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Options

Pandas-like options system (get/set/reset + option_context).

AggColumns

Aggregation columns accessed via cols.agg.*.

Source code in openretailscience/options.py 
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class AggColumns:
    """Aggregation columns accessed via cols.agg.*."""

    def __init__(self) -> None:
        """Initialize aggregation columns."""
        # Base aggregation columns
        self.customer_id: str = get_option("column.agg.customer_id")
        self.transaction_id: str = get_option("column.agg.transaction_id")
        self.unit_spend: str = get_option("column.agg.unit_spend")
        self.unit_qty: str = get_option("column.agg.unit_quantity")
        self.unit_cost: str = get_option("column.agg.unit_cost")
        self.promo_unit_spend: str = get_option("column.agg.promo_unit_spend")
        self.promo_unit_qty: str = get_option("column.agg.promo_unit_quantity")

        # Period variants
        self.customer_id_p1: str = ColumnHelper.join_options("column.agg.customer_id", "column.suffix.period_1")
        self.customer_id_p2: str = ColumnHelper.join_options("column.agg.customer_id", "column.suffix.period_2")
        self.transaction_id_p1: str = ColumnHelper.join_options("column.agg.transaction_id", "column.suffix.period_1")
        self.transaction_id_p2: str = ColumnHelper.join_options("column.agg.transaction_id", "column.suffix.period_2")
        self.unit_spend_p1: str = ColumnHelper.join_options("column.agg.unit_spend", "column.suffix.period_1")
        self.unit_spend_p2: str = ColumnHelper.join_options("column.agg.unit_spend", "column.suffix.period_2")
        self.unit_qty_p1: str = ColumnHelper.join_options("column.agg.unit_quantity", "column.suffix.period_1")
        self.unit_qty_p2: str = ColumnHelper.join_options("column.agg.unit_quantity", "column.suffix.period_2")
        self.unit_cost_p1: str = ColumnHelper.join_options("column.agg.unit_cost", "column.suffix.period_1")
        self.unit_cost_p2: str = ColumnHelper.join_options("column.agg.unit_cost", "column.suffix.period_2")
        self.promo_unit_spend_p1: str = ColumnHelper.join_options(
            "column.agg.promo_unit_spend",
            "column.suffix.period_1",
        )
        self.promo_unit_spend_p2: str = ColumnHelper.join_options(
            "column.agg.promo_unit_spend",
            "column.suffix.period_2",
        )
        self.promo_unit_qty_p1: str = ColumnHelper.join_options(
            "column.agg.promo_unit_quantity",
            "column.suffix.period_1",
        )
        self.promo_unit_qty_p2: str = ColumnHelper.join_options(
            "column.agg.promo_unit_quantity",
            "column.suffix.period_2",
        )

        # Diff variants
        self.customer_id_diff: str = ColumnHelper.join_options("column.agg.customer_id", "column.suffix.difference")
        self.transaction_id_diff: str = ColumnHelper.join_options(
            "column.agg.transaction_id",
            "column.suffix.difference",
        )
        self.unit_spend_diff: str = ColumnHelper.join_options("column.agg.unit_spend", "column.suffix.difference")
        self.unit_qty_diff: str = ColumnHelper.join_options("column.agg.unit_quantity", "column.suffix.difference")
        self.unit_cost_diff: str = ColumnHelper.join_options("column.agg.unit_cost", "column.suffix.difference")
        self.promo_unit_spend_diff: str = ColumnHelper.join_options(
            "column.agg.promo_unit_spend",
            "column.suffix.difference",
        )
        self.promo_unit_qty_diff: str = ColumnHelper.join_options(
            "column.agg.promo_unit_quantity",
            "column.suffix.difference",
        )

        # Percent diff variants
        self.customer_id_pct_diff: str = ColumnHelper.join_options(
            "column.agg.customer_id",
            "column.suffix.percent_difference",
        )
        self.transaction_id_pct_diff: str = ColumnHelper.join_options(
            "column.agg.transaction_id",
            "column.suffix.percent_difference",
        )
        self.unit_spend_pct_diff: str = ColumnHelper.join_options(
            "column.agg.unit_spend",
            "column.suffix.percent_difference",
        )
        self.unit_qty_pct_diff: str = ColumnHelper.join_options(
            "column.agg.unit_quantity",
            "column.suffix.percent_difference",
        )
        self.unit_cost_pct_diff: str = ColumnHelper.join_options(
            "column.agg.unit_cost",
            "column.suffix.percent_difference",
        )
        self.promo_unit_spend_pct_diff: str = ColumnHelper.join_options(
            "column.agg.promo_unit_spend",
            "column.suffix.percent_difference",
        )
        self.promo_unit_qty_pct_diff: str = ColumnHelper.join_options(
            "column.agg.promo_unit_quantity",
            "column.suffix.percent_difference",
        )

        # Contribution variants
        self.customer_id_contrib: str = ColumnHelper.join_options(
            "column.agg.customer_id",
            "column.suffix.contribution",
        )

        # Percent variants
        self.customers_pct: str = ColumnHelper.join_options("column.agg.customer_id", "column.suffix.percent")

        # Unknown/Total variants
        self.unit_spend_unknown: str = ColumnHelper.join_options(
            "column.agg.unit_spend",
            "column.suffix.unknown_customer",
        )
        self.unit_spend_total: str = ColumnHelper.join_options("column.agg.unit_spend", "column.suffix.total")
        self.transaction_id_unknown: str = ColumnHelper.join_options(
            "column.agg.transaction_id",
            "column.suffix.unknown_customer",
        )
        self.transaction_id_total: str = ColumnHelper.join_options("column.agg.transaction_id", "column.suffix.total")
        self.unit_qty_unknown: str = ColumnHelper.join_options(
            "column.agg.unit_quantity",
            "column.suffix.unknown_customer",
        )
        self.unit_qty_total: str = ColumnHelper.join_options("column.agg.unit_quantity", "column.suffix.total")

__init__()

Initialize aggregation columns.

Source code in openretailscience/options.py 
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def __init__(self) -> None:
    """Initialize aggregation columns."""
    # Base aggregation columns
    self.customer_id: str = get_option("column.agg.customer_id")
    self.transaction_id: str = get_option("column.agg.transaction_id")
    self.unit_spend: str = get_option("column.agg.unit_spend")
    self.unit_qty: str = get_option("column.agg.unit_quantity")
    self.unit_cost: str = get_option("column.agg.unit_cost")
    self.promo_unit_spend: str = get_option("column.agg.promo_unit_spend")
    self.promo_unit_qty: str = get_option("column.agg.promo_unit_quantity")

    # Period variants
    self.customer_id_p1: str = ColumnHelper.join_options("column.agg.customer_id", "column.suffix.period_1")
    self.customer_id_p2: str = ColumnHelper.join_options("column.agg.customer_id", "column.suffix.period_2")
    self.transaction_id_p1: str = ColumnHelper.join_options("column.agg.transaction_id", "column.suffix.period_1")
    self.transaction_id_p2: str = ColumnHelper.join_options("column.agg.transaction_id", "column.suffix.period_2")
    self.unit_spend_p1: str = ColumnHelper.join_options("column.agg.unit_spend", "column.suffix.period_1")
    self.unit_spend_p2: str = ColumnHelper.join_options("column.agg.unit_spend", "column.suffix.period_2")
    self.unit_qty_p1: str = ColumnHelper.join_options("column.agg.unit_quantity", "column.suffix.period_1")
    self.unit_qty_p2: str = ColumnHelper.join_options("column.agg.unit_quantity", "column.suffix.period_2")
    self.unit_cost_p1: str = ColumnHelper.join_options("column.agg.unit_cost", "column.suffix.period_1")
    self.unit_cost_p2: str = ColumnHelper.join_options("column.agg.unit_cost", "column.suffix.period_2")
    self.promo_unit_spend_p1: str = ColumnHelper.join_options(
        "column.agg.promo_unit_spend",
        "column.suffix.period_1",
    )
    self.promo_unit_spend_p2: str = ColumnHelper.join_options(
        "column.agg.promo_unit_spend",
        "column.suffix.period_2",
    )
    self.promo_unit_qty_p1: str = ColumnHelper.join_options(
        "column.agg.promo_unit_quantity",
        "column.suffix.period_1",
    )
    self.promo_unit_qty_p2: str = ColumnHelper.join_options(
        "column.agg.promo_unit_quantity",
        "column.suffix.period_2",
    )

    # Diff variants
    self.customer_id_diff: str = ColumnHelper.join_options("column.agg.customer_id", "column.suffix.difference")
    self.transaction_id_diff: str = ColumnHelper.join_options(
        "column.agg.transaction_id",
        "column.suffix.difference",
    )
    self.unit_spend_diff: str = ColumnHelper.join_options("column.agg.unit_spend", "column.suffix.difference")
    self.unit_qty_diff: str = ColumnHelper.join_options("column.agg.unit_quantity", "column.suffix.difference")
    self.unit_cost_diff: str = ColumnHelper.join_options("column.agg.unit_cost", "column.suffix.difference")
    self.promo_unit_spend_diff: str = ColumnHelper.join_options(
        "column.agg.promo_unit_spend",
        "column.suffix.difference",
    )
    self.promo_unit_qty_diff: str = ColumnHelper.join_options(
        "column.agg.promo_unit_quantity",
        "column.suffix.difference",
    )

