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# sqlglot.dialects.redshift

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      1from __future__ import annotations
      2
      3import typing as t
      4
      5from sqlglot import exp, transforms
      6from sqlglot.dialects.postgres import Postgres
      7from sqlglot.helper import seq_get
      8from sqlglot.tokens import TokenType
      9
     10
     11def _json_sql(self: Postgres.Generator, expression: exp.JSONExtract | exp.JSONExtractScalar) -> str:
     12    return f'{self.sql(expression, "this")}."{expression.expression.name}"'
     13
     14
     15class Redshift(Postgres):
     16    time_format = "'YYYY-MM-DD HH:MI:SS'"
     17    time_mapping = {
     18        **Postgres.time_mapping,
     19        "MON": "%b",
     20        "HH": "%H",
     21    }
     22
     23    class Parser(Postgres.Parser):
     24        FUNCTIONS = {
     25            **Postgres.Parser.FUNCTIONS,
     26            "DATEADD": lambda args: exp.DateAdd(
     27                this=seq_get(args, 2),
     28                expression=seq_get(args, 1),
     29                unit=seq_get(args, 0),
     30            ),
     31            "DATEDIFF": lambda args: exp.DateDiff(
     32                this=seq_get(args, 2),
     33                expression=seq_get(args, 1),
     34                unit=seq_get(args, 0),
     35            ),
     36            "NVL": exp.Coalesce.from_arg_list,
     37        }
     38
     39        CONVERT_TYPE_FIRST = True
     40
     41        def _parse_types(self, check_func: bool = False) -> t.Optional[exp.Expression]:
     42            this = super()._parse_types(check_func=check_func)
     43
     44            if (
     45                isinstance(this, exp.DataType)
     46                and this.this == exp.DataType.Type.VARCHAR
     47                and this.expressions
     48                and this.expressions[0].this == exp.column("MAX")
     49            ):
     50                this.set("expressions", [exp.Var(this="MAX")])
     51
     52            return this
     53
     54    class Tokenizer(Postgres.Tokenizer):
     55        BIT_STRINGS = []
     56        HEX_STRINGS = []
     57        STRING_ESCAPES = ["\\"]
     58
     59        KEYWORDS = {
     60            **Postgres.Tokenizer.KEYWORDS,
     61            "HLLSKETCH": TokenType.HLLSKETCH,
     62            "SUPER": TokenType.SUPER,
     63            "SYSDATE": TokenType.CURRENT_TIMESTAMP,
     64            "TIME": TokenType.TIMESTAMP,
     65            "TIMETZ": TokenType.TIMESTAMPTZ,
     66            "TOP": TokenType.TOP,
     67            "UNLOAD": TokenType.COMMAND,
     68            "VARBYTE": TokenType.VARBINARY,
     69        }
     70
     71        # Redshift allows # to appear as a table identifier prefix
     72        SINGLE_TOKENS = Postgres.Tokenizer.SINGLE_TOKENS.copy()
     73        SINGLE_TOKENS.pop("#")
     74
     75    class Generator(Postgres.Generator):
     76        LOCKING_READS_SUPPORTED = False
     77        RENAME_TABLE_WITH_DB = False
     78
     79        TYPE_MAPPING = {
     80            **Postgres.Generator.TYPE_MAPPING,
     81            exp.DataType.Type.BINARY: "VARBYTE",
     82            exp.DataType.Type.VARBINARY: "VARBYTE",
     83            exp.DataType.Type.INT: "INTEGER",
     84        }
     85
     86        PROPERTIES_LOCATION = {
     87            **Postgres.Generator.PROPERTIES_LOCATION,
     88            exp.LikeProperty: exp.Properties.Location.POST_WITH,
     89        }
     90
     91        TRANSFORMS = {
     92            **Postgres.Generator.TRANSFORMS,
     93            exp.CurrentTimestamp: lambda self, e: "SYSDATE",
     94            exp.DateAdd: lambda self, e: self.func(
     95                "DATEADD", exp.var(e.text("unit") or "day"), e.expression, e.this
     96            ),
     97            exp.DateDiff: lambda self, e: self.func(
