dataio.schemas.bonsai_api package

Submodules

dataio.schemas.bonsai_api.PPF_fact_schemas_samples module

class dataio.schemas.bonsai_api.PPF_fact_schemas_samples.Emissions_samples(*, samples: list[float], time: int, year_emission: int | None = None, location: str, activity: str, activity_unit: str, emission_substance: str, compartment: str, product: str, product_unit: str, value: float, unit: str, flag: str | None = None, elementary_type: str = 'emission')

Bases: FactBaseModel_samples

activity: str

activity_unit: str

compartment: str

elementary_type: str

emission_substance: str

flag: str | None

location: str

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

product: str

product_unit: str

time: int

unit: str

value: float

year_emission: int | None

class dataio.schemas.bonsai_api.PPF_fact_schemas_samples.FinalUses_samples(*, samples: list[float], location: str, product: str, final_user: str, unit: str, value: float, time: int)

Bases: FactBaseModel_samples

final_user: str

location: str

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

product: str

time: int

unit: str

value: float

class dataio.schemas.bonsai_api.PPF_fact_schemas_samples.Imports_samples(*, samples: list[float], location: str, product: str, product_origin: str, unit: str, value: float, time: int)

Bases: FactBaseModel_samples

location: str

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

product: str

product_origin: str

time: int

unit: str

value: float

class dataio.schemas.bonsai_api.PPF_fact_schemas_samples.OutputTotals_samples(*, samples: list[float], location: str, activity: str, output_compartment: str, unit: str, value: float, time: int)

Bases: FactBaseModel_samples

activity: str

location: str

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

output_compartment: str

time: int

unit: str

value: float

class dataio.schemas.bonsai_api.PPF_fact_schemas_samples.PackagingData_samples(*, samples: list[float], location: str, product: str, activity: str, unit: str, value: float, product_destination: str | None = None, associated_product: str | None = None, flag: str | None = None, time: int, product_type: str = 'supply', account_type: str | None = None)

Bases: Supply_samples

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

class dataio.schemas.bonsai_api.PPF_fact_schemas_samples.ProductionVolumes_samples(*, samples: list[float], location: str, product: str, activity: str | None = None, unit: str, value: float, flag: str | None = None, time: int, inventory_time: int | None = None, source: str | None = None, comment: str | None = None, price_type: str | None = None, account_type: str | None = None)

Bases: FactBaseModel_samples

account_type: str | None

activity: str | None

comment: str | None

flag: str | None

inventory_time: int | None

location: str

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

price_type: str | None

product: str

source: str | None

time: int

unit: str

value: float

class dataio.schemas.bonsai_api.PPF_fact_schemas_samples.PropertyOfProducts_samples(*, samples: list[float], location: str | None = None, product: str, value: float, activity: str | None = None, unit: str, description: str | None = None)

Bases: FactBaseModel_samples

activity: str | None

description: str | None

location: str | None

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

product: str

unit: str

value: float

class dataio.schemas.bonsai_api.PPF_fact_schemas_samples.Resource_samples(*, samples: list[float], time: int, year_emission: int | None = None, location: str, activity: str, activity_unit: str, emission_substance: str, compartment: str, product: str, product_unit: str, value: float, unit: str, flag: str | None = None, elementary_type: str = 'emission')

Bases: Emissions_samples

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

class dataio.schemas.bonsai_api.PPF_fact_schemas_samples.SUTAdjustments_samples(*, samples: list[float], location: str, adjustment: str, product: str | None = None, product_origin: str | None = None, final_user: str | None = None, unit: str, value: float, time: int)

Bases: FactBaseModel_samples

adjustment: str

final_user: str | None

location: str

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

product: str | None

product_origin: str | None

time: int

unit: str

value: float

class dataio.schemas.bonsai_api.PPF_fact_schemas_samples.SocialSatellite_samples(*, samples: list[float], location: str, activity: str, social_flow: str, unit: str, value: float, time: int)

Bases: FactBaseModel_samples

activity: str

location: str

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

social_flow: str

time: int

unit: str

value: float

class dataio.schemas.bonsai_api.PPF_fact_schemas_samples.Supply_samples(*, samples: list[float], location: str, product: str, activity: str, unit: str, value: float, product_destination: str | None = None, associated_product: str | None = None, flag: str | None = None, time: int, product_type: str = 'supply', account_type: str | None = None)

Bases: FactBaseModel_samples

account_type: str | None

activity: str

associated_product: str | None

flag: str | None

location: str

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

product: str

product_destination: str | None

product_type: str

time: int

unit: str

value: float

class dataio.schemas.bonsai_api.PPF_fact_schemas_samples.Trade_samples(*, samples: list[float], time: int, product: str, export_location: str, import_location: str, value: float, unit: str, flag: str | None = None, price_type: str | None = None, source: str | None = None, account_type: str | None = None)

Bases: FactBaseModel_samples

account_type: str | None

export_location: str

flag: str | None

import_location: str

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

price_type: str | None

product: str

source: str | None

time: int

unit: str

value: float

class dataio.schemas.bonsai_api.PPF_fact_schemas_samples.TransferCoefficient_samples(*, samples: list[float], location: str | None = None, output: str, input_product: str, activity: str, coefficient_value: float, unit: str, flag: str | None = None, time: int | None = None, transfer_type: str)

Bases: FactBaseModel_samples

activity: str

coefficient_value: float

flag: str | None

input_product: str

location: str | None

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

output: str

time: int | None

transfer_type: str

unit: str

class dataio.schemas.bonsai_api.PPF_fact_schemas_samples.Use_samples(*, samples: list[float], location: str, product: str, activity: str, unit: str, value: float, associated_product: str | None = None, flag: str | None = None, time: int, product_origin: str | None = None, product_type: str = 'use', account_type: str | None = None)

Bases: FactBaseModel_samples

account_type: str | None

activity: str

associated_product: str | None

flag: str | None

location: str

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

product: str

product_origin: str | None

product_type: str

time: int

unit: str

value: float

class dataio.schemas.bonsai_api.PPF_fact_schemas_samples.Valuation_samples(*, samples: list[float], location: str, product: str, valuation: str, unit: str, value: float, time: int)

Bases: FactBaseModel_samples

location: str

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

product: str

time: int

unit: str

valuation: str

value: float

class dataio.schemas.bonsai_api.PPF_fact_schemas_samples.ValueAdded_samples(*, samples: list[float], location: str, activity: str, value_added_component: str, unit: str, value: float, time: int)

Bases: FactBaseModel_samples

activity: str

location: str

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

time: int

unit: str

value: float

value_added_component: str

class dataio.schemas.bonsai_api.PPF_fact_schemas_samples.WasteSupply_samples(*, samples: list[float], location: str, product: str, activity: str, unit: str, value: float, product_destination: str | None = None, associated_product: str | None = None, flag: str | None = None, time: int, product_type: str = 'supply', account_type: str | None = None, waste_fraction: bool)

Bases: Supply_samples

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

waste_fraction: bool

class dataio.schemas.bonsai_api.PPF_fact_schemas_samples.WasteUse_samples(*, samples: list[float], location: str, product: str, activity: str, unit: str, value: float, associated_product: str | None = None, flag: str | None = None, time: int, product_origin: str | None = None, product_type: str = 'use', account_type: str | None = None, waste_fraction: bool)

