transform_rename_columns

TransformRenameColumnsAction

Bases: PipelineAction

Renames the specified columns in the DataFrame.

This method updates the DataFrame in the provided context by renaming columns according to the mapping defined in the columns dictionary, where each key represents an old column name and its corresponding value represents the new column name.

Example

Rename Column:
    action: TRANSFORM_RENAME_COLUMNS
    options:
        columns:
            a_very_long_column_name: shortname

Source code in src/cloe_nessy/pipeline/actions/transform_rename_columns.py

class TransformRenameColumnsAction(PipelineAction):
    """Renames the specified columns in the DataFrame.

    This method updates the DataFrame in the provided context by renaming columns according
    to the mapping defined in the `columns` dictionary, where each key represents an old column
    name and its corresponding value represents the new column name.

    Example:
        ```yaml
        Rename Column:
            action: TRANSFORM_RENAME_COLUMNS
            options:
                columns:
                    a_very_long_column_name: shortname
        ```
    """

    name: str = "TRANSFORM_RENAME_COLUMNS"

    def run(
        self,
        context: PipelineContext,
        *,
        columns: dict[str, str] | None = None,
        **_: Any,
    ) -> PipelineContext:
        """Renames the specified columns in the DataFrame.

        Args:
            context: Context in which this Action is executed.
            columns: A dictionary where the key is the old column name
                and the value is the new column name.

        Raises:
            ValueError: If no columns are provided.
            ValueError: If the data from context is None.

        Returns:
            Context after the execution of this Action.
        """
        if not columns:
            raise ValueError("No columns provided.")

        if context.data is None:
            raise ValueError("Data from the context is required for the operation.")

        df = context.data

        if isinstance(columns, dict):
            df = df.withColumnsRenamed(columns)
        else:
            raise ValueError("'columns' should be a dict, like {'old_name_1':'new_name_1', 'old_name_2':'new_name_2'}")

        return context.from_existing(data=df)  # type: ignore

run(context, *, columns=None, **_)

Renames the specified columns in the DataFrame.

Parameters:

Name	Type	Description	Default
context	PipelineContext	Context in which this Action is executed.	required
columns	dict[str, str] | None	A dictionary where the key is the old column name and the value is the new column name.	None

Raises:

Type	Description
ValueError	If no columns are provided.
ValueError	If the data from context is None.

Returns:

Type	Description
PipelineContext	Context after the execution of this Action.

Source code in src/cloe_nessy/pipeline/actions/transform_rename_columns.py

def run(
    self,
    context: PipelineContext,
    *,
    columns: dict[str, str] | None = None,
    **_: Any,
) -> PipelineContext:
    """Renames the specified columns in the DataFrame.

    Args:
        context: Context in which this Action is executed.
        columns: A dictionary where the key is the old column name
            and the value is the new column name.

    Raises:
        ValueError: If no columns are provided.
        ValueError: If the data from context is None.

    Returns:
        Context after the execution of this Action.
    """
    if not columns:
        raise ValueError("No columns provided.")

    if context.data is None:
        raise ValueError("Data from the context is required for the operation.")

    df = context.data

    if isinstance(columns, dict):
        df = df.withColumnsRenamed(columns)
    else:
        raise ValueError("'columns' should be a dict, like {'old_name_1':'new_name_1', 'old_name_2':'new_name_2'}")

    return context.from_existing(data=df)  # type: ignore