    # Percent diff variants
    self.customer_id_pct_diff: str = ColumnHelper.join_options(
        "column.agg.customer_id",
        "column.suffix.percent_difference",
    )
    self.transaction_id_pct_diff: str = ColumnHelper.join_options(
        "column.agg.transaction_id",
        "column.suffix.percent_difference",
    )
    self.unit_spend_pct_diff: str = ColumnHelper.join_options(
        "column.agg.unit_spend",
        "column.suffix.percent_difference",
    )
    self.unit_qty_pct_diff: str = ColumnHelper.join_options(
        "column.agg.unit_quantity",
        "column.suffix.percent_difference",
    )
    self.unit_cost_pct_diff: str = ColumnHelper.join_options(
        "column.agg.unit_cost",
        "column.suffix.percent_difference",
    )
    self.promo_unit_spend_pct_diff: str = ColumnHelper.join_options(
        "column.agg.promo_unit_spend",
        "column.suffix.percent_difference",
    )
    self.promo_unit_qty_pct_diff: str = ColumnHelper.join_options(
        "column.agg.promo_unit_quantity",
        "column.suffix.percent_difference",
    )

    # Contribution variants
    self.customer_id_contrib: str = ColumnHelper.join_options(
        "column.agg.customer_id",
        "column.suffix.contribution",
    )

    # Percent variants
    self.customers_pct: str = ColumnHelper.join_options("column.agg.customer_id", "column.suffix.percent")

    # Unknown/Total variants
    self.unit_spend_unknown: str = ColumnHelper.join_options(
        "column.agg.unit_spend",
        "column.suffix.unknown_customer",
    )
    self.unit_spend_total: str = ColumnHelper.join_options("column.agg.unit_spend", "column.suffix.total")
    self.transaction_id_unknown: str = ColumnHelper.join_options(
        "column.agg.transaction_id",
        "column.suffix.unknown_customer",
    )
    self.transaction_id_total: str = ColumnHelper.join_options("column.agg.transaction_id", "column.suffix.total")
    self.unit_qty_unknown: str = ColumnHelper.join_options(
        "column.agg.unit_quantity",
        "column.suffix.unknown_customer",
    )
    self.unit_qty_total: str = ColumnHelper.join_options("column.agg.unit_quantity", "column.suffix.total")

CalcColumns

Calculated columns accessed via cols.calc.*.

Source code in openretailscience/options.py 
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class CalcColumns:
    """Calculated columns accessed via cols.calc.*."""

    def __init__(self) -> None:
        """Initialize calculated columns."""
        # Base calculated columns
        self.spend_per_cust: str = get_option("column.calc.spend_per_customer")
        self.trans_per_cust: str = get_option("column.calc.transactions_per_customer")
        self.spend_per_trans: str = get_option("column.calc.spend_per_transaction")
        self.units_per_trans: str = get_option("column.calc.units_per_transaction")
        self.price_per_unit: str = get_option("column.calc.price_per_unit")
        self.price_elasticity: str = get_option("column.calc.price_elasticity")
        self.frequency_elasticity: str = get_option("column.calc.frequency_elasticity")

        # Period variants
        self.spend_per_cust_p1: str = ColumnHelper.join_options(
            "column.calc.spend_per_customer",
            "column.suffix.period_1",
        )
        self.spend_per_cust_p2: str = ColumnHelper.join_options(
            "column.calc.spend_per_customer",
            "column.suffix.period_2",
        )
        self.trans_per_cust_p1: str = ColumnHelper.join_options(
            "column.calc.transactions_per_customer",
            "column.suffix.period_1",
        )
        self.trans_per_cust_p2: str = ColumnHelper.join_options(
            "column.calc.transactions_per_customer",
            "column.suffix.period_2",
        )
        self.spend_per_trans_p1: str = ColumnHelper.join_options(
            "column.calc.spend_per_transaction",
            "column.suffix.period_1",
        )
        self.spend_per_trans_p2: str = ColumnHelper.join_options(
            "column.calc.spend_per_transaction",
            "column.suffix.period_2",
        )
        self.units_per_trans_p1: str = ColumnHelper.join_options(
            "column.calc.units_per_transaction",
            "column.suffix.period_1",
        )
        self.units_per_trans_p2: str = ColumnHelper.join_options(
            "column.calc.units_per_transaction",
            "column.suffix.period_2",
        )
        self.price_per_unit_p1: str = ColumnHelper.join_options("column.calc.price_per_unit", "column.suffix.period_1")
        self.price_per_unit_p2: str = ColumnHelper.join_options("column.calc.price_per_unit", "column.suffix.period_2")

        # Diff variants
        self.spend_per_cust_diff: str = ColumnHelper.join_options(
            "column.calc.spend_per_customer",
            "column.suffix.difference",
        )
        self.trans_per_cust_diff: str = ColumnHelper.join_options(
            "column.calc.transactions_per_customer",
            "column.suffix.difference",
        )
        self.spend_per_trans_diff: str = ColumnHelper.join_options(
            "column.calc.spend_per_transaction",
            "column.suffix.difference",
        )
        self.units_per_trans_diff: str = ColumnHelper.join_options(
            "column.calc.units_per_transaction",
            "column.suffix.difference",
        )
        self.price_per_unit_diff: str = ColumnHelper.join_options(
            "column.calc.price_per_unit",
            "column.suffix.difference",
        )

        # Percent diff variants
        self.spend_per_cust_pct_diff: str = ColumnHelper.join_options(
            "column.calc.spend_per_customer",
            "column.suffix.percent_difference",
        )
        self.trans_per_cust_pct_diff: str = ColumnHelper.join_options(
            "column.calc.transactions_per_customer",
            "column.suffix.percent_difference",
        )
        self.spend_per_trans_pct_diff: str = ColumnHelper.join_options(
            "column.calc.spend_per_transaction",
            "column.suffix.percent_difference",
        )
        self.units_per_trans_pct_diff: str = ColumnHelper.join_options(
            "column.calc.units_per_transaction",
            "column.suffix.percent_difference",
        )
        self.price_per_unit_pct_diff: str = ColumnHelper.join_options(
            "column.calc.price_per_unit",
            "column.suffix.percent_difference",
        )

        # Contribution variants
        self.spend_per_cust_contrib: str = ColumnHelper.join_options(
            "column.calc.spend_per_customer",
            "column.suffix.contribution",
        )
        self.trans_per_cust_contrib: str = ColumnHelper.join_options(
            "column.calc.transactions_per_customer",
            "column.suffix.contribution",
        )
        self.spend_per_trans_contrib: str = ColumnHelper.join_options(
            "column.calc.spend_per_transaction",
            "column.suffix.contribution",
        )
        self.units_per_trans_contrib: str = ColumnHelper.join_options(
            "column.calc.units_per_transaction",
            "column.suffix.contribution",
        )
        self.price_per_unit_contrib: str = ColumnHelper.join_options(
            "column.calc.price_per_unit",
            "column.suffix.contribution",
        )

        # Unknown/Total variants
        self.spend_per_trans_unknown: str = ColumnHelper.join_options(
            "column.calc.spend_per_transaction",
            "column.suffix.unknown_customer",
        )
        self.spend_per_trans_total: str = ColumnHelper.join_options(
            "column.calc.spend_per_transaction",
            "column.suffix.total",
        )
        self.price_per_unit_unknown: str = ColumnHelper.join_options(
            "column.calc.price_per_unit",
            "column.suffix.unknown_customer",
        )
        self.price_per_unit_total: str = ColumnHelper.join_options("column.calc.price_per_unit", "column.suffix.total")
        self.units_per_trans_unknown: str = ColumnHelper.join_options(
            "column.calc.units_per_transaction",
            "column.suffix.unknown_customer",
        )
        self.units_per_trans_total: str = ColumnHelper.join_options(
            "column.calc.units_per_transaction",
            "column.suffix.total",
        )

__init__()

Initialize calculated columns.

