Class Numeric

lib/sqlalchemy/sql/sqltypes.py:538–669

Base for non-integer numeric types, such as ``NUMERIC``, ``FLOAT``, ``DECIMAL``, and other variants. The :class:`.Numeric` datatype when used directly will render DDL corresponding to precision numerics if available, such as ``NUMERIC(precision, scale)``. The :class:`.Float` subcla

class Numeric(NumericCommon[_N], TypeEngine[_N]):
    """Base for non-integer numeric types, such as
    ``NUMERIC``, ``FLOAT``, ``DECIMAL``, and other variants.

    The :class:`.Numeric` datatype when used directly will render DDL
    corresponding to precision numerics if available, such as
    ``NUMERIC(precision, scale)``.  The :class:`.Float` subclass will
    attempt to render a floating-point datatype such as ``FLOAT(precision)``.

    :class:`.Numeric` returns Python ``decimal.Decimal`` objects by default,
    based on the default value of ``True`` for the
    :paramref:`.Numeric.asdecimal` parameter.  If this parameter is set to
    False, returned values are coerced to Python ``float`` objects.

    The :class:`.Float` subtype, being more specific to floating point,
    defaults the :paramref:`.Float.asdecimal` flag to False so that the
    default Python datatype is ``float``.

    .. note::

        When using a :class:`.Numeric` datatype against a database type that
        returns Python floating point values to the driver, the accuracy of the
        decimal conversion indicated by :paramref:`.Numeric.asdecimal` may be
        limited.   The behavior of specific numeric/floating point datatypes
        is a product of the SQL datatype in use, the Python :term:`DBAPI`
        in use, as well as strategies that may be present within
        the SQLAlchemy dialect in use.   Users requiring specific precision/
        scale are encouraged to experiment with the available datatypes
        in order to determine the best results.

    """

    __visit_name__ = "numeric"

    @overload
    def __init__(
        self: Numeric[decimal.Decimal],
        precision: Optional[int] = ...,
        scale: Optional[int] = ...,
        decimal_return_scale: Optional[int] = ...,
        asdecimal: Literal[True] = ...,
    ): ...

    @overload
    def __init__(
        self: Numeric[float],
        precision: Optional[int] = ...,
        scale: Optional[int] = ...,
        decimal_return_scale: Optional[int] = ...,
        asdecimal: Literal[False] = ...,
    ): ...

    def __init__(
        self,
        precision: Optional[int] = None,
        scale: Optional[int] = None,
        decimal_return_scale: Optional[int] = None,
        asdecimal: bool = True,