Bases: Use_samples

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

waste_fraction: bool

dataio.schemas.bonsai_api.PPF_fact_schemas_uncertainty module

class dataio.schemas.bonsai_api.PPF_fact_schemas_uncertainty.Emissions_uncertainty(*, variance: float | None = None, standard_deviation: float | None = None, confidence_interval_95min: float | None = None, confidence_interval_95max: float | None = None, confidence_interval_68min: float | None = None, confidence_interval_68max: float | None = None, distribution: str | None = None, min_value: float | None = None, max_value: float | None = None, uncertainty_comment: str | None = None, time: int, year_emission: int | None = None, location: str, activity: str, activity_unit: str, emission_substance: str, compartment: str, product: str, product_unit: str, value: float, unit: str, flag: str | None = None, elementary_type: str = 'emission')

Bases: FactBaseModel_uncertainty

activity: str

activity_unit: str

compartment: str

elementary_type: str

emission_substance: str

flag: str | None

location: str

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

product: str

product_unit: str

time: int

unit: str

value: float

year_emission: int | None

class dataio.schemas.bonsai_api.PPF_fact_schemas_uncertainty.FinalUses_uncertainty(*, variance: float | None = None, standard_deviation: float | None = None, confidence_interval_95min: float | None = None, confidence_interval_95max: float | None = None, confidence_interval_68min: float | None = None, confidence_interval_68max: float | None = None, distribution: str | None = None, min_value: float | None = None, max_value: float | None = None, uncertainty_comment: str | None = None, location: str, product: str, final_user: str, unit: str, value: float, time: int)

Bases: FactBaseModel_uncertainty

final_user: str

location: str

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

product: str

time: int

unit: str

value: float

class dataio.schemas.bonsai_api.PPF_fact_schemas_uncertainty.Imports_uncertainty(*, variance: float | None = None, standard_deviation: float | None = None, confidence_interval_95min: float | None = None, confidence_interval_95max: float | None = None, confidence_interval_68min: float | None = None, confidence_interval_68max: float | None = None, distribution: str | None = None, min_value: float | None = None, max_value: float | None = None, uncertainty_comment: str | None = None, location: str, product: str, product_origin: str, unit: str, value: float, time: int)

Bases: FactBaseModel_uncertainty

location: str

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

product: str

product_origin: str

time: int

unit: str

value: float

class dataio.schemas.bonsai_api.PPF_fact_schemas_uncertainty.OutputTotals_uncertainty(*, variance: float | None = None, standard_deviation: float | None = None, confidence_interval_95min: float | None = None, confidence_interval_95max: float | None = None, confidence_interval_68min: float | None = None, confidence_interval_68max: float | None = None, distribution: str | None = None, min_value: float | None = None, max_value: float | None = None, uncertainty_comment: str | None = None, location: str, activity: str, output_compartment: str, unit: str, value: float, time: int)

Bases: FactBaseModel_uncertainty

activity: str

location: str

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

output_compartment: str

time: int

unit: str

value: float

class dataio.schemas.bonsai_api.PPF_fact_schemas_uncertainty.PackagingData_uncertainty(*, variance: float | None = None, standard_deviation: float | None = None, confidence_interval_95min: float | None = None, confidence_interval_95max: float | None = None, confidence_interval_68min: float | None = None, confidence_interval_68max: float | None = None, distribution: str | None = None, min_value: float | None = None, max_value: float | None = None, uncertainty_comment: str | None = None, location: str, product: str, activity: str, unit: str, value: float, product_destination: str | None = None, associated_product: str | None = None, flag: str | None = None, time: int, product_type: str = 'supply', account_type: str | None = None)

Bases: Supply_uncertainty

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

class dataio.schemas.bonsai_api.PPF_fact_schemas_uncertainty.ProductionVolumes_uncertainty(*, variance: float | None = None, standard_deviation: float | None = None, confidence_interval_95min: float | None = None, confidence_interval_95max: float | None = None, confidence_interval_68min: float | None = None, confidence_interval_68max: float | None = None, distribution: str | None = None, min_value: float | None = None, max_value: float | None = None, uncertainty_comment: str | None = None, location: str, product: str, activity: str | None = None, unit: str, value: float, flag: str | None = None, time: int, inventory_time: int | None = None, source: str | None = None, comment: str | None = None, price_type: str | None = None, account_type: str | None = None)

Bases: FactBaseModel_uncertainty

account_type: str | None

activity: str | None

comment: str | None

flag: str | None

inventory_time: int | None

location: str

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

price_type: str | None

product: str

source: str | None

time: int

unit: str

value: float

class dataio.schemas.bonsai_api.PPF_fact_schemas_uncertainty.PropertyOfProducts_uncertainty(*, variance: float | None = None, standard_deviation: float | None = None, confidence_interval_95min: float | None = None, confidence_interval_95max: float | None = None, confidence_interval_68min: float | None = None, confidence_interval_68max: float | None = None, distribution: str | None = None, min_value: float | None = None, max_value: float | None = None, uncertainty_comment: str | None = None, location: str | None = None, product: str, value: float, activity: str | None = None, unit: str, description: str | None = None)

Bases: FactBaseModel_uncertainty

activity: str | None

description: str | None

location: str | None

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

product: str

unit: str

value: float

class dataio.schemas.bonsai_api.PPF_fact_schemas_uncertainty.Resource_uncertainty(*, variance: float | None = None, standard_deviation: float | None = None, confidence_interval_95min: float | None = None, confidence_interval_95max: float | None = None, confidence_interval_68min: float | None = None, confidence_interval_68max: float | None = None, distribution: str | None = None, min_value: float | None = None, max_value: float | None = None, uncertainty_comment: str | None = None, time: int, year_emission: int | None = None, location: str, activity: str, activity_unit: str, emission_substance: str, compartment: str, product: str, product_unit: str, value: float, unit: str, flag: str | None = None, elementary_type: str = 'emission')

Bases: Emissions_uncertainty

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

class dataio.schemas.bonsai_api.PPF_fact_schemas_uncertainty.SUTAdjustments_uncertainty(*, variance: float | None = None, standard_deviation: float | None = None, confidence_interval_95min: float | None = None, confidence_interval_95max: float | None = None, confidence_interval_68min: float | None = None, confidence_interval_68max: float | None = None, distribution: str | None = None, min_value: float | None = None, max_value: float | None = None, uncertainty_comment: str | None = None, location: str, adjustment: str, product: str | None = None, product_origin: str | None = None, final_user: str | None = None, unit: str, value: float, time: int)

Bases: FactBaseModel_uncertainty

adjustment: str

final_user: str | None

location: str

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

product: str | None

product_origin: str | None

time: int

unit: str

value: float

class dataio.schemas.bonsai_api.PPF_fact_schemas_uncertainty.SocialSatellite_uncertainty(*, variance: float | None = None, standard_deviation: float | None = None, confidence_interval_95min: float | None = None, confidence_interval_95max: float | None = None, confidence_interval_68min: float | None = None, confidence_interval_68max: float | None = None, distribution: str | None = None, min_value: float | None = None, max_value: float | None = None, uncertainty_comment: str | None = None, location: str, activity: str, social_flow: str, unit: str, value: float, time: int)

Bases: FactBaseModel_uncertainty

activity: str

location: str

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

social_flow: str

time: int

unit: str

value: float

class dataio.schemas.bonsai_api.PPF_fact_schemas_uncertainty.Supply_uncertainty(*, variance: float | None = None, standard_deviation: float | None = None, confidence_interval_95min: float | None = None, confidence_interval_95max: float | None = None, confidence_interval_68min: float | None = None, confidence_interval_68max: float | None = None, distribution: str | None = None, min_value: float | None = None, max_value: float | None = None, uncertainty_comment: str | None = None, location: str, product: str, activity: str, unit: str, value: float, product_destination: str | None = None, associated_product: str | None = None, flag: str | None = None, time: int, product_type: str = 'supply', account_type: str | None = None)