     98                "DATEDIFF", exp.var(e.text("unit") or "day"), e.expression, e.this
     99            ),
    100            exp.DistKeyProperty: lambda self, e: f"DISTKEY({e.name})",
    101            exp.DistStyleProperty: lambda self, e: self.naked_property(e),
    102            exp.JSONExtract: _json_sql,
    103            exp.JSONExtractScalar: _json_sql,
    104            exp.Select: transforms.preprocess([transforms.eliminate_distinct_on]),
    105            exp.SortKeyProperty: lambda self, e: f"{'COMPOUND ' if e.args['compound'] else ''}SORTKEY({self.format_args(*e.this)})",
    106        }
    107
    108        # Postgres maps exp.Pivot to no_pivot_sql, but Redshift support pivots
    109        TRANSFORMS.pop(exp.Pivot)
    110
    111        # Redshift uses the POW | POWER (expr1, expr2) syntax instead of expr1 ^ expr2 (postgres)
    112        TRANSFORMS.pop(exp.Pow)
    113
    114        RESERVED_KEYWORDS = {*Postgres.Generator.RESERVED_KEYWORDS, "snapshot", "type"}
    115
    116        def values_sql(self, expression: exp.Values) -> str:
    117            """
    118            Converts `VALUES...` expression into a series of unions.
    119
    120            Note: If you have a lot of unions then this will result in a large number of recursive statements to
    121            evaluate the expression. You may need to increase `sys.setrecursionlimit` to run and it can also be
    122            very slow.
    123            """
    124
    125            # The VALUES clause is still valid in an `INSERT INTO ..` statement, for example
    126            if not expression.find_ancestor(exp.From, exp.Join):
    127                return super().values_sql(expression)
    128
    129            column_names = expression.alias and expression.args["alias"].columns
    130
    131            selects = []
    132            rows = [tuple_exp.expressions for tuple_exp in expression.expressions]
    133
    134            for i, row in enumerate(rows):
    135                if i == 0 and column_names:
    136                    row = [
    137                        exp.alias_(value, column_name)
    138                        for value, column_name in zip(row, column_names)
    139                    ]
    140
    141                selects.append(exp.Select(expressions=row))
    142
    143            subquery_expression: exp.Select | exp.Union = selects[0]
    144            if len(selects) > 1:
    145                for select in selects[1:]:
    146                    subquery_expression = exp.union(subquery_expression, select, distinct=False)
    147
    148            return self.subquery_sql(subquery_expression.subquery(expression.alias))
    149
    150        def with_properties(self, properties: exp.Properties) -> str:
    151            """Redshift doesn't have `WITH` as part of their with_properties so we remove it"""
    152            return self.properties(properties, prefix=" ", suffix="")
    153
    154        def datatype_sql(self, expression: exp.DataType) -> str:
    155            """
    156            Redshift converts the `TEXT` data type to `VARCHAR(255)` by default when people more generally mean
    157            VARCHAR of max length which is `VARCHAR(max)` in Redshift. Therefore if we get a `TEXT` data type
    158            without precision we convert it to `VARCHAR(max)` and if it does have precision then we just convert
    159            `TEXT` to `VARCHAR`.
    160            """
    161            if expression.this == exp.DataType.Type.TEXT:
    162                expression = expression.copy()
    163                expression.set("this", exp.DataType.Type.VARCHAR)
    164                precision = expression.args.get("expressions")
    165
    166                if not precision:
    167                    expression.append("expressions", exp.Var(this="MAX"))
    168
    169            return super().datatype_sql(expression)

