context_enricher

context_enricher

ContextEnricher

ContextEnricher(
    dataframe: DataFrame, *, uuid_column: str = "uuid"
)

Enrich timeseries DataFrames with contextual metadata.

Merges metadata (descriptions, units, tolerances, value mappings) onto timeseries data using UUID-based lookups. This enables downstream analytics to access context without separate lookups.

Example usage::

enricher = ContextEnricher(timeseries_df)

# Add descriptions and units from metadata
enriched = enricher.enrich_with_metadata(
    metadata_df,
    metadata_uuid_col="uuid",
    columns=["description", "unit", "area"],
)

# Add tolerance limits
enriched = enricher.enrich_with_tolerances(
    tolerance_df,
    tolerance_uuid_col="uuid",
    low_col="low_limit",
    high_col="high_limit",
)

Initialize with a timeseries DataFrame.

Parameters:

Name	Type	Description	Default
dataframe	DataFrame	Timeseries DataFrame with a UUID column.	required
uuid_column	str	Column name for signal UUID.	'uuid'

enrich_with_metadata

enrich_with_metadata(
    metadata: DataFrame,
    *,
    metadata_uuid_col: str = "uuid",
    columns: Optional[List[str]] = None
) -> pd.DataFrame

Join metadata columns onto timeseries by UUID.

Parameters:

Name	Type	Description	Default
metadata	DataFrame	Metadata DataFrame containing signal info.	required
metadata_uuid_col	str	UUID column in metadata.	'uuid'
columns	Optional[List[str]]	Specific columns to merge. If None, merges all non-UUID columns.	None

Returns:

Type	Description
DataFrame	Enriched DataFrame with metadata columns attached.

enrich_with_tolerances

enrich_with_tolerances(
    tolerances: DataFrame,
    *,
    tolerance_uuid_col: str = "uuid",
    low_col: str = "low_limit",
    high_col: str = "high_limit"
) -> pd.DataFrame

Attach tolerance limits from a tolerance DataFrame.

Parameters:

Name	Type	Description	Default
tolerances	DataFrame	DataFrame with UUID, low_limit, high_limit columns.	required
tolerance_uuid_col	str	UUID column in tolerances.	'uuid'
low_col	str	Column with lower tolerance limit.	'low_limit'
high_col	str	Column with upper tolerance limit.	'high_limit'

Returns:

Type	Description
DataFrame	DataFrame with tolerance columns appended.

enrich_with_mapping

enrich_with_mapping(
    mapping: DataFrame,
    *,
    mapping_uuid_col: str = "uuid",
    raw_value_col: str = "raw_value",
    mapped_value_col: str = "mapped_value",
    value_column: str = "value_string"
) -> pd.DataFrame

Apply value mappings from a mapping DataFrame.

Maps raw values (e.g. numeric codes) to descriptive strings using a UUID-specific mapping table.

Parameters:

Name	Type	Description	Default
mapping	DataFrame	DataFrame with uuid, raw_value, mapped_value columns.	required
mapping_uuid_col	str	UUID column in mapping.	'uuid'
raw_value_col	str	Column with raw values to match.	'raw_value'
mapped_value_col	str	Column with mapped/descriptive values.	'mapped_value'
value_column	str	Column in timeseries to match against raw values.	'value_string'

Returns:

Type	Description
DataFrame	DataFrame with a 'mapped_value' column appended.

get_enriched_dataframe

get_enriched_dataframe() -> pd.DataFrame

Return the current state of the dataframe.