Merging upstream version 10.5.2.
Signed-off-by: Daniel Baumann <daniel@debian.org>
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58 changed files with 1480 additions and 383 deletions
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@ -22,6 +22,7 @@ from sqlglot.helper import (
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split_num_words,
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subclasses,
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)
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from sqlglot.tokens import Token
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if t.TYPE_CHECKING:
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from sqlglot.dialects.dialect import Dialect
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@ -457,6 +458,23 @@ class Expression(metaclass=_Expression):
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assert isinstance(self, type_)
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return self
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def dump(self):
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"""
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Dump this Expression to a JSON-serializable dict.
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"""
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from sqlglot.serde import dump
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return dump(self)
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@classmethod
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def load(cls, obj):
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"""
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Load a dict (as returned by `Expression.dump`) into an Expression instance.
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"""
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from sqlglot.serde import load
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return load(obj)
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class Condition(Expression):
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def and_(self, *expressions, dialect=None, **opts):
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@ -631,11 +649,15 @@ class Create(Expression):
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"replace": False,
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"unique": False,
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"materialized": False,
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"data": False,
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"statistics": False,
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"no_primary_index": False,
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"indexes": False,
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}
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class Describe(Expression):
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pass
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arg_types = {"this": True, "kind": False}
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class Set(Expression):
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@ -731,7 +753,7 @@ class Column(Condition):
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class ColumnDef(Expression):
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arg_types = {
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"this": True,
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"kind": True,
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"kind": False,
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"constraints": False,
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"exists": False,
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}
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@ -879,7 +901,15 @@ class Identifier(Expression):
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class Index(Expression):
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arg_types = {"this": False, "table": False, "where": False, "columns": False}
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arg_types = {
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"this": False,
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"table": False,
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"where": False,
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"columns": False,
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"unique": False,
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"primary": False,
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"amp": False, # teradata
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}
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class Insert(Expression):
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@ -1361,6 +1391,7 @@ class Table(Expression):
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"laterals": False,
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"joins": False,
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"pivots": False,
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"hints": False,
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}
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@ -1818,7 +1849,12 @@ class Select(Subqueryable):
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join.this.replace(join.this.subquery())
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if join_type:
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natural: t.Optional[Token]
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side: t.Optional[Token]
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kind: t.Optional[Token]
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natural, side, kind = maybe_parse(join_type, into="JOIN_TYPE", **parse_args) # type: ignore
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if natural:
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join.set("natural", True)
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if side:
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@ -2111,6 +2147,7 @@ class DataType(Expression):
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JSON = auto()
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JSONB = auto()
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INTERVAL = auto()
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TIME = auto()
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TIMESTAMP = auto()
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TIMESTAMPTZ = auto()
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TIMESTAMPLTZ = auto()
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@ -2171,11 +2208,24 @@ class DataType(Expression):
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}
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@classmethod
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def build(cls, dtype, **kwargs) -> DataType:
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return DataType(
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this=dtype if isinstance(dtype, DataType.Type) else DataType.Type[dtype.upper()],
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**kwargs,
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)
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def build(
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cls, dtype: str | DataType.Type, dialect: t.Optional[str | Dialect] = None, **kwargs
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) -> DataType:
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from sqlglot import parse_one
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if isinstance(dtype, str):
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data_type_exp: t.Optional[Expression]
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if dtype.upper() in cls.Type.__members__:
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data_type_exp = DataType(this=DataType.Type[dtype.upper()])
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else:
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data_type_exp = parse_one(dtype, read=dialect, into=DataType)
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if data_type_exp is None:
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raise ValueError(f"Unparsable data type value: {dtype}")
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elif isinstance(dtype, DataType.Type):
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data_type_exp = DataType(this=dtype)
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else:
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raise ValueError(f"Invalid data type: {type(dtype)}. Expected str or DataType.Type")
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return DataType(**{**data_type_exp.args, **kwargs})
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# https://www.postgresql.org/docs/15/datatype-pseudo.html
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@ -2429,6 +2479,7 @@ class In(Predicate):
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"query": False,