Bases: FactBaseModel_uncertainty

account_type: str | None

activity: str

associated_product: str | None

flag: str | None

location: str

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

product: str

product_destination: str | None

product_type: str

time: int

unit: str

value: float

class dataio.schemas.bonsai_api.PPF_fact_schemas_uncertainty.Trade_uncertainty(*, variance: float | None = None, standard_deviation: float | None = None, confidence_interval_95min: float | None = None, confidence_interval_95max: float | None = None, confidence_interval_68min: float | None = None, confidence_interval_68max: float | None = None, distribution: str | None = None, min_value: float | None = None, max_value: float | None = None, uncertainty_comment: str | None = None, time: int, product: str, export_location: str, import_location: str, value: float, unit: str, flag: str | None = None, price_type: str | None = None, source: str | None = None, account_type: str | None = None)

Bases: FactBaseModel_uncertainty

account_type: str | None

export_location: str

flag: str | None

import_location: str

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

price_type: str | None

product: str

source: str | None

time: int

unit: str

value: float

class dataio.schemas.bonsai_api.PPF_fact_schemas_uncertainty.TransferCoefficient_uncertainty(*, variance: float | None = None, standard_deviation: float | None = None, confidence_interval_95min: float | None = None, confidence_interval_95max: float | None = None, confidence_interval_68min: float | None = None, confidence_interval_68max: float | None = None, distribution: str | None = None, min_value: float | None = None, max_value: float | None = None, uncertainty_comment: str | None = None, location: str | None = None, output_product: str, input_product: str, activity: str, coefficient_value: float, unit: str, flag: str | None = None, time: int | None = None, transfer_type: str)

Bases: FactBaseModel_uncertainty

activity: str

coefficient_value: float

flag: str | None

input_product: str

location: str | None

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

output_product: str

time: int | None

transfer_type: str

unit: str

class dataio.schemas.bonsai_api.PPF_fact_schemas_uncertainty.Use_uncertainty(*, variance: float | None = None, standard_deviation: float | None = None, confidence_interval_95min: float | None = None, confidence_interval_95max: float | None = None, confidence_interval_68min: float | None = None, confidence_interval_68max: float | None = None, distribution: str | None = None, min_value: float | None = None, max_value: float | None = None, uncertainty_comment: str | None = None, location: str, product: str, activity: str, unit: str, value: float, associated_product: str | None = None, flag: str | None = None, time: int, product_origin: str | None = None, product_type: str = 'use', account_type: str | None = None)

Bases: FactBaseModel_uncertainty

account_type: str | None

activity: str

associated_product: str | None

flag: str | None

location: str

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

product: str

product_origin: str | None

product_type: str

time: int

unit: str

value: float

class dataio.schemas.bonsai_api.PPF_fact_schemas_uncertainty.Valuation_uncertainty(*, variance: float | None = None, standard_deviation: float | None = None, confidence_interval_95min: float | None = None, confidence_interval_95max: float | None = None, confidence_interval_68min: float | None = None, confidence_interval_68max: float | None = None, distribution: str | None = None, min_value: float | None = None, max_value: float | None = None, uncertainty_comment: str | None = None, location: str, product: str, valuation: str, unit: str, value: float, time: int)

Bases: FactBaseModel_uncertainty

location: str

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

product: str

time: int

unit: str

valuation: str

value: float

class dataio.schemas.bonsai_api.PPF_fact_schemas_uncertainty.ValueAdded_uncertainty(*, variance: float | None = None, standard_deviation: float | None = None, confidence_interval_95min: float | None = None, confidence_interval_95max: float | None = None, confidence_interval_68min: float | None = None, confidence_interval_68max: float | None = None, distribution: str | None = None, min_value: float | None = None, max_value: float | None = None, uncertainty_comment: str | None = None, location: str, activity: str, value_added_component: str, unit: str, value: float, time: int)

Bases: FactBaseModel_uncertainty

activity: str

location: str

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

time: int

unit: str

value: float

value_added_component: str

class dataio.schemas.bonsai_api.PPF_fact_schemas_uncertainty.WasteSupply_uncertainty(*, variance: float | None = None, standard_deviation: float | None = None, confidence_interval_95min: float | None = None, confidence_interval_95max: float | None = None, confidence_interval_68min: float | None = None, confidence_interval_68max: float | None = None, distribution: str | None = None, min_value: float | None = None, max_value: float | None = None, uncertainty_comment: str | None = None, location: str, product: str, activity: str, unit: str, value: float, product_destination: str | None = None, associated_product: str | None = None, flag: str | None = None, time: int, product_type: str = 'supply', account_type: str | None = None, waste_fraction: bool)

Bases: Supply_uncertainty

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

waste_fraction: bool

class dataio.schemas.bonsai_api.PPF_fact_schemas_uncertainty.WasteUse_uncertainty(*, variance: float | None = None, standard_deviation: float | None = None, confidence_interval_95min: float | None = None, confidence_interval_95max: float | None = None, confidence_interval_68min: float | None = None, confidence_interval_68max: float | None = None, distribution: str | None = None, min_value: float | None = None, max_value: float | None = None, uncertainty_comment: str | None = None, location: str, product: str, activity: str, unit: str, value: float, associated_product: str | None = None, flag: str | None = None, time: int, product_origin: str | None = None, product_type: str = 'use', account_type: str | None = None, waste_fraction: bool)

Bases: Use_uncertainty

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

waste_fraction: bool

dataio.schemas.bonsai_api.admin module

class dataio.schemas.bonsai_api.admin.DataResource(name: str, schema_name: str | BonsaiBaseModel, location: str | Path | None = None, task_name: str | None = None, stage: str | None = None, data_flow_direction: str | None = None, data_version: str | float | None = None, code_version: str | float | None = None, comment: str | None = None, last_update: datetime | None = None, created_by: str | None = None, license: str | None = None, license_url: str | None = None, dag_run_id: str | None = None, url: str | None = None, root_location: str | Path | None = None, api_endpoint: str | None = None, id: UUID | None = None)

Bases: BonsaiBaseModel

api_endpoint: str | None

append_comment(comment: str)

code_version: str | None

comment: str | None

created_by: str | None

dag_run_id: str | None

data_flow_direction: str | None

data_version: str | None

id: UUID | None

last_update: datetime

license: str | None

license_url: str | None

property location: str

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_post_init(context: Any, /) → None

This function is meant to behave like a BaseModel method to initialise private attributes.

It takes context as an argument since that’s what pydantic-core passes when calling it.

Parameters:

• self – The BaseModel instance.

• context – The context.

name: str

names

alias of Names

schema_name: str

stage: str | None

task_name: str | None

to_pandas() → DataFrame

Converts instances of BaseToolModel within BaseTableClass to a pandas DataFrame.

Returns:

DataFrame containing data from instances of BaseToolModel.