class Redshift(sqlglot.dialects.postgres.Postgres): View Source

     16class Redshift(Postgres):
     17    time_format = "'YYYY-MM-DD HH:MI:SS'"
     18    time_mapping = {
     19        **Postgres.time_mapping,
     20        "MON": "%b",
     21        "HH": "%H",
     22    }
     23
     24    class Parser(Postgres.Parser):
     25        FUNCTIONS = {
     26            **Postgres.Parser.FUNCTIONS,
     27            "DATEADD": lambda args: exp.DateAdd(
     28                this=seq_get(args, 2),
     29                expression=seq_get(args, 1),
     30                unit=seq_get(args, 0),
     31            ),
     32            "DATEDIFF": lambda args: exp.DateDiff(
     33                this=seq_get(args, 2),
     34                expression=seq_get(args, 1),
     35                unit=seq_get(args, 0),
     36            ),
     37            "NVL": exp.Coalesce.from_arg_list,
     38        }
     39
     40        CONVERT_TYPE_FIRST = True
     41
     42        def _parse_types(self, check_func: bool = False) -> t.Optional[exp.Expression]:
     43            this = super()._parse_types(check_func=check_func)
     44
     45            if (
     46                isinstance(this, exp.DataType)
     47                and this.this == exp.DataType.Type.VARCHAR
     48                and this.expressions
     49                and this.expressions[0].this == exp.column("MAX")
     50            ):
     51                this.set("expressions", [exp.Var(this="MAX")])
     52
     53            return this
     54
     55    class Tokenizer(Postgres.Tokenizer):
     56        BIT_STRINGS = []
     57        HEX_STRINGS = []
     58        STRING_ESCAPES = ["\\"]
     59
     60        KEYWORDS = {
     61            **Postgres.Tokenizer.KEYWORDS,
     62            "HLLSKETCH": TokenType.HLLSKETCH,
     63            "SUPER": TokenType.SUPER,
     64            "SYSDATE": TokenType.CURRENT_TIMESTAMP,
     65            "TIME": TokenType.TIMESTAMP,
     66            "TIMETZ": TokenType.TIMESTAMPTZ,
     67            "TOP": TokenType.TOP,
     68            "UNLOAD": TokenType.COMMAND,
     69            "VARBYTE": TokenType.VARBINARY,
     70        }
     71
     72        # Redshift allows # to appear as a table identifier prefix
     73        SINGLE_TOKENS = Postgres.Tokenizer.SINGLE_TOKENS.copy()
     74        SINGLE_TOKENS.pop("#")
     75
     76    class Generator(Postgres.Generator):
     77        LOCKING_READS_SUPPORTED = False
     78        RENAME_TABLE_WITH_DB = False
     79
     80        TYPE_MAPPING = {
     81            **Postgres.Generator.TYPE_MAPPING,
     82            exp.DataType.Type.BINARY: "VARBYTE",
     83            exp.DataType.Type.VARBINARY: "VARBYTE",
     84            exp.DataType.Type.INT: "INTEGER",
     85        }
     86
     87        PROPERTIES_LOCATION = {
     88            **Postgres.Generator.PROPERTIES_LOCATION,
     89            exp.LikeProperty: exp.Properties.Location.POST_WITH,
     90        }
     91
     92        TRANSFORMS = {
     93            **Postgres.Generator.TRANSFORMS,
     94            exp.CurrentTimestamp: lambda self, e: "SYSDATE",
     95            exp.DateAdd: lambda self, e: self.func(
     96                "DATEADD", exp.var(e.text("unit") or "day"), e.expression, e.this
     97            ),
     98            exp.DateDiff: lambda self, e: self.func(
     99                "DATEDIFF", exp.var(e.text("unit") or "day"), e.expression, e.this
    100            ),
    101            exp.DistKeyProperty: lambda self, e: f"DISTKEY({e.name})",
    102            exp.DistStyleProperty: lambda self, e: self.naked_property(e),
    103            exp.JSONExtract: _json_sql,
    104            exp.JSONExtractScalar: _json_sql,
    105            exp.Select: transforms.preprocess([transforms.eliminate_distinct_on]),
    106            exp.SortKeyProperty: lambda self, e: f"{'COMPOUND ' if e.args['compound'] else ''}SORTKEY({self.format_args(*e.this)})",
    107        }
    108
    109        # Postgres maps exp.Pivot to no_pivot_sql, but Redshift support pivots
    110        TRANSFORMS.pop(exp.Pivot)
    111
    112        # Redshift uses the POW | POWER (expr1, expr2) syntax instead of expr1 ^ expr2 (postgres)
    113        TRANSFORMS.pop(exp.Pow)
    114
    115        RESERVED_KEYWORDS = {*Postgres.Generator.RESERVED_KEYWORDS, "snapshot", "type"}
    116
    117        def values_sql(self, expression: exp.Values) -> str:
    118            """
    119            Converts `VALUES...` expression into a series of unions.
    120
    121            Note: If you have a lot of unions then this will result in a large number of recursive statements to
    122            evaluate the expression. You may need to increase `sys.setrecursionlimit` to run and it can also be
    123            very slow.
    124            """
    125
    126            # The VALUES clause is still valid in an `INSERT INTO ..` statement, for example
    127            if not expression.find_ancestor(exp.From, exp.Join):
    128                return super().values_sql(expression)
    129
    130            column_names = expression.alias and expression.args["alias"].columns
    131
    132            selects = []
    133            rows = [tuple_exp.expressions for tuple_exp in expression.expressions]
    134
    135            for i, row in enumerate(rows):
    136                if i == 0 and column_names:
    137                    row = [
    138                        exp.alias_(value, column_name)
    139                        for value, column_name in zip(row, column_names)
    140                    ]
    141
    142                selects.append(exp.Select(expressions=row))
    143
    144            subquery_expression: exp.Select | exp.Union = selects[0]
    145            if len(selects) > 1:
    146                for select in selects[1:]:
    147                    subquery_expression = exp.union(subquery_expression, select, distinct=False)
    148
    149            return self.subquery_sql(subquery_expression.subquery(expression.alias))
    150
    151        def with_properties(self, properties: exp.Properties) -> str:
    152            """Redshift doesn't have `WITH` as part of their with_properties so we remove it"""
    153            return self.properties(properties, prefix=" ", suffix="")
    154
    155        def datatype_sql(self, expression: exp.DataType) -> str:
    156            """
    157            Redshift converts the `TEXT` data type to `VARCHAR(255)` by default when people more generally mean
    158            VARCHAR of max length which is `VARCHAR(max)` in Redshift. Therefore if we get a `TEXT` data type
    159            without precision we convert it to `VARCHAR(max)` and if it does have precision then we just convert
    160            `TEXT` to `VARCHAR`.
    161            """
    162            if expression.this == exp.DataType.Type.TEXT:
    163                expression = expression.copy()
    164                expression.set("this", exp.DataType.Type.VARCHAR)
    165                precision = expression.args.get("expressions")
    166
    167                if not precision:
    168                    expression.append("expressions", exp.Var(this="MAX"))
    169
    170            return super().datatype_sql(expression)

