BaseLogger

class BaseLogger

Bases: abc.ABC, etna.core.mixins.BaseMixin

Abstract class for implementing loggers.

Create logger instance.

Inherited-members

Methods

finish_experiment(*args, **kwargs)	Finish experiment.
log(msg, **kwargs)	Log any event.
log_backtest_metrics(ts, metrics_df, ...)	Write metrics to logger.
log_backtest_run(metrics, forecast, test)	Backtest metrics from one fold to logger.
set_params(**params)	Return new object instance with modified parameters.
start_experiment(*args, **kwargs)	Start experiment.
to_dict()	Collect all information about etna object in dict.

finish_experiment(*args, **kwargs)

Finish experiment.

abstract log(msg: Union[str, Dict[str, Any]], **kwargs)

Log any event.

e.g. “Fitted segment segment_name”

Parameters

• msg (Union[str, Dict[str, Any]]) – Message or dict to log

• kwargs – Additional parameters for particular implementation

abstract log_backtest_metrics(ts: TSDataset, metrics_df: pandas.core.frame.DataFrame, forecast_df: pandas.core.frame.DataFrame, fold_info_df: pandas.core.frame.DataFrame)

Write metrics to logger.

Parameters

• ts (TSDataset) – TSDataset to with backtest data

• metrics_df (pandas.core.frame.DataFrame) – Dataframe produced with etna.pipeline.Pipeline._get_backtest_metrics()

• forecast_df (pandas.core.frame.DataFrame) – Forecast from backtest

• fold_info_df (pandas.core.frame.DataFrame) – Fold information from backtest

log_backtest_run(metrics: pandas.core.frame.DataFrame, forecast: pandas.core.frame.DataFrame, test: pandas.core.frame.DataFrame)

Backtest metrics from one fold to logger.

Parameters

• metrics (pandas.core.frame.DataFrame) – Dataframe with metrics from backtest fold

• forecast (pandas.core.frame.DataFrame) – Dataframe with forecast

• test (pandas.core.frame.DataFrame) – Dataframe with ground truth

start_experiment(*args, **kwargs)

Start experiment.

Complete logger initialization or reinitialize it before the next experiment with the same name.