Return type:

pandas.DataFrame

url: str | None

dataio.schemas.bonsai_api.base_models module

class dataio.schemas.bonsai_api.base_models.CorrespondenceModel(*, created_by: str | None = None, create_time: ~datetime.datetime = <factory>)

Bases: BonsaiBaseModel

create_time: datetime

created_by: str | None

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

class dataio.schemas.bonsai_api.base_models.DimensionModel(*, code: str | None = None, position: int | None = None, created_by: str | None = None)

Bases: BonsaiBaseModel

classmethod check_code_names(v, field)

code: str | None

created_by: str | None

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

position: int | None

class dataio.schemas.bonsai_api.base_models.FactBaseModel_samples(*, samples: list[float])

Bases: BonsaiBaseModel

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

samples: list[float]

class dataio.schemas.bonsai_api.base_models.FactBaseModel_uncertainty(*, variance: float | None = None, standard_deviation: float | None = None, confidence_interval_95min: float | None = None, confidence_interval_95max: float | None = None, confidence_interval_68min: float | None = None, confidence_interval_68max: float | None = None, distribution: str | None = None, min_value: float | None = None, max_value: float | None = None, uncertainty_comment: str | None = None)

Bases: BonsaiBaseModel

confidence_interval_68max: float | None

confidence_interval_68min: float | None

confidence_interval_95max: float | None

confidence_interval_95min: float | None

distribution: str | None

max_value: float | None

min_value: float | None

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

standard_deviation: float | None

uncertainty_comment: str | None

variance: float | None

class dataio.schemas.bonsai_api.base_models.MatrixModel

Bases: object

column_schema: FactBaseModel_uncertainty

row_schema: FactBaseModel_uncertainty

dataio.schemas.bonsai_api.correspondences module

class dataio.schemas.bonsai_api.correspondences.ActivityTypeCorrespondence(*, created_by: str | None = None, create_time: ~datetime.datetime = <factory>, description: str | None = None, comment: str | None = None)

Bases: CorrespondenceModel

comment: str | None

description: str | None

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

class dataio.schemas.bonsai_api.correspondences.FlowObjectCorrespondence(*, created_by: str | None = None, create_time: ~datetime.datetime = <factory>, description: str | None = None, comment: str | None = None)

Bases: CorrespondenceModel

comment: str | None

description: str | None

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

class dataio.schemas.bonsai_api.correspondences.LocationCorrespondence(*, created_by: str | None = None, create_time: ~datetime.datetime = <factory>, description: str | None = None, comment: str | None = None)

Bases: CorrespondenceModel

comment: str | None

description: str | None

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

class dataio.schemas.bonsai_api.correspondences.ProductCorrespondence(*, created_by: str | None = None, create_time: ~datetime.datetime = <factory>, external_name: ~typing.Annotated[str, ~annotated_types.MaxLen(max_length=200)], external_description: str | None = None, base_name: ~dataio.schemas.bonsai_api.dims.FlowObject | None = None)

Bases: CorrespondenceModel

base_name: FlowObject | None

external_description: str | None

external_name: str

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

dataio.schemas.bonsai_api.dims module

class dataio.schemas.bonsai_api.dims.ActivityType(*, code: str, position: int | None = None, created_by: str | None = None, parent_code: str | None = None, level: str | None = None, description: str | None = None, comment: str | None = None)

Bases: ClassificationNode

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

class dataio.schemas.bonsai_api.dims.Calendar(*, code: str | None = None, position: int | None = None, created_by: str | None = None, description: str)

Bases: DimensionModel

description: str

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

class dataio.schemas.bonsai_api.dims.ChemicalCompound(*, code: str, position: int | None = None, created_by: str | None = None, name: str, description: str | None = None, comment: str | None = None)

Bases: DimensionModel

code: str

comment: str | None

description: str | None

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

name: str

names

alias of Names

class dataio.schemas.bonsai_api.dims.ClassificationNode(*, code: str, position: int | None = None, created_by: str | None = None, parent_code: str | None = None, level: str | None = None, description: str | None = None, comment: str | None = None)

Bases: DimensionModel

code: str

comment: str | None

description: str | None

level: str | None

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

parent_code: str | None

class dataio.schemas.bonsai_api.dims.Compartment(*, code: str, position: int | None = None, created_by: str | None = None, name: str, description: str | None = None, comment: str | None = None)

Bases: DimensionModel

code: str

comment: str | None

description: str | None

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

name: str

names

alias of Names

class dataio.schemas.bonsai_api.dims.DataQuality(*, code: str, position: int | None = None, created_by: str | None = None, name: str, description: str | None = None, comment: str | None = None)

Bases: DimensionModel

code: str

comment: str | None

description: str | None

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

name: str

names

alias of Names

class dataio.schemas.bonsai_api.dims.ExternalDimensionTables(*, code: str | None = None, position: int | None = None, created_by: str | None = None, description: str, comment: str | None = None, urn: str | None = None)

Bases: DimensionModel

comment: str | None

description: str

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

urn: str | None

class dataio.schemas.bonsai_api.dims.FlowObject(*, code: str, position: int | None = None, created_by: str | None = None, parent_code: str | None = None, level: str | None = None, description: str | None = None, comment: str | None = None)

Bases: ClassificationNode

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

class dataio.schemas.bonsai_api.dims.LCIA(*, code: str, position: int | None = None, created_by: str | None = None, name: str, description: str | None = None, comment: str | None = None)

Bases: DimensionModel

code: str

comment: str | None

description: str | None

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

name: str

names

alias of Names

class dataio.schemas.bonsai_api.dims.Level(*, code: str, position: int | None = None, created_by: str | None = None, name: str, description: str | None = None, comment: str | None = None)

Bases: DimensionModel

code: str

comment: str | None

description: str | None

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

name: str

names

alias of Names

class dataio.schemas.bonsai_api.dims.Location(*, code: str, position: int | None = None, created_by: str | None = None, parent_code: str | None = None, level: str | None = None, description: str | None = None, comment: str | None = None)

Bases: ClassificationNode

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

class dataio.schemas.bonsai_api.dims.Market(*, code: str, position: int | None = None, created_by: str | None = None, parent_code: str | None = None, level: str | None = None, description: str | None = None, comment: str | None = None)

Bases: ClassificationNode

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

class dataio.schemas.bonsai_api.dims.UncertaintyDistribution(*, code: str, position: int | None = None, created_by: str | None = None, name: str, description: str | None = None, comment: str | None = None)

Bases: DimensionModel

code: str

comment: str | None

description: str | None

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

name: str

names

alias of Names

class dataio.schemas.bonsai_api.dims.Unit(*, code: str | None = None, position: int | None = None, created_by: str | None = None, scientific_notation: Annotated[str, MaxLen(max_length=50)], name: Annotated[str | None, MaxLen(max_length=50)] = None, description: str | None = None, unit_dimension: str)

Bases: DimensionModel

description: str | None

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

name: str | None

names

alias of Names

scientific_notation: str

unit_dimension: str

class dataio.schemas.bonsai_api.dims.UnitConversion(*, code: str | None = None, position: int | None = None, created_by: str | None = None, unit: str, reference_unit: str, conversion_factor: float)

Bases: DimensionModel

conversion_factor: float

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

reference_unit: str

unit: str

class dataio.schemas.bonsai_api.dims.Year(*, code: str | None = None, position: int | None = None, created_by: str | None = None, name: str, calendar: str)

Bases: DimensionModel

calendar: str

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

name: str

names

alias of Names

dataio.schemas.bonsai_api.external_schemas module

class dataio.schemas.bonsai_api.external_schemas.ADBMonetaryIOT(*, variance: float | None = None, standard_deviation: float | None = None, confidence_interval_95min: float | None = None, confidence_interval_95max: float | None = None, confidence_interval_68min: float | None = None, confidence_interval_68max: float | None = None, distribution: str | None = None, min_value: float | None = None, max_value: float | None = None, uncertainty_comment: str | None = None, location: str, time: int, unit: str, value: float, comment: str | None = None, flag: str | None = None, supplier_name: str, supplier_code: str, user_name: str, user_code: str, price_type: str = 'current prices', money_unit: str | None = None, diagonal: bool | None = None)

