def METHOD_NAME(dest_dir: str) -> None:
    #
    # Load inputs.
    #
    # Retrieve snapshot.
    snap = cast(Snapshot, paths.load_dependency("uk_historical_electricity.xls"))
    # Load data from the two relevant sheets of the excel file.
    # The original excel file is poorly formatted and will be hard to parse automatically.
    data = pr.ExcelFile(snap.path)
    tb_fuel_input = data.parse(sheet_name="Fuel input", metadata=snap.to_table_metadata())
    tb_supply = data.parse(sheet_name="Supply, availability & consump", metadata=snap.to_table_metadata())
    tb_efficiency = data.parse(sheet_name="Generated and supplied", metadata=snap.to_table_metadata())
    #
    # Process data.
    #
    # Process data from the sheet about fuels input for electricity generation.
    tb_fuel_input = prepare_data(
        tb=tb_fuel_input,
        expected_content={
            1: ["Total", "all", "fuels"],
            2: ["Coal"],
            3: ["Oil"],
            4: ["Natural", "gas"],
            5: ["Nuclear"],
            6: ["Natural", "flow hydro"],
            7: ["Wind", "and solar"],
            9: ["Other", "fuels"],
        },
        columns={
            0: "year",
            1: "all_sources",
            2: "coal",
            3: "oil",
            4: "gas",
            5: "nuclear",
            6: "hydro",
            7: "wind_and_solar",
            9: "other",
        },
        table_name="fuel_input",
    )
    # Prepare data from the sheet about electricity supply, availability and consumption.
    tb_supply = prepare_data(
        tb=tb_supply,
        expected_content={
            1: ["Electricity", "supplied"],
            3: ["Net", "Imports"],
        },
        columns={
            0: "year",
            1: "electricity_generation",
            3: "net_imports",
        },
        table_name="supply",
    )
    # Prepare data from the sheet about electricity generated and supplied.
    tb_efficiency = prepare_data(
        tb=tb_efficiency,
        expected_content={
            33: ["Implied", "Efficiency"],
        },
        columns={
            0: "year",
            33: "implied_efficiency",
        },
        table_name="efficiency",
    )
    #
    # Save outputs.
    #
    # Create a new meadow dataset with the same metadata as the snapshot.
    ds_meadow = create_dataset(
        dest_dir,
        tables=[tb_fuel_input, tb_supply, tb_efficiency],
        default_metadata=snap.metadata,
        check_variables_metadata=True,
    )
    # Save changes in the new garden dataset.
    ds_meadow.save()