##### Inherited Members

sqlglot.dialects.dialect.Dialect
  get_or_raise
  format_time
  parse
  parse_into
  generate
  transpile
  tokenize
  parser
  generator

class Redshift.Parser(sqlglot.dialects.postgres.Postgres.Parser): View Source

    24    class Parser(Postgres.Parser):
    25        FUNCTIONS = {
    26            **Postgres.Parser.FUNCTIONS,
    27            "DATEADD": lambda args: exp.DateAdd(
    28                this=seq_get(args, 2),
    29                expression=seq_get(args, 1),
    30                unit=seq_get(args, 0),
    31            ),
    32            "DATEDIFF": lambda args: exp.DateDiff(
    33                this=seq_get(args, 2),
    34                expression=seq_get(args, 1),
    35                unit=seq_get(args, 0),
    36            ),
    37            "NVL": exp.Coalesce.from_arg_list,
    38        }
    39
    40        CONVERT_TYPE_FIRST = True
    41
    42        def _parse_types(self, check_func: bool = False) -> t.Optional[exp.Expression]:
    43            this = super()._parse_types(check_func=check_func)
    44
    45            if (
    46                isinstance(this, exp.DataType)
    47                and this.this == exp.DataType.Type.VARCHAR
    48                and this.expressions
    49                and this.expressions[0].this == exp.column("MAX")
    50            ):
    51                this.set("expressions", [exp.Var(this="MAX")])
    52
    53            return this

Parser consumes a list of tokens produced by the `sqlglot.tokens.Tokenizer` and produces a parsed syntax tree.