Bases: baseExternalSchemas

diagonal: bool | None

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

money_unit: str | None

names

alias of Names

price_type: str

supplier_code: str

supplier_name: str

user_code: str

user_name: str

class dataio.schemas.bonsai_api.external_schemas.AfricanMonetarySUT(*, variance: float | None = None, standard_deviation: float | None = None, confidence_interval_95min: float | None = None, confidence_interval_95max: float | None = None, confidence_interval_68min: float | None = None, confidence_interval_68max: float | None = None, distribution: str | None = None, min_value: float | None = None, max_value: float | None = None, uncertainty_comment: str | None = None, location: str, time: int, unit: str, value: float, comment: str | None = None, flag: str | None = None, table_type: str, product_code: str, product_name: str, activity_code: str, activity_name: str, price_type: str = 'current prices', consumer_price: bool = False, money_unit: str | None = None, diagonal: bool | None = None)

Bases: ExternalMonetarySUT

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

class dataio.schemas.bonsai_api.external_schemas.AustralianMonetarySUT(*, variance: float | None = None, standard_deviation: float | None = None, confidence_interval_95min: float | None = None, confidence_interval_95max: float | None = None, confidence_interval_68min: float | None = None, confidence_interval_68max: float | None = None, distribution: str | None = None, min_value: float | None = None, max_value: float | None = None, uncertainty_comment: str | None = None, location: str, time: int, unit: str, value: float, comment: str | None = None, flag: str | None = None, table_type: str, product_code: str, product_name: str, activity_code: str, activity_name: str, price_type: str = 'current prices', consumer_price: bool = False, money_unit: str | None = None, diagonal: bool | None = None)

Bases: ExternalMonetarySUT

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

class dataio.schemas.bonsai_api.external_schemas.BACITrade(*, variance: float | None = None, standard_deviation: float | None = None, confidence_interval_95min: float | None = None, confidence_interval_95max: float | None = None, confidence_interval_68min: float | None = None, confidence_interval_68max: float | None = None, distribution: str | None = None, min_value: float | None = None, max_value: float | None = None, uncertainty_comment: str | None = None, time: int, product: str, export_location: str, import_location: str, value: float, unit: str, flag: str | None = None)

Bases: FactBaseModel_uncertainty

export_location: str

flag: str | None

import_location: str

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

product: str

time: int

unit: str

value: float

class dataio.schemas.bonsai_api.external_schemas.BrokenYearMonetarySUT(*, variance: float | None = None, standard_deviation: float | None = None, confidence_interval_95min: float | None = None, confidence_interval_95max: float | None = None, confidence_interval_68min: float | None = None, confidence_interval_68max: float | None = None, distribution: str | None = None, min_value: float | None = None, max_value: float | None = None, uncertainty_comment: str | None = None, location: str, time: date, unit: str, value: float, comment: str | None = None, flag: str | None = None, table_type: str, product_code: str, product_name: str, activity_code: str, activity_name: str, price_type: str = 'current prices', consumer_price: bool = False, money_unit: str | None = None, diagonal: bool | None = None)

Bases: ExternalMonetarySUT

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

time: date

class dataio.schemas.bonsai_api.external_schemas.ComexTrade(*, variance: float | None = None, standard_deviation: float | None = None, confidence_interval_95min: float | None = None, confidence_interval_95max: float | None = None, confidence_interval_68min: float | None = None, confidence_interval_68max: float | None = None, distribution: str | None = None, min_value: float | None = None, max_value: float | None = None, uncertainty_comment: str | None = None, time: int, product: str, activity: str, export_location: str, import_location: str, value: float, unit: str, transport_mode: str | None = None, country_active_transport_mode: str | None = None, container: str | None = None, flag: str | None = None)

Bases: FactBaseModel_uncertainty

activity: str

container: str | None

country_active_transport_mode: str | None

export_location: str

flag: str | None

import_location: str

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

product: str

time: int

transport_mode: str | None

unit: str

value: float

class dataio.schemas.bonsai_api.external_schemas.EgyptianMonetarySUT(*, variance: float | None = None, standard_deviation: float | None = None, confidence_interval_95min: float | None = None, confidence_interval_95max: float | None = None, confidence_interval_68min: float | None = None, confidence_interval_68max: float | None = None, distribution: str | None = None, min_value: float | None = None, max_value: float | None = None, uncertainty_comment: str | None = None, location: str, time: date, unit: str, value: float, comment: str | None = None, flag: str | None = None, table_type: str, product_code: str, product_name: str, activity_code: str, activity_name: str, price_type: str = 'current prices', consumer_price: bool = False, money_unit: str | None = None, diagonal: bool | None = None)

Bases: BrokenYearMonetarySUT

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

class dataio.schemas.bonsai_api.external_schemas.EuropeanMonetarySUT(*, variance: float | None = None, standard_deviation: float | None = None, confidence_interval_95min: float | None = None, confidence_interval_95max: float | None = None, confidence_interval_68min: float | None = None, confidence_interval_68max: float | None = None, distribution: str | None = None, min_value: float | None = None, max_value: float | None = None, uncertainty_comment: str | None = None, location: str, time: int, unit: str, value: float, comment: str | None = None, flag: str | None = None, table_type: str, product_code: str, product_name: str, activity_code: str, activity_name: str, price_type: str = 'current prices', consumer_price: bool = False, money_unit: str | None = None, diagonal: bool | None = None)

Bases: ExternalMonetarySUT

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

class dataio.schemas.bonsai_api.external_schemas.ExternalMonetarySUT(*, variance: float | None = None, standard_deviation: float | None = None, confidence_interval_95min: float | None = None, confidence_interval_95max: float | None = None, confidence_interval_68min: float | None = None, confidence_interval_68max: float | None = None, distribution: str | None = None, min_value: float | None = None, max_value: float | None = None, uncertainty_comment: str | None = None, location: str, time: int, unit: str, value: float, comment: str | None = None, flag: str | None = None, table_type: str, product_code: str, product_name: str, activity_code: str, activity_name: str, price_type: str = 'current prices', consumer_price: bool = False, money_unit: str | None = None, diagonal: bool | None = None)

Bases: baseExternalSchemas

activity_code: str

activity_name: str

consumer_price: bool

diagonal: bool | None

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

money_unit: str | None

names

alias of Names

price_type: str

product_code: str

product_name: str

table_type: str

class dataio.schemas.bonsai_api.external_schemas.FAOstat(*, variance: float | None = None, standard_deviation: float | None = None, confidence_interval_95min: float | None = None, confidence_interval_95max: float | None = None, confidence_interval_68min: float | None = None, confidence_interval_68max: float | None = None, distribution: str | None = None, min_value: float | None = None, max_value: float | None = None, uncertainty_comment: str | None = None, product_name: str, product: str, fao_element: str, location: str, time: int, value: float, unit: str, flag: str | None = None)

Bases: FactBaseModel_uncertainty

fao_element: str

flag: str | None

location: str

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

product: str

product_name: str

time: int

unit: str

value: float

class dataio.schemas.bonsai_api.external_schemas.FAOtrade(*, variance: float | None = None, standard_deviation: float | None = None, confidence_interval_95min: float | None = None, confidence_interval_95max: float | None = None, confidence_interval_68min: float | None = None, confidence_interval_68max: float | None = None, distribution: str | None = None, min_value: float | None = None, max_value: float | None = None, uncertainty_comment: str | None = None, product_name: str, product: str, export_location: str, import_location: str, time: int, value: float, unit: str, flag: str | None = None)

