nannyml.config module
- class nannyml.config.CalculatorConfig(*, type: str, name: Optional[str] = None, enabled: Optional[bool] = True, outputs: Optional[List[nannyml.config.WriterConfig]] = None, store: Optional[nannyml.config.StoreConfig] = None, params: Dict[str, Any])[source]
Bases:
pydantic.main.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.
- enabled: Optional[bool]
- name: Optional[str]
- outputs: Optional[List[nannyml.config.WriterConfig]]
- params: Dict[str, Any]
- store: Optional[nannyml.config.StoreConfig]
- type: str
- class nannyml.config.ChunkerConfig(*, chunk_size: Optional[int] = None, chunk_period: Optional[str] = None, chunk_count: Optional[int] = None)[source]
Bases:
pydantic.main.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.Config(*, input: Optional[nannyml.config.InputConfig] = None, calculators: List[nannyml.config.CalculatorConfig], scheduling: Optional[nannyml.config.SchedulingConfig] = None, ignore_errors: Optional[bool] = None)[source]
Bases:
pydantic.main.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.
- calculators: List[nannyml.config.CalculatorConfig]
- ignore_errors: Optional[bool]
- input: Optional[nannyml.config.InputConfig]
- scheduling: Optional[nannyml.config.SchedulingConfig]
- class nannyml.config.CronSchedulingConfig(*, crontab: str)[source]
Bases:
pydantic.main.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.
- crontab: str
- class nannyml.config.InputConfig(*, reference_data: nannyml.config.InputDataConfig, analysis_data: nannyml.config.InputDataConfig, target_data: Optional[nannyml.config.TargetDataConfig] = None)[source]
Bases:
pydantic.main.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: nannyml.config.InputDataConfig
- reference_data: nannyml.config.InputDataConfig
- target_data: Optional[nannyml.config.TargetDataConfig]
- class nannyml.config.InputDataConfig(*, path: str, credentials: Optional[Dict[str, Any]] = None, read_args: Optional[Dict[str, Any]] = None)[source]
Bases:
pydantic.main.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.IntervalSchedulingConfig(*, weeks: Optional[int] = None, days: Optional[int] = None, hours: Optional[int] = None, minutes: Optional[int] = None)[source]
Bases:
pydantic.main.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.
- days: Optional[int]
- hours: Optional[int]
- minutes: Optional[int]
- weeks: Optional[int]
- class nannyml.config.SchedulingConfig(*, interval: Optional[nannyml.config.IntervalSchedulingConfig] = None, cron: Optional[nannyml.config.CronSchedulingConfig] = None)[source]
Bases:
pydantic.main.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.
- cron: Optional[nannyml.config.CronSchedulingConfig]
- interval: Optional[nannyml.config.IntervalSchedulingConfig]
- class nannyml.config.StoreConfig(*, path: str, credentials: Optional[Dict[str, Any]] = None, filename: Optional[str] = None, invalidate: bool = False)[source]
Bases:
pydantic.main.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]]
- filename: Optional[str]
- invalidate: bool
- path: str
- class nannyml.config.TargetDataConfig(*, path: str, credentials: Optional[Dict[str, Any]] = None, read_args: Optional[Dict[str, Any]] = None, join_column: Optional[str] = None)[source]
Bases:
nannyml.config.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]
- class nannyml.config.WriterConfig(*, type: str, params: Optional[Dict[str, Any]] = None, write_args: Optional[Dict[str, Any]] = None)[source]
Bases:
pydantic.main.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.
- params: Optional[Dict[str, Any]]
- type: str
- write_args: Optional[Dict[str, Any]]