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"unnest": False,
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"field": False,
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"is_global": False,
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}
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@ -2678,6 +2729,10 @@ class DatetimeTrunc(Func, TimeUnit):
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arg_types = {"this": True, "unit": True, "zone": False}
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class LastDateOfMonth(Func):
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pass
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class Extract(Func):
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arg_types = {"this": True, "expression": True}
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@ -2815,7 +2870,13 @@ class Length(Func):
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class Levenshtein(Func):
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arg_types = {"this": True, "expression": False}
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arg_types = {
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"this": True,
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"expression": False,
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"ins_cost": False,
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"del_cost": False,
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"sub_cost": False,
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}
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class Ln(Func):
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@ -2890,6 +2951,16 @@ class Quantile(AggFunc):
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arg_types = {"this": True, "quantile": True}
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# Clickhouse-specific:
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# https://clickhouse.com/docs/en/sql-reference/aggregate-functions/reference/quantiles/#quantiles
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class Quantiles(AggFunc):
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arg_types = {"parameters": True, "expressions": True}
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class QuantileIf(AggFunc):
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arg_types = {"parameters": True, "expressions": True}
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class ApproxQuantile(Quantile):
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arg_types = {"this": True, "quantile": True, "accuracy": False}
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@ -2962,8 +3033,10 @@ class StrToTime(Func):
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arg_types = {"this": True, "format": True}
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# Spark allows unix_timestamp()
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# https://spark.apache.org/docs/3.1.3/api/python/reference/api/pyspark.sql.functions.unix_timestamp.html
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class StrToUnix(Func):
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arg_types = {"this": True, "format": True}
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arg_types = {"this": False, "format": False}
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class NumberToStr(Func):
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@ -3131,7 +3204,7 @@ def maybe_parse(
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dialect=None,
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prefix=None,
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**opts,
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) -> t.Optional[Expression]:
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) -> Expression:
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"""Gracefully handle a possible string or expression.
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Example:
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@ -3627,11 +3700,11 @@ def to_table(sql_path: t.Optional[str | Table], **kwargs) -> t.Optional[Table]:
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if not isinstance(sql_path, str):
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raise ValueError(f"Invalid type provided for a table: {type(sql_path)}")
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catalog, db, table_name = [to_identifier(x) for x in split_num_words(sql_path, ".", 3)]
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catalog, db, table_name = (to_identifier(x) for x in split_num_words(sql_path, ".", 3))
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return Table(this=table_name, db=db, catalog=catalog, **kwargs)
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def to_column(sql_path: str, **kwargs) -> Column:
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def to_column(sql_path: str | Column, **kwargs) -> Column:
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"""
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Create a column from a `[table].[column]` sql path. Schema is optional.
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@ -3646,7 +3719,7 @@ def to_column(sql_path: str, **kwargs) -> Column:
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return sql_path
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if not isinstance(sql_path, str):
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raise ValueError(f"Invalid type provided for column: {type(sql_path)}")
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table_name, column_name = [to_identifier(x) for x in split_num_words(sql_path, ".", 2)]
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table_name, column_name = (to_identifier(x) for x in split_num_words(sql_path, ".", 2))
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return Column(this=column_name, table=table_name, **kwargs)
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@ -3748,7 +3821,7 @@ def table_(table, db=None, catalog=None, quoted=None, alias=None) -> Table:
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def values(
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values: t.Iterable[t.Tuple[t.Any, ...]],
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alias: t.Optional[str] = None,
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columns: t.Optional[t.Iterable[str]] = None,
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columns: t.Optional[t.Iterable[str] | t.Dict[str, DataType]] = None,
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) -> Values:
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"""Build VALUES statement.
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@ -3759,7 +3832,10 @@ def values(
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Args:
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values: values statements that will be converted to SQL
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alias: optional alias
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columns: Optional list of ordered column names. An alias is required when providing column names.
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columns: Optional list of ordered column names or ordered dictionary of column names to types.
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If either are provided then an alias is also required.
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If a dictionary is provided then the first column of the values will be casted to the expected type
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in order to help with type inference.
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Returns:
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Values: the Values expression object
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@ -3771,8 +3847,15 @@ def values(
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if columns
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else TableAlias(this=to_identifier(alias) if alias else None)
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)
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expressions = [convert(tup) for tup in values]
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if columns and isinstance(columns, dict):
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types = list(columns.values())
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expressions[0].set(
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"expressions",
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[Cast(this=x, to=types[i]) for i, x in enumerate(expressions[0].expressions)],
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)
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return Values(
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expressions=[convert(tup) for tup in values],
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expressions=expressions,
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alias=table_alias,
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)
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