Bases: FactBaseModel_uncertainty

export_location: str

flag: str | None

import_location: str

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

product: str

product_name: str

time: int

unit: str

value: float

class dataio.schemas.bonsai_api.external_schemas.IndianMonetarySUT(*, variance: float | None = None, standard_deviation: float | None = None, confidence_interval_95min: float | None = None, confidence_interval_95max: float | None = None, confidence_interval_68min: float | None = None, confidence_interval_68max: float | None = None, distribution: str | None = None, min_value: float | None = None, max_value: float | None = None, uncertainty_comment: str | None = None, location: str, time: date, unit: str, value: float, comment: str | None = None, flag: str | None = None, table_type: str, product_code: str, product_name: str, activity_code: str, activity_name: str, price_type: str = 'current prices', consumer_price: bool = False, money_unit: str | None = None, diagonal: bool | None = None)

Bases: BrokenYearMonetarySUT

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

class dataio.schemas.bonsai_api.external_schemas.IndustrialCommodityStatistic(*, variance: float | None = None, standard_deviation: float | None = None, confidence_interval_95min: float | None = None, confidence_interval_95max: float | None = None, confidence_interval_68min: float | None = None, confidence_interval_68max: float | None = None, distribution: str | None = None, min_value: float | None = None, max_value: float | None = None, uncertainty_comment: str | None = None, location: str, product: str, activity: str | None = None, unit: str, value: float, flag: str | None = None, time: int, inventory_time: int | None = None, source: str | None = None, comment: str | None = None, price_type: str | None = None, account_type: str | None = None)

Bases: ProductionVolumes_uncertainty

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

class dataio.schemas.bonsai_api.external_schemas.InternationalMonetarySUT(*, variance: float | None = None, standard_deviation: float | None = None, confidence_interval_95min: float | None = None, confidence_interval_95max: float | None = None, confidence_interval_68min: float | None = None, confidence_interval_68max: float | None = None, distribution: str | None = None, min_value: float | None = None, max_value: float | None = None, uncertainty_comment: str | None = None, location: str, time: int, unit: str, value: float, comment: str | None = None, flag: str | None = None, table_type: str, product_code: str, product_name: str, activity_code: str, activity_name: str, price_type: str = 'current prices', consumer_price: bool = False, money_unit: str | None = None, diagonal: bool | None = None)

Bases: ExternalMonetarySUT

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

class dataio.schemas.bonsai_api.external_schemas.JapanMonetarySUT(*, variance: float | None = None, standard_deviation: float | None = None, confidence_interval_95min: float | None = None, confidence_interval_95max: float | None = None, confidence_interval_68min: float | None = None, confidence_interval_68max: float | None = None, distribution: str | None = None, min_value: float | None = None, max_value: float | None = None, uncertainty_comment: str | None = None, location: str, time: date, unit: str, value: float, comment: str | None = None, flag: str | None = None, table_type: str, product_code: str, product_name: str, activity_code: str, activity_name: str, price_type: str = 'current prices', consumer_price: bool = False, money_unit: str | None = None, diagonal: bool | None = None)

Bases: BrokenYearMonetarySUT

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

class dataio.schemas.bonsai_api.external_schemas.NACEMonetarySUT(*, variance: float | None = None, standard_deviation: float | None = None, confidence_interval_95min: float | None = None, confidence_interval_95max: float | None = None, confidence_interval_68min: float | None = None, confidence_interval_68max: float | None = None, distribution: str | None = None, min_value: float | None = None, max_value: float | None = None, uncertainty_comment: str | None = None, location: str, time: int, unit: str, value: float, comment: str | None = None, flag: str | None = None, table_type: str, product_code: str, product_name: str, activity_code: str, activity_name: str, price_type: str = 'current prices', consumer_price: bool = False, money_unit: str | None = None, diagonal: bool | None = None)

Bases: ExternalMonetarySUT

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

class dataio.schemas.bonsai_api.external_schemas.OECDMonetarySUT(*, variance: float | None = None, standard_deviation: float | None = None, confidence_interval_95min: float | None = None, confidence_interval_95max: float | None = None, confidence_interval_68min: float | None = None, confidence_interval_68max: float | None = None, distribution: str | None = None, min_value: float | None = None, max_value: float | None = None, uncertainty_comment: str | None = None, location: str, time: int, unit: str, value: float, comment: str | None = None, flag: str | None = None, table_type: str, product_code: str, product_name: str, activity_code: str, activity_name: str, price_type: str = 'current prices', consumer_price: bool = False, money_unit: str | None = None, diagonal: bool | None = None)

Bases: ExternalMonetarySUT

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

class dataio.schemas.bonsai_api.external_schemas.OldEuropeanMonetarySUT(*, variance: float | None = None, standard_deviation: float | None = None, confidence_interval_95min: float | None = None, confidence_interval_95max: float | None = None, confidence_interval_68min: float | None = None, confidence_interval_68max: float | None = None, distribution: str | None = None, min_value: float | None = None, max_value: float | None = None, uncertainty_comment: str | None = None, location: str, time: int, unit: str, value: float, comment: str | None = None, flag: str | None = None, table_type: str, product_code: str, product_name: str, activity_code: str, activity_name: str, price_type: str = 'current prices', consumer_price: bool = False, money_unit: str | None = None, diagonal: bool | None = None)

Bases: ExternalMonetarySUT

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

class dataio.schemas.bonsai_api.external_schemas.OlderEuropeanMonetarySUT(*, variance: float | None = None, standard_deviation: float | None = None, confidence_interval_95min: float | None = None, confidence_interval_95max: float | None = None, confidence_interval_68min: float | None = None, confidence_interval_68max: float | None = None, distribution: str | None = None, min_value: float | None = None, max_value: float | None = None, uncertainty_comment: str | None = None, location: str, time: int, unit: str, value: float, comment: str | None = None, flag: str | None = None, table_type: str, product_code: str, product_name: str, activity_code: str, activity_name: str, price_type: str = 'current prices', consumer_price: bool = False, money_unit: str | None = None, diagonal: bool | None = None)

Bases: ExternalMonetarySUT

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

class dataio.schemas.bonsai_api.external_schemas.PRODCOMProductionVolume(*, variance: float | None = None, standard_deviation: float | None = None, confidence_interval_95min: float | None = None, confidence_interval_95max: float | None = None, confidence_interval_68min: float | None = None, confidence_interval_68max: float | None = None, distribution: str | None = None, min_value: float | None = None, max_value: float | None = None, uncertainty_comment: str | None = None, location: str, product: str, activity: str | None = None, unit: str, value: float, flag: str | None = None, time: int, inventory_time: int | None = None, source: str | None = None, comment: str | None = None, price_type: str | None = None, account_type: str | None = None, indicator: str)

Bases: ProductionVolumes_uncertainty

indicator: str

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

class dataio.schemas.bonsai_api.external_schemas.PRODCOMSoldProductionVolume(*, variance: float | None = None, standard_deviation: float | None = None, confidence_interval_95min: float | None = None, confidence_interval_95max: float | None = None, confidence_interval_68min: float | None = None, confidence_interval_68max: float | None = None, distribution: str | None = None, min_value: float | None = None, max_value: float | None = None, uncertainty_comment: str | None = None, location: str, product: str, activity: str | None = None, unit: str, value: float, flag: str | None = None, time: int, inventory_time: int | None = None, source: str | None = None, comment: str | None = None, price_type: str | None = None, account_type: str | None = None, indicator: str)

Bases: ProductionVolumes_uncertainty

indicator: str

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

class dataio.schemas.bonsai_api.external_schemas.ProdcomTrade(*, variance: float | None = None, standard_deviation: float | None = None, confidence_interval_95min: float | None = None, confidence_interval_95max: float | None = None, confidence_interval_68min: float | None = None, confidence_interval_68max: float | None = None, distribution: str | None = None, min_value: float | None = None, max_value: float | None = None, uncertainty_comment: str | None = None, time: int, product: int, export_location: str, import_location: str, value: float, unit: str, flag: str | None = None)

