nannyml.config module

class nannyml.config.ChunkerConfig(*, chunk_size: int = None, chunk_period: str = None, chunk_count: int = None)[source]

Bases: BaseModel

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

Raises ValidationError if the input data cannot be parsed to form a valid model.

chunk_count: Optional[int]
chunk_period: Optional[str]
chunk_size: Optional[int]
class nannyml.config.ColumnMapping(*, features: List[str], timestamp: str, y_pred: str, y_pred_proba: Union[str, Dict[str, str]], y_true: str)[source]

Bases: BaseModel

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

Raises ValidationError if the input data cannot be parsed to form a valid model.

features: List[str]
timestamp: str
y_pred: str
y_pred_proba: Union[str, Dict[str, str]]
y_true: str
class nannyml.config.Config(*, input: InputConfig, output: OutputConfig, column_mapping: ColumnMapping, chunker: ChunkerConfig = None, ignore_errors: bool = None)[source]

Bases: BaseModel

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

Raises ValidationError if the input data cannot be parsed to form a valid model.

chunker: Optional[ChunkerConfig]
column_mapping: ColumnMapping
ignore_errors: Optional[bool]
input: InputConfig
classmethod load(config_path: str = None)[source]
output: OutputConfig
class nannyml.config.InputConfig(*, reference_data: InputDataConfig, analysis_data: InputDataConfig, target_data: TargetDataConfig = None)[source]

Bases: BaseModel

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

Raises ValidationError if the input data cannot be parsed to form a valid model.

analysis_data: InputDataConfig
reference_data: InputDataConfig
target_data: Optional[TargetDataConfig]
class nannyml.config.InputDataConfig(*, path: str, credentials: Dict[str, Any] = None, read_args: Dict[str, Any] = None)[source]

Bases: BaseModel

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

Raises ValidationError if the input data cannot be parsed to form a valid model.

credentials: Optional[Dict[str, Any]]
path: str
read_args: Optional[Dict[str, Any]]
class nannyml.config.OutputConfig(*, path: str, format: str = 'parquet', credentials: Dict[str, Any] = None, write_args: Dict[str, Any] = None)[source]

Bases: BaseModel

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

Raises ValidationError if the input data cannot be parsed to form a valid model.

credentials: Optional[Dict[str, Any]]
format: str
path: str
write_args: Optional[Dict[str, Any]]
class nannyml.config.TargetDataConfig(*, path: str, credentials: Dict[str, Any] = None, read_args: Dict[str, Any] = None, join_column: str = None)[source]

Bases: InputDataConfig

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

Raises ValidationError if the input data cannot be parsed to form a valid model.

join_column: Optional[str]
nannyml.config.get_config_path(custom_config_path: Optional[str] = None) Path[source]