###### Arguments:

- error_level: the desired error level. Default: ErrorLevel.RAISE
- error_message_context: determines the amount of context to capture from a query string when displaying the error message (in number of characters). Default: 50.
- index_offset: Index offset for arrays eg ARRAY[0] vs ARRAY[1] as the head of a list. Default: 0
- alias_post_tablesample: If the table alias comes after tablesample. Default: False
- max_errors: Maximum number of error messages to include in a raised ParseError. This is only relevant if error_level is ErrorLevel.RAISE. Default: 3
- null_ordering: Indicates the default null ordering method to use if not explicitly set. Options are "nulls_are_small", "nulls_are_large", "nulls_are_last". Default: "nulls_are_small"

##### Inherited Members

sqlglot.parser.Parser
  Parser
  reset
  parse
  parse_into
  check_errors
  raise_error
  expression
  validate_expression

class Redshift.Tokenizer(sqlglot.dialects.postgres.Postgres.Tokenizer): View Source

    55    class Tokenizer(Postgres.Tokenizer):
    56        BIT_STRINGS = []
    57        HEX_STRINGS = []
    58        STRING_ESCAPES = ["\\"]
    59
    60        KEYWORDS = {
    61            **Postgres.Tokenizer.KEYWORDS,
    62            "HLLSKETCH": TokenType.HLLSKETCH,
    63            "SUPER": TokenType.SUPER,
    64            "SYSDATE": TokenType.CURRENT_TIMESTAMP,
    65            "TIME": TokenType.TIMESTAMP,
    66            "TIMETZ": TokenType.TIMESTAMPTZ,
    67            "TOP": TokenType.TOP,
    68            "UNLOAD": TokenType.COMMAND,
    69            "VARBYTE": TokenType.VARBINARY,
    70        }
    71
    72        # Redshift allows # to appear as a table identifier prefix
    73        SINGLE_TOKENS = Postgres.Tokenizer.SINGLE_TOKENS.copy()
    74        SINGLE_TOKENS.pop("#")

##### Inherited Members

sqlglot.tokens.Tokenizer
  reset
  tokenize

class Redshift.Generator(sqlglot.dialects.postgres.Postgres.Generator): View Source