Bases: FactBaseModel_uncertainty

export_location: str

flag: str | None

import_location: str

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

product: int

time: int

unit: str

value: float

class dataio.schemas.bonsai_api.external_schemas.StatCanChemProductionVolume(*, variance: float | None = None, standard_deviation: float | None = None, confidence_interval_95min: float | None = None, confidence_interval_95max: float | None = None, confidence_interval_68min: float | None = None, confidence_interval_68max: float | None = None, distribution: str | None = None, min_value: float | None = None, max_value: float | None = None, uncertainty_comment: str | None = None, location: str, product: str, activity: str | None = None, unit: str, value: float, flag: str | None = None, time: int, inventory_time: int | None = None, source: str | None = None, comment: str | None = None, price_type: str | None = None, account_type: str | None = None)

Bases: ProductionVolumes_uncertainty

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

class dataio.schemas.bonsai_api.external_schemas.UNdataEnergyBalance(*, variance: float | None = None, standard_deviation: float | None = None, confidence_interval_95min: float | None = None, confidence_interval_95max: float | None = None, confidence_interval_68min: float | None = None, confidence_interval_68max: float | None = None, distribution: str | None = None, min_value: float | None = None, max_value: float | None = None, uncertainty_comment: str | None = None, activity: str, product: str, location: str, time: int, value: float, unit: str, comment: str | None = None, flag: str | None = None)

Bases: FactBaseModel_uncertainty

activity: str

comment: str | None

flag: str | None

location: str

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

product: str

time: int

unit: str

value: float

class dataio.schemas.bonsai_api.external_schemas.UNdataEnergyStatistic(*, variance: float | None = None, standard_deviation: float | None = None, confidence_interval_95min: float | None = None, confidence_interval_95max: float | None = None, confidence_interval_68min: float | None = None, confidence_interval_68max: float | None = None, distribution: str | None = None, min_value: float | None = None, max_value: float | None = None, uncertainty_comment: str | None = None, activity: str, product: str, location: str, time: int, value: float, unit: str, comment: str | None = None, flag: str | None = None, conversion_factor: float | None = None)

Bases: FactBaseModel_uncertainty

activity: str

comment: str | None

conversion_factor: float | None

flag: str | None

location: str

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

product: str

time: int

unit: str

value: float

class dataio.schemas.bonsai_api.external_schemas.UNdataWDI(*, variance: float | None = None, standard_deviation: float | None = None, confidence_interval_95min: float | None = None, confidence_interval_95max: float | None = None, confidence_interval_68min: float | None = None, confidence_interval_68max: float | None = None, distribution: str | None = None, min_value: float | None = None, max_value: float | None = None, uncertainty_comment: str | None = None, location: str, time: int, value: float, unit: str, flag: str | None = None)

Bases: FactBaseModel_uncertainty

flag: str | None

location: str

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

time: int

unit: str

value: float

class dataio.schemas.bonsai_api.external_schemas.USGSProductionVolume(*, variance: float | None = None, standard_deviation: float | None = None, confidence_interval_95min: float | None = None, confidence_interval_95max: float | None = None, confidence_interval_68min: float | None = None, confidence_interval_68max: float | None = None, distribution: str | None = None, min_value: float | None = None, max_value: float | None = None, uncertainty_comment: str | None = None, location: str, product: str, activity: str | None = None, unit: str, value: float, flag: str | None = None, time: int, inventory_time: int | None = None, source: str | None = None, comment: str | None = None, price_type: str | None = None, account_type: str | None = None)

Bases: ProductionVolumes_uncertainty

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

class dataio.schemas.bonsai_api.external_schemas.UnfcccProductionVolume(*, variance: float | None = None, standard_deviation: float | None = None, confidence_interval_95min: float | None = None, confidence_interval_95max: float | None = None, confidence_interval_68min: float | None = None, confidence_interval_68max: float | None = None, distribution: str | None = None, min_value: float | None = None, max_value: float | None = None, uncertainty_comment: str | None = None, location: str, product: str, activity: str | None = None, unit: str, value: float, flag: str | None = None, time: int, inventory_time: int | None = None, source: str | None = None, comment: str | None = None, price_type: str | None = None, account_type: str | None = None)

Bases: ProductionVolumes_uncertainty

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

class dataio.schemas.bonsai_api.external_schemas.baseExternalSchemas(*, variance: float | None = None, standard_deviation: float | None = None, confidence_interval_95min: float | None = None, confidence_interval_95max: float | None = None, confidence_interval_68min: float | None = None, confidence_interval_68max: float | None = None, distribution: str | None = None, min_value: float | None = None, max_value: float | None = None, uncertainty_comment: str | None = None, location: str, time: int, unit: str, value: float, comment: str | None = None, flag: str | None = None)

Bases: FactBaseModel_uncertainty

comment: str | None

flag: str | None

location: str

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

time: int

unit: str

value: float

dataio.schemas.bonsai_api.facts module

class dataio.schemas.bonsai_api.facts.CountryFootprint(*, variance: float | None = None, standard_deviation: float | None = None, confidence_interval_95min: float | None = None, confidence_interval_95max: float | None = None, confidence_interval_68min: float | None = None, confidence_interval_68max: float | None = None, distribution: str | None = None, min_value: float | None = None, max_value: float | None = None, uncertainty_comment: str | None = None, act_code: str, region_code: str, value: float, unit_emission: str)

Bases: FactBaseModel_uncertainty

class ConfigDict

Bases: object

from_attributes = True

act_code: str

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

region_code: str

unit_emission: str

value: float

class dataio.schemas.bonsai_api.facts.CountryRecipe(*, variance: float | None = None, standard_deviation: float | None = None, confidence_interval_95min: float | None = None, confidence_interval_95max: float | None = None, confidence_interval_68min: float | None = None, confidence_interval_68max: float | None = None, distribution: str | None = None, min_value: float | None = None, max_value: float | None = None, uncertainty_comment: str | None = None, product_code: str | None = None, unit_reference: str | None = None, act_code: str, region_code: str, value: float, unit_emission: str)

Bases: FactBaseModel_uncertainty

class ConfigDict

Bases: object

from_attributes = True

act_code: str

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

product_code: str | None

region_code: str

unit_emission: str

unit_reference: str | None

value: float

class dataio.schemas.bonsai_api.facts.Footprint(*, variance: float | None = None, standard_deviation: float | None = None, confidence_interval_95min: float | None = None, confidence_interval_95max: float | None = None, confidence_interval_68min: float | None = None, confidence_interval_68max: float | None = None, distribution: str | None = None, min_value: float | None = None, max_value: float | None = None, uncertainty_comment: str | None = None, flow_code: str, description: str | None = None, unit_reference: str | None = None, region_code: str, value: float = 0.0, unit_emission: str = 'tonnes CO2eq')

Bases: FactBaseModel_uncertainty

description: str | None

flow_code: str

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

region_code: str

unit_emission: str

unit_reference: str | None

value: float

class dataio.schemas.bonsai_api.facts.Recipe(*, variance: float | None = None, standard_deviation: float | None = None, confidence_interval_95min: float | None = None, confidence_interval_95max: float | None = None, confidence_interval_68min: float | None = None, confidence_interval_68max: float | None = None, distribution: str | None = None, min_value: float | None = None, max_value: float | None = None, uncertainty_comment: str | None = None, prefixed_id: str, flow: str, region_reference: str, unit_reference: str, flow_input: str, region_inflow: str | None = None, value_inflow: float | None = None, unit_inflow: str | None = None, value_emission: float, unit_emission: str, metrics: str)