Source code in openretailscience/options.py 
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def __init__(self) -> None:
    """Initialize calculated columns."""
    # Base calculated columns
    self.spend_per_cust: str = get_option("column.calc.spend_per_customer")
    self.trans_per_cust: str = get_option("column.calc.transactions_per_customer")
    self.spend_per_trans: str = get_option("column.calc.spend_per_transaction")
    self.units_per_trans: str = get_option("column.calc.units_per_transaction")
    self.price_per_unit: str = get_option("column.calc.price_per_unit")
    self.price_elasticity: str = get_option("column.calc.price_elasticity")
    self.frequency_elasticity: str = get_option("column.calc.frequency_elasticity")

    # Period variants
    self.spend_per_cust_p1: str = ColumnHelper.join_options(
        "column.calc.spend_per_customer",
        "column.suffix.period_1",
    )
    self.spend_per_cust_p2: str = ColumnHelper.join_options(
        "column.calc.spend_per_customer",
        "column.suffix.period_2",
    )
    self.trans_per_cust_p1: str = ColumnHelper.join_options(
        "column.calc.transactions_per_customer",
        "column.suffix.period_1",
    )
    self.trans_per_cust_p2: str = ColumnHelper.join_options(
        "column.calc.transactions_per_customer",
        "column.suffix.period_2",
    )
    self.spend_per_trans_p1: str = ColumnHelper.join_options(
        "column.calc.spend_per_transaction",
        "column.suffix.period_1",
    )
    self.spend_per_trans_p2: str = ColumnHelper.join_options(
        "column.calc.spend_per_transaction",
        "column.suffix.period_2",
    )
    self.units_per_trans_p1: str = ColumnHelper.join_options(
        "column.calc.units_per_transaction",
        "column.suffix.period_1",
    )
    self.units_per_trans_p2: str = ColumnHelper.join_options(
        "column.calc.units_per_transaction",
        "column.suffix.period_2",
    )
    self.price_per_unit_p1: str = ColumnHelper.join_options("column.calc.price_per_unit", "column.suffix.period_1")
    self.price_per_unit_p2: str = ColumnHelper.join_options("column.calc.price_per_unit", "column.suffix.period_2")

    # Diff variants
    self.spend_per_cust_diff: str = ColumnHelper.join_options(
        "column.calc.spend_per_customer",
        "column.suffix.difference",
    )
    self.trans_per_cust_diff: str = ColumnHelper.join_options(
        "column.calc.transactions_per_customer",
        "column.suffix.difference",
    )
    self.spend_per_trans_diff: str = ColumnHelper.join_options(
        "column.calc.spend_per_transaction",
        "column.suffix.difference",
    )
    self.units_per_trans_diff: str = ColumnHelper.join_options(
        "column.calc.units_per_transaction",
        "column.suffix.difference",
    )
    self.price_per_unit_diff: str = ColumnHelper.join_options(
        "column.calc.price_per_unit",
        "column.suffix.difference",
    )

    # Percent diff variants
    self.spend_per_cust_pct_diff: str = ColumnHelper.join_options(
        "column.calc.spend_per_customer",
        "column.suffix.percent_difference",
    )
    self.trans_per_cust_pct_diff: str = ColumnHelper.join_options(
        "column.calc.transactions_per_customer",
        "column.suffix.percent_difference",
    )
    self.spend_per_trans_pct_diff: str = ColumnHelper.join_options(
        "column.calc.spend_per_transaction",
        "column.suffix.percent_difference",
    )
    self.units_per_trans_pct_diff: str = ColumnHelper.join_options(
        "column.calc.units_per_transaction",
        "column.suffix.percent_difference",
    )
    self.price_per_unit_pct_diff: str = ColumnHelper.join_options(
        "column.calc.price_per_unit",
        "column.suffix.percent_difference",
    )

    # Contribution variants
    self.spend_per_cust_contrib: str = ColumnHelper.join_options(
        "column.calc.spend_per_customer",
        "column.suffix.contribution",
    )
    self.trans_per_cust_contrib: str = ColumnHelper.join_options(
        "column.calc.transactions_per_customer",
        "column.suffix.contribution",
    )
    self.spend_per_trans_contrib: str = ColumnHelper.join_options(
        "column.calc.spend_per_transaction",
        "column.suffix.contribution",
    )
    self.units_per_trans_contrib: str = ColumnHelper.join_options(
        "column.calc.units_per_transaction",
        "column.suffix.contribution",
    )
    self.price_per_unit_contrib: str = ColumnHelper.join_options(
        "column.calc.price_per_unit",
        "column.suffix.contribution",
    )

    # Unknown/Total variants
    self.spend_per_trans_unknown: str = ColumnHelper.join_options(
        "column.calc.spend_per_transaction",
        "column.suffix.unknown_customer",
    )
    self.spend_per_trans_total: str = ColumnHelper.join_options(
        "column.calc.spend_per_transaction",
        "column.suffix.total",
    )
    self.price_per_unit_unknown: str = ColumnHelper.join_options(
        "column.calc.price_per_unit",
        "column.suffix.unknown_customer",
    )
    self.price_per_unit_total: str = ColumnHelper.join_options("column.calc.price_per_unit", "column.suffix.total")
    self.units_per_trans_unknown: str = ColumnHelper.join_options(
        "column.calc.units_per_transaction",
        "column.suffix.unknown_customer",
    )
    self.units_per_trans_total: str = ColumnHelper.join_options(
        "column.calc.units_per_transaction",
        "column.suffix.total",
    )

ColumnHelper

A class to help with column naming conventions.

Access patterns: - Base columns: cols.transaction_date, cols.customer_id, etc. - Aggregation columns: cols.agg.unit_spend, cols.agg.customer_id_p1, etc. - Calculated columns: cols.calc.spend_per_cust, cols.calc.price_per_unit_diff, etc.

Source code in openretailscience/options.py 
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class ColumnHelper:
    """A class to help with column naming conventions.

    Access patterns:
    - Base columns: cols.transaction_date, cols.customer_id, etc.
    - Aggregation columns: cols.agg.unit_spend, cols.agg.customer_id_p1, etc.
    - Calculated columns: cols.calc.spend_per_cust, cols.calc.price_per_unit_diff, etc.
    """

    def __init__(self) -> None:
        """Initialize column helper with base columns and nested column groups."""
        # Base columns (stay flat on ColumnHelper)
        self.transaction_date = get_option("column.transaction_date")
        self.transaction_time = get_option("column.transaction_time")
        self.customer_id = get_option("column.customer_id")
        self.transaction_id = get_option("column.transaction_id")
        self.product_id = get_option("column.product_id")
        self.store_id = get_option("column.store_id")
        self.unit_spend = get_option("column.unit_spend")
        self.unit_qty = get_option("column.unit_quantity")
        self.unit_cost = get_option("column.unit_cost")
        self.promo_unit_spend = get_option("column.promo_unit_spend")
        self.promo_unit_qty = get_option("column.promo_unit_quantity")

        # Nested column groups
        self.agg = AggColumns()
        self.calc = CalcColumns()

    @staticmethod
    def join_options(*args: str, sep: str = "_") -> str:
        """Resolve option keys to their values and join them with a separator.

        Used to build suffixed column names (e.g. period indicators ``p1``/``p2``,
        ``diff``).

        Args:
            *args (str): Option keys to resolve and join (e.g. ``"column.agg.unit_spend"``,
                ``"column.suffix.period_1"``).
            sep (str): Separator used when joining values. Defaults to ``"_"``.

        Returns:
            str: The resolved option values joined by ``sep``.
        """
        return sep.join(map(get_option, args))

__init__()

Initialize column helper with base columns and nested column groups.

Source code in openretailscience/options.py 
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def __init__(self) -> None:
    """Initialize column helper with base columns and nested column groups."""
    # Base columns (stay flat on ColumnHelper)
    self.transaction_date = get_option("column.transaction_date")
    self.transaction_time = get_option("column.transaction_time")
    self.customer_id = get_option("column.customer_id")
    self.transaction_id = get_option("column.transaction_id")
    self.product_id = get_option("column.product_id")
    self.store_id = get_option("column.store_id")
    self.unit_spend = get_option("column.unit_spend")
    self.unit_qty = get_option("column.unit_quantity")
    self.unit_cost = get_option("column.unit_cost")
    self.promo_unit_spend = get_option("column.promo_unit_spend")
    self.promo_unit_qty = get_option("column.promo_unit_quantity")

    # Nested column groups
    self.agg = AggColumns()
    self.calc = CalcColumns()

join_options(*args, sep='_') staticmethod

Resolve option keys to their values and join them with a separator.

Used to build suffixed column names (e.g. period indicators p1/p2, diff).

Parameters:

Name Type Description Default
*args str

Option keys to resolve and join (e.g. "column.agg.unit_spend", "column.suffix.period_1").

 ()
sep str

Separator used when joining values. Defaults to "_".

 '_'

Returns:

Name Type Description
str str

The resolved option values joined by sep.
Source code in openretailscience/options.py 
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@staticmethod
def join_options(*args: str, sep: str = "_") -> str:
    """Resolve option keys to their values and join them with a separator.

    Used to build suffixed column names (e.g. period indicators ``p1``/``p2``,
    ``diff``).

    Args:
        *args (str): Option keys to resolve and join (e.g. ``"column.agg.unit_spend"``,
            ``"column.suffix.period_1"``).
        sep (str): Separator used when joining values. Defaults to ``"_"``.

    Returns:
        str: The resolved option values joined by ``sep``.
    """
    return sep.join(map(get_option, args))

Options

A class to manage configurable options.