     76    class Generator(Postgres.Generator):
     77        LOCKING_READS_SUPPORTED = False
     78        RENAME_TABLE_WITH_DB = False
     79
     80        TYPE_MAPPING = {
     81            **Postgres.Generator.TYPE_MAPPING,
     82            exp.DataType.Type.BINARY: "VARBYTE",
     83            exp.DataType.Type.VARBINARY: "VARBYTE",
     84            exp.DataType.Type.INT: "INTEGER",
     85        }
     86
     87        PROPERTIES_LOCATION = {
     88            **Postgres.Generator.PROPERTIES_LOCATION,
     89            exp.LikeProperty: exp.Properties.Location.POST_WITH,
     90        }
     91
     92        TRANSFORMS = {
     93            **Postgres.Generator.TRANSFORMS,
     94            exp.CurrentTimestamp: lambda self, e: "SYSDATE",
     95            exp.DateAdd: lambda self, e: self.func(
     96                "DATEADD", exp.var(e.text("unit") or "day"), e.expression, e.this
     97            ),
     98            exp.DateDiff: lambda self, e: self.func(
     99                "DATEDIFF", exp.var(e.text("unit") or "day"), e.expression, e.this
    100            ),
    101            exp.DistKeyProperty: lambda self, e: f"DISTKEY({e.name})",
    102            exp.DistStyleProperty: lambda self, e: self.naked_property(e),
    103            exp.JSONExtract: _json_sql,
    104            exp.JSONExtractScalar: _json_sql,
    105            exp.Select: transforms.preprocess([transforms.eliminate_distinct_on]),
    106            exp.SortKeyProperty: lambda self, e: f"{'COMPOUND ' if e.args['compound'] else ''}SORTKEY({self.format_args(*e.this)})",
    107        }
    108
    109        # Postgres maps exp.Pivot to no_pivot_sql, but Redshift support pivots
    110        TRANSFORMS.pop(exp.Pivot)
    111
    112        # Redshift uses the POW | POWER (expr1, expr2) syntax instead of expr1 ^ expr2 (postgres)
    113        TRANSFORMS.pop(exp.Pow)
    114
    115        RESERVED_KEYWORDS = {*Postgres.Generator.RESERVED_KEYWORDS, "snapshot", "type"}
    116
    117        def values_sql(self, expression: exp.Values) -> str:
    118            """
    119            Converts `VALUES...` expression into a series of unions.
    120
    121            Note: If you have a lot of unions then this will result in a large number of recursive statements to
    122            evaluate the expression. You may need to increase `sys.setrecursionlimit` to run and it can also be
    123            very slow.
    124            """
    125
    126            # The VALUES clause is still valid in an `INSERT INTO ..` statement, for example
    127            if not expression.find_ancestor(exp.From, exp.Join):
    128                return super().values_sql(expression)
    129
    130            column_names = expression.alias and expression.args["alias"].columns
    131
    132            selects = []
    133            rows = [tuple_exp.expressions for tuple_exp in expression.expressions]
    134
    135            for i, row in enumerate(rows):
    136                if i == 0 and column_names:
    137                    row = [
    138                        exp.alias_(value, column_name)
    139                        for value, column_name in zip(row, column_names)
    140                    ]
    141
    142                selects.append(exp.Select(expressions=row))
    143
    144            subquery_expression: exp.Select | exp.Union = selects[0]
    145            if len(selects) > 1:
    146                for select in selects[1:]:
    147                    subquery_expression = exp.union(subquery_expression, select, distinct=False)
    148
    149            return self.subquery_sql(subquery_expression.subquery(expression.alias))
    150
    151        def with_properties(self, properties: exp.Properties) -> str:
    152            """Redshift doesn't have `WITH` as part of their with_properties so we remove it"""
    153            return self.properties(properties, prefix=" ", suffix="")
    154
    155        def datatype_sql(self, expression: exp.DataType) -> str:
    156            """
    157            Redshift converts the `TEXT` data type to `VARCHAR(255)` by default when people more generally mean
    158            VARCHAR of max length which is `VARCHAR(max)` in Redshift. Therefore if we get a `TEXT` data type
    159            without precision we convert it to `VARCHAR(max)` and if it does have precision then we just convert
    160            `TEXT` to `VARCHAR`.
    161            """
    162            if expression.this == exp.DataType.Type.TEXT:
    163                expression = expression.copy()
    164                expression.set("this", exp.DataType.Type.VARCHAR)
    165                precision = expression.args.get("expressions")
    166
    167                if not precision:
    168                    expression.append("expressions", exp.Var(this="MAX"))
    169
    170            return super().datatype_sql(expression)

Generator interprets the given syntax tree and produces a SQL string as an output.

###### Arguments:

- time_mapping (dict): the dictionary of custom time mappings in which the key represents a python time format and the output the target time format
- time_trie (trie): a trie of the time_mapping keys
- pretty (bool): if set to True the returned string will be formatted. Default: False.
- quote_start (str): specifies which starting character to use to delimit quotes. Default: '.
- quote_end (str): specifies which ending character to use to delimit quotes. Default: '.
- identifier_start (str): specifies which starting character to use to delimit identifiers. Default: ".
- identifier_end (str): specifies which ending character to use to delimit identifiers. Default: ".
- bit_start (str): specifies which starting character to use to delimit bit literals. Default: None.
- bit_end (str): specifies which ending character to use to delimit bit literals. Default: None.
- hex_start (str): specifies which starting character to use to delimit hex literals. Default: None.
- hex_end (str): specifies which ending character to use to delimit hex literals. Default: None.
- byte_start (str): specifies which starting character to use to delimit byte literals. Default: None.
- byte_end (str): specifies which ending character to use to delimit byte literals. Default: None.
- raw_start (str): specifies which starting character to use to delimit raw literals. Default: None.
- raw_end (str): specifies which ending character to use to delimit raw literals. Default: None.
- identify (bool | str): 'always': always quote, 'safe': quote identifiers if they don't contain an upcase, True defaults to always.
- normalize (bool): if set to True all identifiers will lower cased
- string_escape (str): specifies a string escape character. Default: '.
- identifier_escape (str): specifies an identifier escape character. Default: ".
- pad (int): determines padding in a formatted string. Default: 2.
- indent (int): determines the size of indentation in a formatted string. Default: 4.
- unnest_column_only (bool): if true unnest table aliases are considered only as column aliases
- normalize_functions (str): normalize function names, "upper", "lower", or None Default: "upper"
- alias_post_tablesample (bool): if the table alias comes after tablesample Default: False
- unsupported_level (ErrorLevel): determines the generator's behavior when it encounters unsupported expressions. Default ErrorLevel.WARN.
- null_ordering (str): Indicates the default null ordering method to use if not explicitly set. Options are "nulls_are_small", "nulls_are_large", "nulls_are_last". Default: "nulls_are_small"
- max_unsupported (int): Maximum number of unsupported messages to include in a raised UnsupportedError. This is only relevant if unsupported_level is ErrorLevel.RAISE. Default: 3
- leading_comma (bool): if the the comma is leading or trailing in select statements Default: False
- max_text_width: The max number of characters in a segment before creating new lines in pretty mode. The default is on the smaller end because the length only represents a segment and not the true line length. Default: 80
- comments: Whether or not to preserve comments in the output SQL code. Default: True

