KPI Energy Losses - Types

For more details on energy losses data and waterfall calculation see this dedicated page in the reference section.

KpiEnergyLossesTypes(perfdb)

Class used for handling energy losses types (where energy is measured).

Parameters:

• perfdb

  (PerfDB) –

  Top level object carrying all functionality and the connection handler.

Source code in echo_postgres/perfdb_root.py

def __init__(self, perfdb: e_pg.PerfDB) -> None:
    """Base class that all subclasses should inherit from.

    Parameters
    ----------
    perfdb : PerfDB
        Top level object carrying all functionality and the connection handler.

    """
    self._perfdb: e_pg.PerfDB = perfdb

get(output_type='dict')

Gets the possible energy losses types.

The main attributes are: - name - display_name - description - loss_order - source - bazefield_point - resource_assessment_loss_type_id - resource_assessment_loss_type_name - target_source - considered_in_waterfall - waterfall_group - applicable_to

Parameters:

• output_type

  (Literal['dict', 'DataFrame'], default: 'dict' ) –

  Output type of the data. Can be one of ["dict", "DataFrame"] By default "dict"

Returns:

• DataFrame –

  In case output_type is "DataFrame", returns a DataFrame with the following format: index = name, columns = [description, id]

• dict[str, dict[str, str]] –

  In case output_type is "dict", returns a dictionary in the format {name: {attribute: value, ...}, ...}

Source code in echo_postgres/kpi_energy_losses_types.py

@validate_call
def get(
    self,
    output_type: Literal["dict", "DataFrame"] = "dict",
) -> DataFrame | dict[str, dict[str, str]]:
    """Gets the possible energy losses types.

    The main attributes are:
    - name
    - display_name
    - description
    - loss_order
    - source
    - bazefield_point
    - resource_assessment_loss_type_id
    - resource_assessment_loss_type_name
    - target_source
    - considered_in_waterfall
    - waterfall_group
    - applicable_to

    Parameters
    ----------
    output_type : Literal["dict", "DataFrame"], optional
        Output type of the data. Can be one of ["dict", "DataFrame"]
        By default "dict"

    Returns
    -------
    DataFrame
        In case output_type is "DataFrame", returns a DataFrame with the following format: index = name, columns = [description, id]
    dict[str, dict[str, str]]
        In case output_type is "dict", returns a dictionary in the format {name: {attribute: value, ...}, ...}
    """
    # validate the input
    if output_type not in ["dict", "DataFrame"]:
        raise ValueError(f"output_type must be one of ['dict', 'DataFrame'], got {output_type}")

    # build the query
    query = sql.SQL("SELECT * FROM performance.v_energyloss_types")

    with self._perfdb.conn.reconnect() as conn:
        df = conn.read_to_pandas(query, post_convert="pyarrow")

    df = df.set_index("name")

    return df if output_type == "DataFrame" else df.to_dict(orient="index")

get_ids()

Gets the possible energy losses types.

Returns:

• dict[str, int] –

  A dictionary in the format {name: id, ...}

Source code in echo_postgres/kpi_energy_losses_types.py

def get_ids(self) -> dict[str, int]:
    """Gets the possible energy losses types.

    Returns
    -------
    dict[str, int]
        A dictionary in the format {name: id, ...}
    """
    query = sql.SQL("SELECT name, id FROM performance.v_energyloss_types")

    with self._perfdb.conn.reconnect() as conn:
        data = conn.read_to_pandas(query, post_convert="pyarrow")

    data = data.set_index("name")

    return data["id"].to_dict()