Source code in openretailscience/options.py 
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class Options:
    """A class to manage configurable options."""

    def __init__(self) -> None:
        """Initializes the options with default values."""
        self._options: dict[str, OptionTypes] = {
            # Database columns
            "column.customer_id": "customer_id",
            "column.transaction_id": "transaction_id",
            "column.transaction_date": "transaction_date",
            "column.transaction_time": "transaction_time",
            "column.product_id": "product_id",
            "column.unit_quantity": "unit_quantity",
            "column.unit_price": "unit_price",
            "column.unit_spend": "unit_spend",
            "column.unit_cost": "unit_cost",
            "column.promo_unit_spend": "promo_unit_spend",
            "column.promo_unit_quantity": "promo_unit_quantity",
            "column.store_id": "store_id",
            # Aggregation columns
            "column.agg.customer_id": "customers",
            "column.agg.transaction_id": "transactions",
            "column.agg.product_id": "products",
            "column.agg.unit_quantity": "units",
            "column.agg.unit_price": "prices",
            "column.agg.unit_spend": "spend",
            "column.agg.unit_cost": "costs",
            "column.agg.promo_unit_spend": "promo_spend",
            "column.agg.promo_unit_quantity": "promo_units",
            "column.agg.store_id": "stores",
            # Calculated columns
            "column.calc.price_per_unit": "price_per_unit",
            "column.calc.units_per_transaction": "units_per_transaction",
            "column.calc.spend_per_customer": "spend_per_customer",
            "column.calc.spend_per_transaction": "spend_per_transaction",
            "column.calc.transactions_per_customer": "transactions_per_customer",
            "column.calc.price_elasticity": "price_elasticity",
            "column.calc.frequency_elasticity": "frequency_elasticity",
            # Abbreviation suffix
            "column.suffix.count": "cnt",
            "column.suffix.percent": "pct",
            "column.suffix.difference": "diff",
            "column.suffix.percent_difference": "pct_diff",
            "column.suffix.contribution": "contrib",
            "column.suffix.period_1": "p1",
            "column.suffix.period_2": "p2",
            "column.suffix.unknown_customer": "unknown",
            "column.suffix.total": "total",
            # Performance / query optimization
            "optimization.use_native_sql": True,
            # Color palettes
            # 27-color rotation: 9 curated hues at 3 shades. First 5 hues are max-separated on the
            # hue wheel (~70 degrees apart) for 3-5 series. Order: primaries (500), lights (200),
            # darks (700).
            "plot.color.multi_color_palette": [
                COLORS[hue][shade]
                for shade in (500, 200, 700)
                for hue in ("green", "blue", "orange", "violet", "red", "cyan", "pink", "yellow", "teal")
            ],
            "plot.color.positive": COLORS["green"][500],
            "plot.color.negative": COLORS["red"][500],
            "plot.color.neutral": COLORS["gray"][500],
            # Semantic colors (`primary`, `difference`) live one shade darker than their hue's
            # categorical counterpart in `multi_color_palette` (which uses the 500-shade tier as
            # its primary set). The extra weight signals "this means something specific" vs
            # "one of N peers" — keeps the semantic role visually distinct while staying inside
            # the same Tailwind hue family.
            "plot.color.difference": COLORS["blue"][600],
            "plot.color.context": COLORS["gray"][300],
            "plot.color.primary": COLORS["green"][600],
            "plot.color.sequential": "green",
            # Chrome (eyebrow / title / subtitle / tab / source) colors
            "plot.color.eyebrow": COLORS["neutral"][500],
            "plot.color.subtitle": COLORS["neutral"][600],
            "plot.color.title": COLORS["neutral"][950],
            "plot.color.tab": COLORS["green"][600],
            "plot.color.source": COLORS["neutral"][500],
            # Plot font options
            "plot.font.title_font": "poppins_semi_bold",
            "plot.font.eyebrow_font": "poppins_semi_bold",
            "plot.font.subtitle_font": "poppins_regular",
            "plot.font.label_font": "poppins_regular",
            "plot.font.tick_font": "poppins_regular",
            "plot.font.source_font": "poppins_light_italic",
            "plot.font.data_label_font": "poppins_medium",
            "plot.font.legend_font": "poppins_regular",
            "plot.font.title_size": 22.0,
            "plot.font.eyebrow_size": 10.0,
            "plot.font.subtitle_size": 12.0,
            "plot.font.label_size": 11.0,
            "plot.font.tick_size": 10.0,
            "plot.font.source_size": 9.0,
            "plot.font.data_label_size": 10.0,
            "plot.font.legend_size": 10.0,
            # Plot spacing options
            "plot.spacing.x_label_pad": 10,
            "plot.spacing.y_label_pad": 10,
            # Plot style options
            "plot.style.background_color": "white",
            "plot.style.grid_color": COLORS["neutral"][200],
            "plot.style.grid_alpha": 1.0,
            "plot.style.show_top_spine": False,
            "plot.style.show_right_spine": False,
            "plot.style.show_bottom_spine": True,
            "plot.style.show_left_spine": True,
            "plot.style.legend_bbox_to_anchor": [1.02, 1.0],
            "plot.style.legend_loc": "upper left",
            "plot.style.cell_corner_radius": 0.05,
            "plot.style.cell_gap": 3.0,
            "plot.style.auto_rotate_x_ticks": True,
            "plot.style.auto_wrap_x_ticks": True,
            "plot.style.show_tab": True,
        }
        self._descriptions: dict[str, str] = {
            # Database columns
            "column.customer_id": "The name of the column containing customer IDs.",
            "column.transaction_id": "The name of the column containing transaction IDs.",
            "column.transaction_date": "The name of the column containing transaction dates.",
            "column.transaction_time": "The name of the column containing transaction times.",
            "column.product_id": "The name of the column containing product IDs.",
            "column.unit_quantity": "The name of the column containing the number of units sold.",
            "column.unit_price": "The name of the column containing the unit price of the product.",
            "column.unit_spend": (
                "The name of the column containing the total spend of the products in the transaction. "
                "ie, unit_price * units"
            ),
            "column.unit_cost": (
                "The name of the column containing the total cost of the products in the transaction. "
                "ie, single unit cost * units"
            ),
            "column.promo_unit_spend": (
                "The name of the column containing the total spend on promotion of the products in the transaction. "
                "ie, promotional unit price * units"
            ),
            "column.promo_unit_quantity": "The name of the column containing the number of units sold on promotion.",
            "column.store_id": "The name of the column containing store IDs of the transaction.",
            # Aggregation columns
            "column.agg.customer_id": "The name of the column containing the number of unique customers.",
            "column.agg.transaction_id": "The name of the column containing the number of transactions.",
            "column.agg.product_id": "The name of the column containing the number of unique products.",
            "column.agg.unit_quantity": "The name of the column containing the total number of units sold.",
            "column.agg.unit_price": "The name of the column containing the total unit price of products.",
            "column.agg.unit_spend": (
                "The name of the column containing the total spend of the units in the transaction."
            ),
            "column.agg.unit_cost": "The name of the column containing the total unit cost of products.",
            "column.agg.promo_unit_spend": (
                "The name of the column containing the total promotional spend of the units in the transaction."
            ),
            "column.agg.promo_unit_quantity": (
                "The name of the column containing the total number of units sold on promotion."
            ),
            "column.agg.store_id": "The name of the column containing the number of unique stores.",
            # Calculated columns
            "column.calc.price_per_unit": "The name of the column containing the price per unit.",
            "column.calc.units_per_transaction": "The name of the column containing the units per transaction.",
            "column.calc.spend_per_customer": "The name of the column containing the spend per customer.",
            "column.calc.spend_per_transaction": "The name of the column containing the spend per transaction.",
            "column.calc.transactions_per_customer": "The name of the column containing the transactions per customer.",
            "column.calc.price_elasticity": "The name of the column containing the price elasticity calculation.",
            "column.calc.frequency_elasticity": (
                "The name of the column containing the frequency elasticity calculation."
            ),
            # Abbreviation suffixes
            "column.suffix.count": "The suffix to use for count columns.",
            "column.suffix.percent": "The suffix to use for percentage columns.",
            "column.suffix.difference": "The suffix to use for difference columns.",
            "column.suffix.percent_difference": "The suffix to use for percentage difference columns.",
            "column.suffix.contribution": "The suffix to use for revenue contribution columns.",
            "column.suffix.period_1": (
                "The suffix to use for period 1 columns. Often this could represent last year for instance."
            ),
            "column.suffix.period_2": (
                "The suffix to use for period 2 columns. Often this could represent this year for instance."
            ),
            "column.suffix.unknown_customer": "The suffix to use for unknown customer columns.",
            "column.suffix.total": "The suffix to use for total columns.",
            # Performance / query optimization
            "optimization.use_native_sql": (
                "Whether to use backend-native SQL features for faster queries where supported. "
                "When False, or on backends without support, the portable fallback path is used. "
                "Results are identical either way."
            ),
            # Color options
            "plot.color.multi_color_palette": (
                "Multi-color palette for plots with many series (default: 27 Tailwind colors, "
                "9 curated hues at shades 500 / 200 / 700)."
            ),
            "plot.color.positive": "Color for positive values (e.g., gains, increases)",
            "plot.color.negative": "Color for negative values (e.g., losses, decreases)",
            "plot.color.neutral": "Color for neutral values (e.g., net amounts)",
            "plot.color.difference": "Color for difference values (e.g., waterfall transitions, tree differences)",
            "plot.color.context": "Color for de-emphasized context lines",
            "plot.color.primary": "Default color for single-series plots",
            "plot.color.sequential": (
                "Tailwind color name (e.g., 'green', 'blue') or matplotlib colormap name"
                " (e.g., 'Greens', 'viridis') for sequential ramps (heatmaps, cohort tables, period-on-period)"
            ),
            "plot.color.eyebrow": "Color for the small uppercase eyebrow text above the title.",
            "plot.color.subtitle": "Color for the subtitle text below the title.",
            "plot.color.title": "Color for the main plot title.",
            "plot.color.tab": "Color for the small rectangular tab mark above the title block.",
            "plot.color.source": "Color for the source text rendered below the plot.",
            # Plot font descriptions
            "plot.font.title_font": "The font family to use for plot titles.",
            "plot.font.eyebrow_font": "The font family to use for the eyebrow text above the title.",
            "plot.font.subtitle_font": "The font family to use for the subtitle text below the title.",
            "plot.font.label_font": "The font family to use for axis labels.",
            "plot.font.tick_font": "The font family to use for axis tick labels.",
            "plot.font.source_font": "The font family to use for source text.",
            "plot.font.data_label_font": "The font family to use for data point labels.",
            "plot.font.legend_font": "The font family to use for legend title and entry text.",
            "plot.font.title_size": "The font size for plot titles (in points).",
            "plot.font.eyebrow_size": "The font size for the eyebrow text above the title (in points).",
            "plot.font.subtitle_size": "The font size for the subtitle text (in points).",
            "plot.font.label_size": "The font size for axis labels (in points).",
            "plot.font.tick_size": "The font size for axis tick labels (in points).",
            "plot.font.source_size": "The font size for source text (in points).",
            "plot.font.data_label_size": "The font size for data point labels (in points).",
            "plot.font.legend_size": "The font size for legend entry text (in points).",
            # Plot spacing descriptions
            "plot.spacing.x_label_pad": "The padding below the x-axis label (in points).",
            "plot.spacing.y_label_pad": "The padding to the left of the y-axis label (in points).",
            # Plot style descriptions
            "plot.style.background_color": "The background color of the plot area.",
            "plot.style.grid_color": "The color of the grid lines.",
            "plot.style.grid_alpha": "The transparency of the grid lines (0.0 to 1.0).",
            "plot.style.show_top_spine": "Whether to show the top border of the plot.",
            "plot.style.show_right_spine": "Whether to show the right border of the plot.",
            "plot.style.show_bottom_spine": "Whether to show the bottom border of the plot.",
            "plot.style.show_left_spine": "Whether to show the left border of the plot.",
            "plot.style.legend_bbox_to_anchor": "The bounding box anchor for legend positioning when moved outside.",
            "plot.style.legend_loc": "The location of the legend when moved outside the plot.",
            "plot.style.cell_corner_radius": (
                "Corner radius (in cell-size data units) for cell-based plots like heatmap and cohort. "
                "Values around 0.03 give a subtle softening; larger values produce a pill-chip look."
            ),
            "plot.style.cell_gap": (
                "Width (in points) of the visual gap between adjacent cells in cell-based plots. "
                "Drawn as a background-coloured edge on each cell so the gap stays a fixed pixel size "
                "regardless of axes aspect or grid dimensions."
            ),
            "plot.style.auto_rotate_x_ticks": (
                "When True, categorical x-axis tick labels render horizontal and only rotate "
                "to 45° or 90° when neighbouring labels would overlap. When False, the rotation "
                "set by matplotlib (or pandas, for bar plots) is left unchanged."
            ),
            "plot.style.auto_wrap_x_ticks": (
                "When True, multi-word categorical x-tick labels are split onto two balanced "
                "lines before falling back to rotation when neighbours would overlap (e.g. "
                "'Camden High St' becomes 'Camden\\nHigh St'). Single-word labels are left "
                "alone and proceed straight to rotation."
            ),
            "plot.style.show_tab": (
                "When True (default), the small green tab mark renders above the title block "
                "on charts with header chrome. Set to False to suppress the tab project-wide; "
                "use ``option_context`` to scope the change to a block."
            ),
        }
        self._default_options: dict[str, OptionTypes] = self._options.copy()

