boilercv_pipeline.sync_dvc

boilercv_pipeline.sync_dvc#

Sync dvc.yaml and params.yaml with pipeline specification.

Submodules#

Package Contents#

Classes#

Constants

Constants.

SyncDvc

Sync dvc.yaml and params.yaml with pipeline specification.

Data#

const

API#

class boilercv_pipeline.sync_dvc.Constants(
/,
**data: typing.Any,
)#

Bases: pydantic.BaseModel

Constants.

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.

table_key: str#

‘stage’

Key for the global parameters table.

boilercv_pipeline.sync_dvc.const#

‘Constants(…)’

class boilercv_pipeline.sync_dvc.SyncDvc(
/,
**data: typing.Any,
)#

Bases: pydantic.BaseModel

Sync dvc.yaml and params.yaml with pipeline specification.

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.

root: pathlib.Path#

‘cwd(…)’

Root directory for synced DVC configurations.

pipeline: pathlib.Path#

‘Path(…)’

Primary config file describing the DVC pipeline.

params: pathlib.Path#

‘Path(…)’

DVC’s primary parameters YAML file.

stages: str#

‘boilercv_pipeline.stages’

Dotted module path to the package containing stages.

update_param_values: bool#

‘Field(…)’

Update values of parameters in the parameters YAML file.

Contents