation_decision)
]
state_race_ethnicity_population_count_data = [{
"state_code":
"US_XX",
"race_or_ethnicity":
"ASIAN",
"population_count":
1,
"representation_priority":
1,
}]
data_dict: Dict[str, List[Any]] = {
schema.StatePerson.__tablename__:
persons_data,
schema.StatePersonRace.__tablename__:
races_data,
schema.StatePersonEthnicity.__tablename__:
ethnicity_data,
schema.StateSupervisionViolation.__tablename__:
violations_data,
schema.StateSupervisionViolationResponse.__tablename__:
violation_responses_data,
schema.StateSupervisionViolationTypeEntry.__tablename__:
violation_types_data,
schema.StateSupervisionViolatedConditionEntry.__tablename__: [],
schema.StateSupervisionViolationResponseDecisionEntry.__tablename__:
violation_decisions_data,
schema.StatePersonExternalId.__tablename__: [],
schema.StatePersonAlias.__tablename__: [],
schema.StateAssessment.__tablename__: [],
schema.StateProgramAssignment.__tablename__: [],
schema.StateSentenceGroup.__tablename__: [],
"state_race_ethnicity_population_counts":
state_race_ethnicity_population_count_data,
}
return data_dict