    def set_option(self, pat: str, val: OptionTypes) -> None:
        """Set the value of the specified option.

        Args:
            pat: The option name.
            val: The value to set the option to.

        Raises:
            ValueError: If the option name is unknown.
        """
        if pat not in self._options:
            msg = f"Unknown option: {pat}"
            raise ValueError(msg)

        self._options[pat] = val

    def get_option(self, pat: str) -> OptionTypes:
        """Get the value of the specified option.

        Args:
            pat: The option name.

        Returns:
            The value of the option.

        Raises:
            ValueError: If the option name is unknown.
        """
        if pat in self._options:
            return self._options[pat]

        msg = f"Unknown option: {pat}"
        raise ValueError(msg)

    def reset_option(self, pat: str) -> None:
        """Reset the specified option to its default value.

        Args:
            pat: The option name.

        Raises:
            ValueError: If the option name is unknown.
        """
        if pat not in self._options:
            msg = f"Unknown option: {pat}"
            raise ValueError(msg)

        self._options[pat] = self._default_options[pat]

    def list_options(self) -> list[str]:
        """List all available options.

        Returns:
            A list of all option names.
        """
        return list(self._options.keys())

    def describe_option(self, pat: str) -> str:
        """Describe the specified option.

        Args:
            pat: The option name.

        Returns:
            A string describing the option and its current value.

        Raises:
            ValueError: If the option name is unknown.
        """
        if pat in self._descriptions:
            return f"{pat}: {self._descriptions[pat]} (current value: {self._options[pat]})"

        msg = f"Unknown option: {pat}"
        raise ValueError(msg)

    @staticmethod
    def flatten_options(k: str, v: OptionTypes, parent_key: str = "") -> dict[str, OptionTypes]:
        """Flatten nested options into a single dictionary."""
        if parent_key != "":
            parent_key += "."

        if isinstance(v, dict):
            ret_dict = {}
            for sub_key, sub_value in v.items():
                ret_dict.update(Options.flatten_options(sub_key, sub_value, parent_key=f"{parent_key}{k}"))
            return ret_dict

        return {f"{parent_key}{k}": v}

    @classmethod
    def load_from_project(cls) -> "Options":
        """Try to load options from an openretailscience.toml file in the project root directory.

        If the project root directory cannot be found, return a default Options instance.

        Returns:
            An Options instance with options loaded from the openretailscience.toml file or default
        """
        options_instance = cls()

        project_root = find_project_root()
        if project_root is None:
            return options_instance

        toml_file = Path(project_root) / "openretailscience.toml"
        if toml_file.is_file():
            return Options.load_from_toml(toml_file)

        return options_instance

    @classmethod
    def load_from_toml(cls, file_path: str) -> "Options":
        """Load options from a TOML file.

        Args:
            file_path: The path to the TOML file.

        Raises:
            ValueError: If the TOML file contains unknown options.
        """
        options_instance = cls()

        with open(file_path) as f:
            toml_data = toml.load(f)

        for section, options in toml_data.items():
            for option_name, option_value in Options.flatten_options(section, options).items():
                if option_name in options_instance._options:
                    options_instance.set_option(option_name, option_value)
                else:
                    msg = f"Unknown option in TOML file: {option_name}"
                    raise ValueError(msg)

        return options_instance

__init__()

Initializes the options with default values.

