boilercv_pipeline.models.data

`boilercv_pipeline.models.data`#

Output data model.

class boilercv_pipeline.models.data.Dfs(

/,

**data: typing.Any,

)#

Bases: pydantic.BaseModel

Data frames.

Initialization

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

‘Field(…)’

Source data for this stage.

‘Field(…)’

Destination data for this stage.

class boilercv_pipeline.models.data.Plots(

/,

**data: context_models.types.Data,

)#

Plots.

Initialization

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

classmethod dvc_validate_plot( figure: matplotlib.figure.Figure, info: boilercv_pipeline.sync_dvc.types.DvcValidationInfo, ) → matplotlib.figure.Figure#: Append plot name for dvc.yaml.

class boilercv_pipeline.models.data.Data(

/,

**data: context_models.types.Data,

)#

Data frame and plot outputs.

Initialization

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.