def values_sql(self, expression: sqlglot.expressions.Values) -> str: View Source

    117        def values_sql(self, expression: exp.Values) -> str:
    118            """
    119            Converts `VALUES...` expression into a series of unions.
    120
    121            Note: If you have a lot of unions then this will result in a large number of recursive statements to
    122            evaluate the expression. You may need to increase `sys.setrecursionlimit` to run and it can also be
    123            very slow.
    124            """
    125
    126            # The VALUES clause is still valid in an `INSERT INTO ..` statement, for example
    127            if not expression.find_ancestor(exp.From, exp.Join):
    128                return super().values_sql(expression)
    129
    130            column_names = expression.alias and expression.args["alias"].columns
    131
    132            selects = []
    133            rows = [tuple_exp.expressions for tuple_exp in expression.expressions]
    134
    135            for i, row in enumerate(rows):
    136                if i == 0 and column_names:
    137                    row = [
    138                        exp.alias_(value, column_name)
    139                        for value, column_name in zip(row, column_names)
    140                    ]
    141
    142                selects.append(exp.Select(expressions=row))
    143
    144            subquery_expression: exp.Select | exp.Union = selects[0]
    145            if len(selects) > 1:
    146                for select in selects[1:]:
    147                    subquery_expression = exp.union(subquery_expression, select, distinct=False)
    148
    149            return self.subquery_sql(subquery_expression.subquery(expression.alias))

Converts `VALUES...` expression into a series of unions.

Note: If you have a lot of unions then this will result in a large number of recursive statements to evaluate the expression. You may need to increase `sys.setrecursionlimit` to run and it can also be very slow.

def with_properties(self, properties: sqlglot.expressions.Properties) -> str: View Source

    151        def with_properties(self, properties: exp.Properties) -> str:
    152            """Redshift doesn't have `WITH` as part of their with_properties so we remove it"""
    153            return self.properties(properties, prefix=" ", suffix="")

Redshift doesn't have `WITH` as part of their with_properties so we remove it

def datatype_sql(self, expression: sqlglot.expressions.DataType) -> str: View Source

    155        def datatype_sql(self, expression: exp.DataType) -> str:
    156            """
    157            Redshift converts the `TEXT` data type to `VARCHAR(255)` by default when people more generally mean
    158            VARCHAR of max length which is `VARCHAR(max)` in Redshift. Therefore if we get a `TEXT` data type
    159            without precision we convert it to `VARCHAR(max)` and if it does have precision then we just convert
    160            `TEXT` to `VARCHAR`.
    161            """
    162            if expression.this == exp.DataType.Type.TEXT:
    163                expression = expression.copy()
    164                expression.set("this", exp.DataType.Type.VARCHAR)
    165                precision = expression.args.get("expressions")
    166
    167                if not precision:
    168                    expression.append("expressions", exp.Var(this="MAX"))
    169
    170            return super().datatype_sql(expression)

Redshift converts the `TEXT` data type to `VARCHAR(255)` by default when people more generally mean VARCHAR of max length which is `VARCHAR(max)` in Redshift. Therefore if we get a `TEXT` data type without precision we convert it to `VARCHAR(max)` and if it does have precision then we just convert `TEXT` to `VARCHAR`.

##### Inherited Members

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