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time_series

time_series

Classes:

Name Description
TimeSeriesParameters

Configuration for time-series mode in the Safe Synthesizer pipeline.

TimeSeriesParameters pydantic-model

Bases: Parameters

Configuration for time-series mode in the Safe Synthesizer pipeline.

Controls whether a dataset is treated as time-series data, including timestamp column selection, interval inference, and format validation. The time-series pipeline is currently experimental.

Fields:

Validators:

is_timeseries pydantic-field

Whether to treat the dataset as time series. When enabled, either timestamp_column or timestamp_interval_seconds is required. For grouped time series, group_training_examples_by needs to be set.

timestamp_column pydantic-field

Name of the column containing timestamps used to order records when is_timeseries is True. Required only when is_timeseries is True and timestamp_interval_seconds is not provided.

timestamp_interval_seconds pydantic-field

Interval in seconds between timestamps. If not provided, the timestamp column will be used to infer the interval.

timestamp_format pydantic-field

Format of the timestamp column. Accepts either: (1) Python strftime format codes for string timestamps (e.g., '%Y-%m-%d %H:%M:%S', '%m/%d/%Y'), or (2) 'elapsed_seconds' for numeric (int/float) timestamps representing seconds as an increasing counter (e.g., 0, 60, 120 for 1-minute intervals). If not provided, the format will be inferred from the data.

start_timestamp pydantic-field

Start timestamp. If not provided, the first timestamp in the timestamp column will be used.

stop_timestamp pydantic-field

Stop timestamp. If not provided, the last timestamp in the timestamp column will be used.

validate_timestamp_format(v) pydantic-validator

Validate that timestamp_format is a valid strftime format string.

Source code in src/nemo_safe_synthesizer/config/time_series.py 
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@field_validator("timestamp_format")
@classmethod
def validate_timestamp_format(cls, v: str | None) -> str | None:
    """Validate that timestamp_format is a valid strftime format string."""
    if v is None or v == "elapsed_seconds":
        return v
    try:
        datetime.now().strftime(v)
    except ValueError as e:
        raise ValueError(f"Invalid strftime format '{v}': {e}") from e
    return v

check_timestamp_column_or_interval_when_timeseries() pydantic-validator

Validate that time-series mode has a timestamp source and non-timeseries mode has no timestamp_column.

Source code in src/nemo_safe_synthesizer/config/time_series.py 
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@model_validator(mode="after")
def check_timestamp_column_or_interval_when_timeseries(self):
    """Validate that time-series mode has a timestamp source and non-timeseries mode has no `timestamp_column`."""
    if self.is_timeseries:
        if self.timestamp_column is None and self.timestamp_interval_seconds is None:
            raise ValueError(
                "At least one of timestamp_column or timestamp_interval_seconds must be provided when is_timeseries is True."
            )
    else:
        if self.timestamp_column is not None:
            raise ValueError("timestamp_column can only be set when is_timeseries is True.")
    return self