class Config(pydantic.BaseModel):
num_eval_samples: int = pydantic.Schema(..., alias="num_samples")
output_types: Set[OutputType]
quantiles: List[str] # FIXME: validate list elements
class Config:
allow_population_by_alias = True
class Config(pydantic.BaseModel):
num_samples: int = pydantic.Schema(100, alias="num_eval_samples")
output_types: Set[OutputType] = {"quantiles", "mean"}
# FIXME: validate list elements
quantiles: List[str] = ["0.1", "0.5", "0.9"]
class Config:
allow_population_by_alias = True
# store additional fields
extra = "allow"
class MetaData(pydantic.BaseModel):
freq: str = pydantic.Schema(..., alias="time_granularity") # type: ignore
target: Optional[BasicFeatureInfo] = None
feat_static_cat: List[CategoricalFeatureInfo] = []
feat_static_real: List[BasicFeatureInfo] = []
feat_dynamic_real: List[BasicFeatureInfo] = []
feat_dynamic_cat: List[CategoricalFeatureInfo] = []
prediction_length: Optional[int] = None
class Config(pydantic.BaseConfig):
allow_population_by_alias = True
class Record(pydantic.BaseModel):
'''
A Record essentially represents a row in our Airtable table.
'''
# Airtable's unique id for this row, e.g. "recFLEuThPbUkwmsq".
id: str
# The fields of this row. We need to call it "fields_" because
# the attribute "fields" is already used by pydantic.
fields_: Fields = pydantic.Schema(default=..., alias='fields')
# The date the row was created, e.g. '2018-10-15T20:27:20.000Z'.
createdTime: str
class Row(pydantic.BaseModel):
BOROUGH: str
BLOCK: str
LOT: str
ADDRESS: str
ZIP_CODE: str = pydantic.Schema(..., alias="ZIP CODE")
MANAGED_BY: str = pydantic.Schema(..., alias="MANAGED BY")
FACILITY: str
@property
def pad_bbl(self) -> str:
boro = BOROUGH_NUMBERS[self.BOROUGH]
return to_pad_bbl(boro, int(self.BLOCK), int(self.LOT))
@property
def full_address(self) -> str:
city = self.BOROUGH
if city == MANHATTAN:
city = 'NEW YORK'
return f'{self.ADDRESS}\n{city}, NY {self.ZIP_CODE}'
def is_main_management_office(self) -> bool:
return ('DEVELOPMENT MANAGEMENT OFFICE' in self.FACILITY
and 'SATELLITE' not in self.FACILITY)
class EnzoModel(BaseModel):
hierarchy : EnzoGrid = pydantic.Schema(..., **e)
class Config:
title = 'Enzo Schema'
class MainModel(pydantic.BaseModel):
data : datatypes = pydantic.Schema('test.txt', shape = [3,2,4])
class Config:
title = 'New Schema'
class Fields(pydantic.BaseModel):
'''
The fields in a row of our Airtable table. Note that these are
only the fields we care about and control: the Airtable will
likely contain extra fields that matter to users, but that
we don't care about for the purposes of syncing.
The names of the fields are either attributes of our
user model, or they are attributes of related models, which
are named using Django's syntax for lookups that span
relationships [1]:
> To span a relationship, just use the field name of related
> fields across models, separated by double underscores,
> until you get to the field you want.
In some cases, we use pydantic's "alias" feature to ensure
that the Airtable field name is more readable than the
notation we use internally.
[1] https://docs.djangoproject.com/en/2.1/topics/db/queries/
'''
# The primary key of the JustfixUser that the row represents.
pk: int = -1
# The user's first name.
first_name: str = ''
# The user's last name.
last_name: str = ''
# The admin URL where the user info can be viewed/changed.
admin_url: str = ''
# The user's phone number.
phone_number: str = ''
# Whether we can SMS the user.
onboarding_info__can_we_sms: bool = pydantic.Schema(default=False,
alias='can_we_sms')
# The user's lease type.
onboarding_info__lease_type: str = pydantic.Schema(default='',
alias='lease_type')
# When the user's letter of complaint was requested.
letter_request__created_at: Optional[str] = pydantic.Schema(
# Note that it's important to set dates to None/null in Airtable if they don't
# exist, as Airtable will complain that it can't parse the value if we give it
# an empty string.
default=None,
alias='letter_request_date')
# The tenant's full mailing address.
onboarding_info__address_for_mailing: str = pydantic.Schema(
default='', alias='address')
# The tenant's boro-block-lot (BBL) number.
onboarding_info__pad_bbl: str = pydantic.Schema(default='',
alias='pad_bbl')
# A link to the letter of complaint PDF.
letter_request__admin_pdf_url: str = pydantic.Schema(
default='', alias='letter_pdf_url')
# The tenant's landlord's name.
landlord_details__name: str = pydantic.Schema(default='',
alias='landlord_name')
# The tenant's landlord's address.
landlord_details__address: str = pydantic.Schema(default='',
alias='landlord_address')
# Whether or not the user wants us to mail the letter for them.
letter_request__will_we_mail: bool = pydantic.Schema(
default=False, alias='will_we_mail_letter')
@classmethod
def from_user(cls: Type[T], user: JustfixUser) -> T:
'''
Given a user, return the Fields that represent their data.
'''
kwargs: Dict[str, Any] = {}
for field in cls.__fields__.values():
kwargs[field.alias] = get_user_field_for_airtable(user, field)
return cls(**kwargs)
class ApplicationSecret(pydantic.BaseModel):
secret: str = pydantic.Schema('CHANGE-ME',
description='Application Secret')
class LabMember(pydantic.BaseModel):
first: str = pydantic.Schema(..., description='First Name')
last: str = pydantic.Schema(..., description='Last Name')
year: int = pydantic.Schema(1, description='Years in program.')
department: Department = pydantic.Schema('Aero/Astro',
description='Student Department')
