def infer_literal_type(value):
import ibis.expr.rules as rules
if value is None or value is null:
return dt.null
elif isinstance(value, bool):
return dt.boolean
elif isinstance(value, compat.integer_types):
return rules.int_literal_class(value)
elif isinstance(value, float):
return dt.double
elif isinstance(value, six.string_types):
return dt.string
elif isinstance(value, datetime.datetime):
return dt.timestamp
elif isinstance(value, datetime.date):
return dt.date
elif isinstance(value, datetime.time):
return dt.time
elif isinstance(value, list):
if not value:
return dt.Array(dt.any)
return dt.Array(
rules.highest_precedence_type(list(map(literal, value))))
raise com.InputTypeError(value)
def output_type(self):
import ibis.expr.rules as rules
value = self.value
if isinstance(value, bool):
return BooleanScalar
elif isinstance(value, compat.integer_types):
return rules.int_literal_class(value).scalar_type()
elif isinstance(value, float):
return DoubleScalar
elif isinstance(value, six.string_types):
return StringScalar
elif isinstance(value, datetime.datetime):
return TimestampScalar
elif isinstance(value, datetime.date):
return DateScalar
elif isinstance(value, list):
value_type = rules.highest_precedence_type(
list(map(literal, value))
)
return lambda value, value_type=value_type: ArrayScalar(
value, dt.Array(value_type)
)
raise com.InputTypeError(value)
def add_column(self, expr, name=None):
"""
Add indicated column expression to table, producing a new table. Note:
this is a shortcut for performing a projection having the same effect.
Returns
-------
modified_table : TableExpr
"""
if not isinstance(expr, ArrayExpr):
raise com.InputTypeError('Must pass array expression')
if name is not None:
expr = expr.name(name)
return self.projection([self, expr])
def output_type(self):
import ibis.expr.rules as rules
if isinstance(self.value, bool):
klass = BooleanScalar
elif isinstance(self.value, (int, long)):
int_type = rules.int_literal_class(self.value)
klass = int_type.scalar_type()
elif isinstance(self.value, float):
klass = DoubleScalar
elif isinstance(self.value, six.string_types):
klass = StringScalar
elif isinstance(self.value, datetime.datetime):
klass = TimestampScalar
else:
raise com.InputTypeError(self.value)
return klass
def infer_literal_type(value):
import ibis.expr.rules as rules
if value is None or value is null:
return dt.null
elif isinstance(value, bool):
return dt.boolean
elif isinstance(value, compat.integer_types):
return rules.int_literal_class(value)
elif isinstance(value, float):
return dt.double
elif isinstance(value, six.string_types):
return dt.string
elif isinstance(value, datetime.timedelta):
return dt.interval
elif isinstance(value, datetime.datetime):
return dt.timestamp
elif isinstance(value, datetime.date):
return dt.date
elif isinstance(value, datetime.time):
return dt.time
elif isinstance(value, list):
if not value:
return dt.Array(dt.null)
return dt.Array(
rules.highest_precedence_type(list(map(literal, value))))
elif isinstance(value, collections.OrderedDict):
if not value:
raise TypeError('Empty struct type not supported')
return dt.Struct(
list(value.keys()),
[literal(element).type() for element in value.values()],
)
elif isinstance(value, dict):
if not value:
return dt.Map(dt.null, dt.null)
return dt.Map(
rules.highest_precedence_type(list(map(literal, value.keys()))),
rules.highest_precedence_type(list(map(literal, value.values()))),
)
raise com.InputTypeError(value)
def infer_dtype_default(value):
raise com.InputTypeError(value)
def infer_dtype_default(value: GenericAny) -> DataType:
"""Default implementation of :func:`~ibis.expr.datatypes.infer`."""
raise com.InputTypeError(value)