Source code in openretailscience/options.py 
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def __init__(self) -> None:
    """Initializes the options with default values."""
    self._options: dict[str, OptionTypes] = {
        # Database columns
        "column.customer_id": "customer_id",
        "column.transaction_id": "transaction_id",
        "column.transaction_date": "transaction_date",
        "column.transaction_time": "transaction_time",
        "column.product_id": "product_id",
        "column.unit_quantity": "unit_quantity",
        "column.unit_price": "unit_price",
        "column.unit_spend": "unit_spend",
        "column.unit_cost": "unit_cost",
        "column.promo_unit_spend": "promo_unit_spend",
        "column.promo_unit_quantity": "promo_unit_quantity",
        "column.store_id": "store_id",
        # Aggregation columns
        "column.agg.customer_id": "customers",
        "column.agg.transaction_id": "transactions",
        "column.agg.product_id": "products",
        "column.agg.unit_quantity": "units",
        "column.agg.unit_price": "prices",
        "column.agg.unit_spend": "spend",
        "column.agg.unit_cost": "costs",
        "column.agg.promo_unit_spend": "promo_spend",
        "column.agg.promo_unit_quantity": "promo_units",
        "column.agg.store_id": "stores",
        # Calculated columns
        "column.calc.price_per_unit": "price_per_unit",
        "column.calc.units_per_transaction": "units_per_transaction",
        "column.calc.spend_per_customer": "spend_per_customer",
        "column.calc.spend_per_transaction": "spend_per_transaction",
        "column.calc.transactions_per_customer": "transactions_per_customer",
        "column.calc.price_elasticity": "price_elasticity",
        "column.calc.frequency_elasticity": "frequency_elasticity",
        # Abbreviation suffix
        "column.suffix.count": "cnt",
        "column.suffix.percent": "pct",
        "column.suffix.difference": "diff",
        "column.suffix.percent_difference": "pct_diff",
        "column.suffix.contribution": "contrib",
        "column.suffix.period_1": "p1",
        "column.suffix.period_2": "p2",
        "column.suffix.unknown_customer": "unknown",
        "column.suffix.total": "total",
        # Performance / query optimization
        "optimization.use_native_sql": True,
        # Color palettes
        # 27-color rotation: 9 curated hues at 3 shades. First 5 hues are max-separated on the
        # hue wheel (~70 degrees apart) for 3-5 series. Order: primaries (500), lights (200),
        # darks (700).
        "plot.color.multi_color_palette": [
            COLORS[hue][shade]
            for shade in (500, 200, 700)
            for hue in ("green", "blue", "orange", "violet", "red", "cyan", "pink", "yellow", "teal")
        ],
        "plot.color.positive": COLORS["green"][500],
        "plot.color.negative": COLORS["red"][500],
        "plot.color.neutral": COLORS["gray"][500],
        # Semantic colors (`primary`, `difference`) live one shade darker than their hue's
        # categorical counterpart in `multi_color_palette` (which uses the 500-shade tier as
        # its primary set). The extra weight signals "this means something specific" vs
        # "one of N peers" — keeps the semantic role visually distinct while staying inside
        # the same Tailwind hue family.
        "plot.color.difference": COLORS["blue"][600],
        "plot.color.context": COLORS["gray"][300],
        "plot.color.primary": COLORS["green"][600],
        "plot.color.sequential": "green",
        # Chrome (eyebrow / title / subtitle / tab / source) colors
        "plot.color.eyebrow": COLORS["neutral"][500],
        "plot.color.subtitle": COLORS["neutral"][600],
        "plot.color.title": COLORS["neutral"][950],
        "plot.color.tab": COLORS["green"][600],
        "plot.color.source": COLORS["neutral"][500],
        # Plot font options
        "plot.font.title_font": "poppins_semi_bold",
        "plot.font.eyebrow_font": "poppins_semi_bold",
        "plot.font.subtitle_font": "poppins_regular",
        "plot.font.label_font": "poppins_regular",
        "plot.font.tick_font": "poppins_regular",
        "plot.font.source_font": "poppins_light_italic",
        "plot.font.data_label_font": "poppins_medium",
        "plot.font.legend_font": "poppins_regular",
        "plot.font.title_size": 22.0,
        "plot.font.eyebrow_size": 10.0,
        "plot.font.subtitle_size": 12.0,
        "plot.font.label_size": 11.0,
        "plot.font.tick_size": 10.0,
        "plot.font.source_size": 9.0,
        "plot.font.data_label_size": 10.0,
        "plot.font.legend_size": 10.0,
        # Plot spacing options
        "plot.spacing.x_label_pad": 10,
        "plot.spacing.y_label_pad": 10,
        # Plot style options
        "plot.style.background_color": "white",
        "plot.style.grid_color": COLORS["neutral"][200],
        "plot.style.grid_alpha": 1.0,
        "plot.style.show_top_spine": False,
        "plot.style.show_right_spine": False,
        "plot.style.show_bottom_spine": True,
        "plot.style.show_left_spine": True,
        "plot.style.legend_bbox_to_anchor": [1.02, 1.0],
        "plot.style.legend_loc": "upper left",
        "plot.style.cell_corner_radius": 0.05,
        "plot.style.cell_gap": 3.0,
        "plot.style.auto_rotate_x_ticks": True,
        "plot.style.auto_wrap_x_ticks": True,
        "plot.style.show_tab": True,
    }
    self._descriptions: dict[str, str] = {
        # Database columns
        "column.customer_id": "The name of the column containing customer IDs.",
        "column.transaction_id": "The name of the column containing transaction IDs.",
        "column.transaction_date": "The name of the column containing transaction dates.",
        "column.transaction_time": "The name of the column containing transaction times.",
        "column.product_id": "The name of the column containing product IDs.",
        "column.unit_quantity": "The name of the column containing the number of units sold.",
        "column.unit_price": "The name of the column containing the unit price of the product.",
        "column.unit_spend": (
            "The name of the column containing the total spend of the products in the transaction. "
            "ie, unit_price * units"
        ),
        "column.unit_cost": (
            "The name of the column containing the total cost of the products in the transaction. "
            "ie, single unit cost * units"
        ),
        "column.promo_unit_spend": (
            "The name of the column containing the total spend on promotion of the products in the transaction. "
            "ie, promotional unit price * units"
        ),
        "column.promo_unit_quantity": "The name of the column containing the number of units sold on promotion.",
        "column.store_id": "The name of the column containing store IDs of the transaction.",
        # Aggregation columns
        "column.agg.customer_id": "The name of the column containing the number of unique customers.",
        "column.agg.transaction_id": "The name of the column containing the number of transactions.",
        "column.agg.product_id": "The name of the column containing the number of unique products.",
        "column.agg.unit_quantity": "The name of the column containing the total number of units sold.",
        "column.agg.unit_price": "The name of the column containing the total unit price of products.",
        "column.agg.unit_spend": (
            "The name of the column containing the total spend of the units in the transaction."
        ),
        "column.agg.unit_cost": "The name of the column containing the total unit cost of products.",
        "column.agg.promo_unit_spend": (
            "The name of the column containing the total promotional spend of the units in the transaction."
        ),
        "column.agg.promo_unit_quantity": (
            "The name of the column containing the total number of units sold on promotion."
        ),
        "column.agg.store_id": "The name of the column containing the number of unique stores.",
        # Calculated columns
        "column.calc.price_per_unit": "The name of the column containing the price per unit.",
        "column.calc.units_per_transaction": "The name of the column containing the units per transaction.",
        "column.calc.spend_per_customer": "The name of the column containing the spend per customer.",
        "column.calc.spend_per_transaction": "The name of the column containing the spend per transaction.",
        "column.calc.transactions_per_customer": "The name of the column containing the transactions per customer.",
        "column.calc.price_elasticity": "The name of the column containing the price elasticity calculation.",
        "column.calc.frequency_elasticity": (
            "The name of the column containing the frequency elasticity calculation."
        ),
        # Abbreviation suffixes
        "column.suffix.count": "The suffix to use for count columns.",
        "column.suffix.percent": "The suffix to use for percentage columns.",
        "column.suffix.difference": "The suffix to use for difference columns.",
        "column.suffix.percent_difference": "The suffix to use for percentage difference columns.",
        "column.suffix.contribution": "The suffix to use for revenue contribution columns.",
        "column.suffix.period_1": (
            "The suffix to use for period 1 columns. Often this could represent last year for instance."
        ),
        "column.suffix.period_2": (
            "The suffix to use for period 2 columns. Often this could represent this year for instance."
        ),
        "column.suffix.unknown_customer": "The suffix to use for unknown customer columns.",
        "column.suffix.total": "The suffix to use for total columns.",
        # Performance / query optimization
        "optimization.use_native_sql": (
            "Whether to use backend-native SQL features for faster queries where supported. "
            "When False, or on backends without support, the portable fallback path is used. "
            "Results are identical either way."
        ),
        # Color options
        "plot.color.multi_color_palette": (
            "Multi-color palette for plots with many series (default: 27 Tailwind colors, "
            "9 curated hues at shades 500 / 200 / 700)."
        ),
        "plot.color.positive": "Color for positive values (e.g., gains, increases)",
        "plot.color.negative": "Color for negative values (e.g., losses, decreases)",
        "plot.color.neutral": "Color for neutral values (e.g., net amounts)",
        "plot.color.difference": "Color for difference values (e.g., waterfall transitions, tree differences)",
        "plot.color.context": "Color for de-emphasized context lines",
        "plot.color.primary": "Default color for single-series plots",
        "plot.color.sequential": (
            "Tailwind color name (e.g., 'green', 'blue') or matplotlib colormap name"
            " (e.g., 'Greens', 'viridis') for sequential ramps (heatmaps, cohort tables, period-on-period)"
        ),
        "plot.color.eyebrow": "Color for the small uppercase eyebrow text above the title.",
        "plot.color.subtitle": "Color for the subtitle text below the title.",
        "plot.color.title": "Color for the main plot title.",
        "plot.color.tab": "Color for the small rectangular tab mark above the title block.",
        "plot.color.source": "Color for the source text rendered below the plot.",
        # Plot font descriptions
        "plot.font.title_font": "The font family to use for plot titles.",
        "plot.font.eyebrow_font": "The font family to use for the eyebrow text above the title.",
        "plot.font.subtitle_font": "The font family to use for the subtitle text below the title.",
        "plot.font.label_font": "The font family to use for axis labels.",
        "plot.font.tick_font": "The font family to use for axis tick labels.",
        "plot.font.source_font": "The font family to use for source text.",
        "plot.font.data_label_font": "The font family to use for data point labels.",
        "plot.font.legend_font": "The font family to use for legend title and entry text.",
        "plot.font.title_size": "The font size for plot titles (in points).",
        "plot.font.eyebrow_size": "The font size for the eyebrow text above the title (in points).",
        "plot.font.subtitle_size": "The font size for the subtitle text (in points).",
        "plot.font.label_size": "The font size for axis labels (in points).",
        "plot.font.tick_size": "The font size for axis tick labels (in points).",
        "plot.font.source_size": "The font size for source text (in points).",
        "plot.font.data_label_size": "The font size for data point labels (in points).",
        "plot.font.legend_size": "The font size for legend entry text (in points).",
        # Plot spacing descriptions
        "plot.spacing.x_label_pad": "The padding below the x-axis label (in points).",
        "plot.spacing.y_label_pad": "The padding to the left of the y-axis label (in points).",
        # Plot style descriptions
        "plot.style.background_color": "The background color of the plot area.",
        "plot.style.grid_color": "The color of the grid lines.",
        "plot.style.grid_alpha": "The transparency of the grid lines (0.0 to 1.0).",
        "plot.style.show_top_spine": "Whether to show the top border of the plot.",
        "plot.style.show_right_spine": "Whether to show the right border of the plot.",
        "plot.style.show_bottom_spine": "Whether to show the bottom border of the plot.",
        "plot.style.show_left_spine": "Whether to show the left border of the plot.",
        "plot.style.legend_bbox_to_anchor": "The bounding box anchor for legend positioning when moved outside.",
        "plot.style.legend_loc": "The location of the legend when moved outside the plot.",
        "plot.style.cell_corner_radius": (
            "Corner radius (in cell-size data units) for cell-based plots like heatmap and cohort. "
            "Values around 0.03 give a subtle softening; larger values produce a pill-chip look."
        ),
        "plot.style.cell_gap": (
            "Width (in points) of the visual gap between adjacent cells in cell-based plots. "
            "Drawn as a background-coloured edge on each cell so the gap stays a fixed pixel size "
            "regardless of axes aspect or grid dimensions."
        ),
        "plot.style.auto_rotate_x_ticks": (
            "When True, categorical x-axis tick labels render horizontal and only rotate "
            "to 45° or 90° when neighbouring labels would overlap. When False, the rotation "
            "set by matplotlib (or pandas, for bar plots) is left unchanged."
        ),
        "plot.style.auto_wrap_x_ticks": (
            "When True, multi-word categorical x-tick labels are split onto two balanced "
            "lines before falling back to rotation when neighbours would overlap (e.g. "
            "'Camden High St' becomes 'Camden\\nHigh St'). Single-word labels are left "
            "alone and proceed straight to rotation."
        ),
        "plot.style.show_tab": (
            "When True (default), the small green tab mark renders above the title block "
            "on charts with header chrome. Set to False to suppress the tab project-wide; "
            "use ``option_context`` to scope the change to a block."
        ),
    }
    self._default_options: dict[str, OptionTypes] = self._options.copy()

