nannyml.config module

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.ColumnMapping(*, features: List[str], timestamp: str, y_pred: str, y_pred_proba: Optional[Union[str, Dict[str, str]]] = None, y_true: 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.

features: List[str]
timestamp: str
y_pred: str
y_pred_proba: Optional[Union[str, Dict[str, str]]]
y_true: str
class nannyml.config.Config(*, input: nannyml.config.InputConfig, output: nannyml.config.WriterConfig, column_mapping: nannyml.config.ColumnMapping, chunker: Optional[nannyml.config.ChunkerConfig] = None, scheduling: Optional[nannyml.config.SchedulingConfig] = None, store: Optional[nannyml.config.StoreConfig] = None, problem_type: str, 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.

chunker: Optional[nannyml.config.ChunkerConfig]
column_mapping: nannyml.config.ColumnMapping
ignore_errors: Optional[bool]
input: nannyml.config.InputConfig
classmethod load(config_path: Optional[str] = None)[source]
output: nannyml.config.WriterConfig
problem_type: str
scheduling: Optional[nannyml.config.SchedulingConfig]
store: Optional[nannyml.config.StoreConfig]
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.DatabaseWriterConfig(*, connection_string: str, model_name: Optional[str] = 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.

connection_string: str
model_name: Optional[str]
class nannyml.config.FileStoreConfig(*, path: 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.

path: 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.PickleWriterConfig(*, path: str, credentials: 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.

credentials: Optional[Dict[str, Any]]
path: str
write_args: Optional[Dict[str, Any]]
class nannyml.config.RawFileWriterConfig(*, path: str, format: str = 'parquet', credentials: 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.

credentials: Optional[Dict[str, Any]]
format: str
path: str
write_args: Optional[Dict[str, Any]]
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(*, file: Optional[nannyml.config.FileStoreConfig] = 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.

file: Optional[nannyml.config.FileStoreConfig]
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(*, database: Optional[nannyml.config.DatabaseWriterConfig] = None, raw_files: Optional[nannyml.config.RawFileWriterConfig] = None, pickle: Optional[nannyml.config.PickleWriterConfig] = 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.

database: Optional[nannyml.config.DatabaseWriterConfig]
pickle: Optional[nannyml.config.PickleWriterConfig]
raw_files: Optional[nannyml.config.RawFileWriterConfig]
nannyml.config.get_config_path(custom_config_path: Optional[str] = None) pathlib.Path[source]