Bases: FactBaseModel_uncertainty

flow: str

flow_input: str

metrics: str

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

prefixed_id: str

region_inflow: str | None

region_reference: str

unit_emission: str

unit_inflow: str | None

unit_reference: str

value_emission: float

value_inflow: float | None

dataio.schemas.bonsai_api.ipcc module

class dataio.schemas.bonsai_api.ipcc.ContentData(*, variance: float | None = None, standard_deviation: float | None = None, confidence_interval_95min: float | None = None, confidence_interval_95max: float | None = None, confidence_interval_68min: float | None = None, confidence_interval_68max: float | None = None, distribution: str | None = None, min_value: float | None = None, max_value: float | None = None, uncertainty_comment: str | None = None, product_code: str, content_code: str, product_name: str = None, content_name: str = None, value: float, unit: str, source: str)

Bases: FactBaseModel_uncertainty

content_code: str

content_name: str

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

product_code: str

product_name: str

source: str

unit: str

value: float

class dataio.schemas.bonsai_api.ipcc.Parameters(*, variance: float | None = None, standard_deviation: float | None = None, confidence_interval_95min: float | None = None, confidence_interval_95max: float | None = None, confidence_interval_68min: float | None = None, confidence_interval_68max: float | None = None, distribution: str | None = None, min_value: float | None = None, max_value: float | None = None, uncertainty_comment: str | None = None, time: int = None, location: str = None, activity: str = None, product: str = None, flexible_category: dict | None = None, value: float, unit: str, source: str, flag: str | None = None, description: str)

Bases: FactBaseModel_uncertainty

activity: str

description: str

flag: str | None

flexible_category: dict | None

location: str

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

product: str

source: str

time: int

unit: str

value: float

dataio.schemas.bonsai_api.matrix module

class dataio.schemas.bonsai_api.matrix.A_Matrix

Bases: MatrixModel

column_schema

alias of ActivityColumns

row_schema

alias of ProductRows

class dataio.schemas.bonsai_api.matrix.ActivityColumns(*, variance: float | None = None, standard_deviation: float | None = None, confidence_interval_95min: float | None = None, confidence_interval_95max: float | None = None, confidence_interval_68min: float | None = None, confidence_interval_68max: float | None = None, distribution: str | None = None, min_value: float | None = None, max_value: float | None = None, uncertainty_comment: str | None = None, location: str, activity: str, unit: str, time: int)

Bases: FactBaseModel_uncertainty

activity: str

location: str

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

time: int

unit: str

class dataio.schemas.bonsai_api.matrix.ActivityRows(*, variance: float | None = None, standard_deviation: float | None = None, confidence_interval_95min: float | None = None, confidence_interval_95max: float | None = None, confidence_interval_68min: float | None = None, confidence_interval_68max: float | None = None, distribution: str | None = None, min_value: float | None = None, max_value: float | None = None, uncertainty_comment: str | None = None, location: str, activity: str, unit: str, time: int)

Bases: FactBaseModel_uncertainty

activity: str

location: str

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

time: int

unit: str

class dataio.schemas.bonsai_api.matrix.B_Matrix

Bases: MatrixModel

column_schema

alias of ProductColumns

row_schema

alias of EmissionRows

class dataio.schemas.bonsai_api.matrix.EmissionRows(*, variance: float | None = None, standard_deviation: float | None = None, confidence_interval_95min: float | None = None, confidence_interval_95max: float | None = None, confidence_interval_68min: float | None = None, confidence_interval_68max: float | None = None, distribution: str | None = None, min_value: float | None = None, max_value: float | None = None, uncertainty_comment: str | None = None, emission_substance: str, compartment: str, unit: str, time: int)

Bases: FactBaseModel_uncertainty

compartment: str

emission_substance: str

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

time: int

unit: str

class dataio.schemas.bonsai_api.matrix.IntensitiesMatrix

Bases: MatrixModel

column_schema

alias of ProductColumns

row_schema

alias of EmissionRows

class dataio.schemas.bonsai_api.matrix.Inverse

Bases: MatrixModel

column_schema

alias of ActivityColumns

row_schema

alias of ProductRows

class dataio.schemas.bonsai_api.matrix.ProductColumns(*, variance: float | None = None, standard_deviation: float | None = None, confidence_interval_95min: float | None = None, confidence_interval_95max: float | None = None, confidence_interval_68min: float | None = None, confidence_interval_68max: float | None = None, distribution: str | None = None, min_value: float | None = None, max_value: float | None = None, uncertainty_comment: str | None = None, location: str, product: str, unit: str, time: int)

Bases: FactBaseModel_uncertainty

location: str

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

product: str

time: int

unit: str

class dataio.schemas.bonsai_api.matrix.ProductRows(*, variance: float | None = None, standard_deviation: float | None = None, confidence_interval_95min: float | None = None, confidence_interval_95max: float | None = None, confidence_interval_68min: float | None = None, confidence_interval_68max: float | None = None, distribution: str | None = None, min_value: float | None = None, max_value: float | None = None, uncertainty_comment: str | None = None, location: str, product: str, unit: str, time: int)

Bases: FactBaseModel_uncertainty

location: str

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

product: str

time: int

unit: str

dataio.schemas.bonsai_api.metadata module

class dataio.schemas.bonsai_api.metadata.DataLicense(*, name: str, description: str | None = None, url: str, create_time: ~datetime.datetime = <factory>, created_by: ~dataio.schemas.bonsai_api.metadata.User | None = None)

Bases: BonsaiBaseModel

Pydantic model for Data License.

create_time: datetime

created_by: User | None

description: str | None

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

name: str

names

alias of Names

url: str

class dataio.schemas.bonsai_api.metadata.MetaData(*, id: UUID, created_by: User, last_modified: datetime, license: DataLicense, version: Version)

Bases: BonsaiBaseModel

created_by: User

id: UUID

last_modified: datetime

license: DataLicense

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

version: Version

class dataio.schemas.bonsai_api.metadata.User(*, email: EmailStr, name: str, is_active: bool = True, is_staff: bool = False, is_superuser: bool = False)

Bases: BonsaiBaseModel

Pydantic model representing a user.

email: EmailStr

is_active: bool

is_staff: bool

is_superuser: bool

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

name: str

names

alias of Names

class dataio.schemas.bonsai_api.metadata.Version(*, version: str, create_time: ~datetime.datetime = <factory>, comments: str | None = None)

Bases: BonsaiBaseModel

comments: str | None

create_time: datetime

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

version: str

dataio.schemas.bonsai_api.uncertainty module

class dataio.schemas.bonsai_api.uncertainty.PedigreeMatrix(*, reliability: int | None = None, completeness: int | None = None, temporal_correlation: int | None = None, geographical_correlation: int | None = None, technological_correlation: int | None = None)

Bases: BonsaiBaseModel

completeness: int | None

geographical_correlation: int | None

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

reliability: int | None

technological_correlation: int | None

temporal_correlation: int | None

class dataio.schemas.bonsai_api.uncertainty.Uncertainty(*, variance: float | None = None, standard_deviation: float | None = None, confidence_interval_95min: float | None = None, confidence_interval_95max: float | None = None, confidence_interval_68min: float | None = None, confidence_interval_68max: float | None = None, distribution: str | None = None, min_value: float | None = None, max_value: float | None = None, uncertainty_comment: str | None = None)

Bases: BonsaiBaseModel

confidence_interval_68max: float | None

confidence_interval_68min: float | None

confidence_interval_95max: float | None

confidence_interval_95min: float | None

distribution: str | None

max_value: float | None

min_value: float | None

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

names

alias of Names

standard_deviation: float | None

uncertainty_comment: str | None

variance: float | None

Module contents