describe_option(pat)

Describe the specified option.

Parameters:

Name Type Description Default
pat str

The option name.

 required

Returns:

Type Description
str

A string describing the option and its current value.

Raises:

Type Description
ValueError

If the option name is unknown.
Source code in openretailscience/options.py 
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def describe_option(self, pat: str) -> str:
    """Describe the specified option.

    Args:
        pat: The option name.

    Returns:
        A string describing the option and its current value.

    Raises:
        ValueError: If the option name is unknown.
    """
    if pat in self._descriptions:
        return f"{pat}: {self._descriptions[pat]} (current value: {self._options[pat]})"

    msg = f"Unknown option: {pat}"
    raise ValueError(msg)

flatten_options(k, v, parent_key='') staticmethod

Flatten nested options into a single dictionary.

Source code in openretailscience/options.py 
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@staticmethod
def flatten_options(k: str, v: OptionTypes, parent_key: str = "") -> dict[str, OptionTypes]:
    """Flatten nested options into a single dictionary."""
    if parent_key != "":
        parent_key += "."

    if isinstance(v, dict):
        ret_dict = {}
        for sub_key, sub_value in v.items():
            ret_dict.update(Options.flatten_options(sub_key, sub_value, parent_key=f"{parent_key}{k}"))
        return ret_dict

    return {f"{parent_key}{k}": v}

get_option(pat)

Get the value of the specified option.

Parameters:

Name Type Description Default
pat str

The option name.

 required

Returns:

Type Description
OptionTypes

The value of the option.

Raises:

Type Description
ValueError

If the option name is unknown.
Source code in openretailscience/options.py 
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def get_option(self, pat: str) -> OptionTypes:
    """Get the value of the specified option.

    Args:
        pat: The option name.

    Returns:
        The value of the option.

    Raises:
        ValueError: If the option name is unknown.
    """
    if pat in self._options:
        return self._options[pat]

    msg = f"Unknown option: {pat}"
    raise ValueError(msg)

list_options()

List all available options.

Returns:

Type Description
list[str]

A list of all option names.
Source code in openretailscience/options.py 
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def list_options(self) -> list[str]:
    """List all available options.

    Returns:
        A list of all option names.
    """
    return list(self._options.keys())

load_from_project() classmethod

Try to load options from an openretailscience.toml file in the project root directory.

If the project root directory cannot be found, return a default Options instance.

Returns:

Type Description
Options

An Options instance with options loaded from the openretailscience.toml file or default
Source code in openretailscience/options.py 
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@classmethod
def load_from_project(cls) -> "Options":
    """Try to load options from an openretailscience.toml file in the project root directory.

    If the project root directory cannot be found, return a default Options instance.

    Returns:
        An Options instance with options loaded from the openretailscience.toml file or default
    """
    options_instance = cls()

    project_root = find_project_root()
    if project_root is None:
        return options_instance

    toml_file = Path(project_root) / "openretailscience.toml"
    if toml_file.is_file():
        return Options.load_from_toml(toml_file)

    return options_instance

load_from_toml(file_path) classmethod

Load options from a TOML file.

Parameters:

Name Type Description Default
file_path str

The path to the TOML file.

 required

Raises:

Type Description
ValueError

If the TOML file contains unknown options.
Source code in openretailscience/options.py 
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@classmethod
def load_from_toml(cls, file_path: str) -> "Options":
    """Load options from a TOML file.

    Args:
        file_path: The path to the TOML file.

    Raises:
        ValueError: If the TOML file contains unknown options.
    """
    options_instance = cls()

    with open(file_path) as f:
        toml_data = toml.load(f)

    for section, options in toml_data.items():
        for option_name, option_value in Options.flatten_options(section, options).items():
            if option_name in options_instance._options:
                options_instance.set_option(option_name, option_value)
            else:
                msg = f"Unknown option in TOML file: {option_name}"
                raise ValueError(msg)

    return options_instance

reset_option(pat)

Reset the specified option to its default value.

Parameters:

Name Type Description Default
pat str

The option name.

 required

Raises:

Type Description
ValueError

If the option name is unknown.
Source code in openretailscience/options.py 
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def reset_option(self, pat: str) -> None:
    """Reset the specified option to its default value.

    Args:
        pat: The option name.

    Raises:
        ValueError: If the option name is unknown.
    """
    if pat not in self._options:
        msg = f"Unknown option: {pat}"
        raise ValueError(msg)

    self._options[pat] = self._default_options[pat]

set_option(pat, val)

Set the value of the specified option.

Parameters:

Name Type Description Default
pat str

The option name.

 required
val OptionTypes

The value to set the option to.

 required

Raises:

Type Description
ValueError

If the option name is unknown.
Source code in openretailscience/options.py 
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def set_option(self, pat: str, val: OptionTypes) -> None:
    """Set the value of the specified option.

    Args:
        pat: The option name.
        val: The value to set the option to.

    Raises:
        ValueError: If the option name is unknown.
    """
    if pat not in self._options:
        msg = f"Unknown option: {pat}"
        raise ValueError(msg)

    self._options[pat] = val

PlotStyleHelper

A class to help with plot styling options.

Access patterns: - Font options: style.title_font, style.title_size, etc. - Spacing options: style.x_label_pad, style.y_label_pad, etc. - Style options: style.background_color, style.grid_alpha, etc.

Source code in openretailscience/options.py 
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class PlotStyleHelper:
    """A class to help with plot styling options.

