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from typing import Optional, List
from pydantic import BaseModel, ConfigDict, Field
from pydantic.json_schema import SkipJsonSchema
from generalresearch.models import Source
from generalresearch.models.custom_types import AwareDatetimeISO
from generalresearch.models.thl.profiling.user_question_answer import (
MarketplaceResearchProfileQuestion,
)
from generalresearch.models.thl.user import User
class UserProfileKnowledgeAnswer(BaseModel):
# Returns {id, label, translation} when the prop_type is an item,
# and only {value} if it's a string/text (such as for postalcode)
id: Optional[str] = Field(default=None)
label: Optional[str] = Field(default=None)
translation: Optional[str] = Field(default=None)
value: Optional[str] = Field(default=None)
class UserProfileKnowledge(BaseModel):
property_id: str = Field()
property_label: str = Field()
translation: str = Field()
answer: List[UserProfileKnowledgeAnswer] = Field(default_factory=list)
created: AwareDatetimeISO = Field(
description="When the User submitted this Profiling data"
)
class MarketProfileKnowledge(BaseModel):
"""
This is used solely in API responses, so it is simplified.
"""
source: Source = Field(
max_length=16, description="Marketplace this question is from"
)
question_id: str = Field(examples=["gender", "1843", "gender_plus"])
answer: List[str] = Field(
default_factory=list, examples=[["male"], ["7657644"], ["1"]]
)
created: AwareDatetimeISO = Field(
description="When the User submitted this Profiling data"
)
@classmethod
def from_MarketplaceResearchProfileQuestion(
cls, q: MarketplaceResearchProfileQuestion
):
return cls(
source=q.source,
question_id=q.question_code,
answer=list(q.answer),
created=q.timestamp,
)
class UserInfo(BaseModel):
model_config = ConfigDict()
user: SkipJsonSchema[Optional[User]] = Field(exclude=True, default=None)
user_profile_knowledge: List[UserProfileKnowledge] = Field(default_factory=list)
marketplace_profile_knowledge: List[MarketProfileKnowledge] = Field(
default_factory=list
)
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