    Access patterns:
    - Font options: style.title_font, style.title_size, etc.
    - Spacing options: style.x_label_pad, style.y_label_pad, etc.
    - Style options: style.background_color, style.grid_alpha, etc.
    """

    def __init__(self) -> None:
        """Initialize plot style helper with font, spacing, and style options."""
        # Font options
        self.title_font: str = get_option("plot.font.title_font")
        self.eyebrow_font: str = get_option("plot.font.eyebrow_font")
        self.subtitle_font: str = get_option("plot.font.subtitle_font")
        self.label_font: str = get_option("plot.font.label_font")
        self.tick_font: str = get_option("plot.font.tick_font")
        self.source_font: str = get_option("plot.font.source_font")
        self.data_label_font: str = get_option("plot.font.data_label_font")
        self.legend_font: str = get_option("plot.font.legend_font")
        self.title_size: float = get_option("plot.font.title_size")
        self.eyebrow_size: float = get_option("plot.font.eyebrow_size")
        self.subtitle_size: float = get_option("plot.font.subtitle_size")
        self.label_size: float = get_option("plot.font.label_size")
        self.tick_size: float = get_option("plot.font.tick_size")
        self.source_size: float = get_option("plot.font.source_size")
        self.data_label_size: float = get_option("plot.font.data_label_size")
        self.legend_size: float = get_option("plot.font.legend_size")

        # Chrome colors
        self.eyebrow_color: str = get_option("plot.color.eyebrow")
        self.subtitle_color: str = get_option("plot.color.subtitle")
        self.title_color: str = get_option("plot.color.title")
        self.tab_color: str = get_option("plot.color.tab")
        self.source_color: str = get_option("plot.color.source")

        # Spacing options
        self.x_label_pad: int = get_option("plot.spacing.x_label_pad")
        self.y_label_pad: int = get_option("plot.spacing.y_label_pad")

        # Style options
        self.background_color: str = get_option("plot.style.background_color")
        self.grid_color: str = get_option("plot.style.grid_color")
        self.grid_alpha: float = get_option("plot.style.grid_alpha")
        self.show_top_spine: bool = get_option("plot.style.show_top_spine")
        self.show_right_spine: bool = get_option("plot.style.show_right_spine")
        self.show_bottom_spine: bool = get_option("plot.style.show_bottom_spine")
        self.show_left_spine: bool = get_option("plot.style.show_left_spine")
        self.legend_bbox_to_anchor: list[float] = get_option("plot.style.legend_bbox_to_anchor")
        self.legend_loc: str = get_option("plot.style.legend_loc")
        self.cell_corner_radius: float = get_option("plot.style.cell_corner_radius")
        self.cell_gap: float = get_option("plot.style.cell_gap")
        self.show_tab: bool = get_option("plot.style.show_tab")
        self.auto_rotate_x_ticks: bool = get_option("plot.style.auto_rotate_x_ticks")
        self.auto_wrap_x_ticks: bool = get_option("plot.style.auto_wrap_x_ticks")

__init__()

Initialize plot style helper with font, spacing, and style options.

Source code in openretailscience/options.py 
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def __init__(self) -> None:
    """Initialize plot style helper with font, spacing, and style options."""
    # Font options
    self.title_font: str = get_option("plot.font.title_font")
    self.eyebrow_font: str = get_option("plot.font.eyebrow_font")
    self.subtitle_font: str = get_option("plot.font.subtitle_font")
    self.label_font: str = get_option("plot.font.label_font")
    self.tick_font: str = get_option("plot.font.tick_font")
    self.source_font: str = get_option("plot.font.source_font")
    self.data_label_font: str = get_option("plot.font.data_label_font")
    self.legend_font: str = get_option("plot.font.legend_font")
    self.title_size: float = get_option("plot.font.title_size")
    self.eyebrow_size: float = get_option("plot.font.eyebrow_size")
    self.subtitle_size: float = get_option("plot.font.subtitle_size")
    self.label_size: float = get_option("plot.font.label_size")
    self.tick_size: float = get_option("plot.font.tick_size")
    self.source_size: float = get_option("plot.font.source_size")
    self.data_label_size: float = get_option("plot.font.data_label_size")
    self.legend_size: float = get_option("plot.font.legend_size")

    # Chrome colors
    self.eyebrow_color: str = get_option("plot.color.eyebrow")
    self.subtitle_color: str = get_option("plot.color.subtitle")
    self.title_color: str = get_option("plot.color.title")
    self.tab_color: str = get_option("plot.color.tab")
    self.source_color: str = get_option("plot.color.source")

    # Spacing options
    self.x_label_pad: int = get_option("plot.spacing.x_label_pad")
    self.y_label_pad: int = get_option("plot.spacing.y_label_pad")

    # Style options
    self.background_color: str = get_option("plot.style.background_color")
    self.grid_color: str = get_option("plot.style.grid_color")
    self.grid_alpha: float = get_option("plot.style.grid_alpha")
    self.show_top_spine: bool = get_option("plot.style.show_top_spine")
    self.show_right_spine: bool = get_option("plot.style.show_right_spine")
    self.show_bottom_spine: bool = get_option("plot.style.show_bottom_spine")
    self.show_left_spine: bool = get_option("plot.style.show_left_spine")
    self.legend_bbox_to_anchor: list[float] = get_option("plot.style.legend_bbox_to_anchor")
    self.legend_loc: str = get_option("plot.style.legend_loc")
    self.cell_corner_radius: float = get_option("plot.style.cell_corner_radius")
    self.cell_gap: float = get_option("plot.style.cell_gap")
    self.show_tab: bool = get_option("plot.style.show_tab")
    self.auto_rotate_x_ticks: bool = get_option("plot.style.auto_rotate_x_ticks")
    self.auto_wrap_x_ticks: bool = get_option("plot.style.auto_wrap_x_ticks")

describe_option(pat)

Describe the specified option.

Parameters:

Name Type Description Default
pat str

The option name.

 required

Returns:

Name Type Description
str str

A description of the option and its current value.

Raises:

Type Description
ValueError

If the option name is unknown.
Source code in openretailscience/options.py 
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def describe_option(pat: str) -> str:
    """Describe the specified option.

    Args:
        pat (str): The option name.

    Returns:
        str: A description of the option and its current value.

    Raises:
        ValueError: If the option name is unknown.
    """
    return _global_options.describe_option(pat)

find_project_root()

Walk up from the current working directory to find the project root.

Returns the first directory containing a .git directory or an openretailscience.toml file, or None at the filesystem root.

Source code in openretailscience/options.py 
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def find_project_root() -> str | None:
    """Walk up from the current working directory to find the project root.

    Returns the first directory containing a ``.git`` directory or an
    ``openretailscience.toml`` file, or None at the filesystem root.
    """
    current_dir = Path.cwd()

    while True:
        if (Path(current_dir / ".git")).is_dir() or (Path(current_dir / "openretailscience.toml")).is_file():
            return current_dir

        parent_dir = Path(current_dir).parent
        reached_root = parent_dir == current_dir
        if reached_root:
            return None

        current_dir = parent_dir

get_option(pat)

Get the value of the specified option.

Parameters:

Name Type Description Default
pat str

The option name.

 required

Returns:

Name Type Description
OptionTypes OptionTypes

The value of the option.

Raises:

Type Description
ValueError

If the option name is unknown.
Source code in openretailscience/options.py 
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def get_option(pat: str) -> OptionTypes:
    """Get the value of the specified option.

    Args:
        pat (str): The option name.

    Returns:
        OptionTypes: The value of the option.

    Raises:
        ValueError: If the option name is unknown.
    """
    return _global_options.get_option(pat)

list_options()

List all available options.

Returns:

Type Description
list[str]

list[str]: All option names.
Source code in openretailscience/options.py 
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def list_options() -> list[str]:
    """List all available options.

    Returns:
        list[str]: All option names.
    """
    return _global_options.list_options()

option_context(*args)

Context manager to temporarily set options.

Options may be supplied either as alternating option names and values, or as a single mapping of option names to values. Previous values are restored on exit, even if the body raises.

Parameters:

Name Type Description Default
*args OptionTypes

An even number of arguments alternating between option names and their values, or a single dict mapping option names to values.

 ()

Raises:

Type Description
ValueError

If an odd number of arguments is supplied (positional form), or if an unknown option name is supplied (either form).
Source code in openretailscience/options.py 
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@contextmanager
def option_context(*args: OptionTypes) -> Generator[None, None, None]:
    """Context manager to temporarily set options.

    Options may be supplied either as alternating option names and values, or as a
    single mapping of option names to values. Previous values are restored on exit,
    even if the body raises.

    Args:
        *args (OptionTypes): An even number of arguments alternating between option names
            and their values, or a single dict mapping option names to values.

    Raises:
        ValueError: If an odd number of arguments is supplied (positional form), or if an
            unknown option name is supplied (either form).
    """
    if len(args) == 1 and isinstance(args[0], dict):
        items = args[0].items()
    elif len(args) % 2 != 0:
        raise ValueError("The context manager requires an even number of arguments")
    else:
        items = zip(args[::2], args[1::2], strict=True)

    old_options: dict[str, OptionTypes] = {}
    try:
        for pat, val in items:
            old_options[pat] = get_option(pat)
            set_option(pat, val)
        yield
    finally:
        for pat, val in old_options.items():
            set_option(pat, val)

reset_option(pat)

Reset the specified option to its default value.

Parameters:

Name Type Description Default
pat str

The option name.

 required

Raises:

Type Description
ValueError

If the option name is unknown.
Source code in openretailscience/options.py 
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def reset_option(pat: str) -> None:
    """Reset the specified option to its default value.

    Args:
        pat (str): The option name.

    Raises:
        ValueError: If the option name is unknown.
    """
    _global_options.reset_option(pat)

set_option(pat, val)

Set the value of the specified option.

Parameters:

Name Type Description Default
pat str

The option name.

 required
val OptionTypes

The value to set the option to.

 required

Raises:

Type Description
ValueError

If the option name is unknown.
Source code in openretailscience/options.py 
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def set_option(pat: str, val: OptionTypes) -> None:
    """Set the value of the specified option.

    Args:
        pat (str): The option name.
        val (OptionTypes): The value to set the option to.

    Raises:
        ValueError: If the option name is unknown.
    """
    _global_options.set_option(pat, val)