from __future__ import annotations import typing as t from enum import Enum, auto from functools import reduce from sqlglot import exp from sqlglot.errors import ParseError from sqlglot.generator import Generator from sqlglot.helper import AutoName, flatten, seq_get from sqlglot.parser import Parser from sqlglot.time import TIMEZONES, format_time from sqlglot.tokens import Token, Tokenizer, TokenType from sqlglot.trie import new_trie DATE_ADD_OR_DIFF = t.Union[exp.DateAdd, exp.TsOrDsAdd, exp.DateDiff, exp.TsOrDsDiff] DATE_ADD_OR_SUB = t.Union[exp.DateAdd, exp.TsOrDsAdd, exp.DateSub] if t.TYPE_CHECKING: from sqlglot._typing import B, E class Dialects(str, Enum): """Dialects supported by SQLGLot.""" DIALECT = "" BIGQUERY = "bigquery" CLICKHOUSE = "clickhouse" DATABRICKS = "databricks" DORIS = "doris" DRILL = "drill" DUCKDB = "duckdb" HIVE = "hive" MYSQL = "mysql" ORACLE = "oracle" POSTGRES = "postgres" PRESTO = "presto" REDSHIFT = "redshift" SNOWFLAKE = "snowflake" SPARK = "spark" SPARK2 = "spark2" SQLITE = "sqlite" STARROCKS = "starrocks" TABLEAU = "tableau" TERADATA = "teradata" TRINO = "trino" TSQL = "tsql" class NormalizationStrategy(str, AutoName): """Specifies the strategy according to which identifiers should be normalized.""" LOWERCASE = auto() """Unquoted identifiers are lowercased.""" UPPERCASE = auto() """Unquoted identifiers are uppercased.""" CASE_SENSITIVE = auto() """Always case-sensitive, regardless of quotes.""" CASE_INSENSITIVE = auto() """Always case-insensitive, regardless of quotes.""" class _Dialect(type): classes: t.Dict[str, t.Type[Dialect]] = {} def __eq__(cls, other: t.Any) -> bool: if cls is other: return True if isinstance(other, str): return cls is cls.get(other) if isinstance(other, Dialect): return cls is type(other) return False def __hash__(cls) -> int: return hash(cls.__name__.lower()) @classmethod def __getitem__(cls, key: str) -> t.Type[Dialect]: return cls.classes[key] @classmethod def get( cls, key: str, default: t.Optional[t.Type[Dialect]] = None ) -> t.Optional[t.Type[Dialect]]: return cls.classes.get(key, default) def __new__(cls, clsname, bases, attrs): klass = super().__new__(cls, clsname, bases, attrs) enum = Dialects.__members__.get(clsname.upper()) cls.classes[enum.value if enum is not None else clsname.lower()] = klass klass.TIME_TRIE = new_trie(klass.TIME_MAPPING) klass.FORMAT_TRIE = ( new_trie(klass.FORMAT_MAPPING) if klass.FORMAT_MAPPING else klass.TIME_TRIE ) klass.INVERSE_TIME_MAPPING = {v: k for k, v in klass.TIME_MAPPING.items()} klass.INVERSE_TIME_TRIE = new_trie(klass.INVERSE_TIME_MAPPING) klass.INVERSE_ESCAPE_SEQUENCES = {v: k for k, v in klass.ESCAPE_SEQUENCES.items()} klass.tokenizer_class = getattr(klass, "Tokenizer", Tokenizer) klass.parser_class = getattr(klass, "Parser", Parser) klass.generator_class = getattr(klass, "Generator", Generator) klass.QUOTE_START, klass.QUOTE_END = list(klass.tokenizer_class._QUOTES.items())[0] klass.IDENTIFIER_START, klass.IDENTIFIER_END = list( klass.tokenizer_class._IDENTIFIERS.items() )[0] def get_start_end(token_type: TokenType) -> t.Tuple[t.Optional[str], t.Optional[str]]: return next( ( (s, e) for s, (e, t) in klass.tokenizer_class._FORMAT_STRINGS.items() if t == token_type ), (None, None), ) klass.BIT_START, klass.BIT_END = get_start_end(TokenType.BIT_STRING) klass.HEX_START, klass.HEX_END = get_start_end(TokenType.HEX_STRING) klass.BYTE_START, klass.BYTE_END = get_start_end(TokenType.BYTE_STRING) klass.UNICODE_START, klass.UNICODE_END = get_start_end(TokenType.UNICODE_STRING) if enum not in ("", "bigquery"): klass.generator_class.SELECT_KINDS = () if not klass.SUPPORTS_SEMI_ANTI_JOIN: klass.parser_class.TABLE_ALIAS_TOKENS = klass.parser_class.TABLE_ALIAS_TOKENS | { TokenType.ANTI, TokenType.SEMI, } return klass class Dialect(metaclass=_Dialect): INDEX_OFFSET = 0 """Determines the base index offset for arrays.""" WEEK_OFFSET = 0 """Determines the day of week of DATE_TRUNC(week). Defaults to 0 (Monday). -1 would be Sunday.""" UNNEST_COLUMN_ONLY = False """Determines whether or not `UNNEST` table aliases are treated as column aliases.""" ALIAS_POST_TABLESAMPLE = False """Determines whether or not the table alias comes after tablesample.""" TABLESAMPLE_SIZE_IS_PERCENT = False """Determines whether or not a size in the table sample clause represents percentage.""" NORMALIZATION_STRATEGY = NormalizationStrategy.LOWERCASE """Specifies the strategy according to which identifiers should be normalized.""" IDENTIFIERS_CAN_START_WITH_DIGIT = False """Determines whether or not an unquoted identifier can start with a digit.""" DPIPE_IS_STRING_CONCAT = True """Determines whether or not the DPIPE token (`||`) is a string concatenation operator.""" STRICT_STRING_CONCAT = False """Determines whether or not `CONCAT`'s arguments must be strings.""" SUPPORTS_USER_DEFINED_TYPES = True """Determines whether or not user-defined data types are supported.""" SUPPORTS_SEMI_ANTI_JOIN = True """Determines whether or not `SEMI` or `ANTI` joins are supported.""" NORMALIZE_FUNCTIONS: bool | str = "upper" """Determines how function names are going to be normalized.""" LOG_BASE_FIRST = True """Determines whether the base comes first in the `LOG` function.""" NULL_ORDERING = "nulls_are_small" """ Indicates the default `NULL` ordering method to use if not explicitly set. Possible values: `"nulls_are_small"`, `"nulls_are_large"`, `"nulls_are_last"` """ TYPED_DIVISION = False """ Whether the behavior of `a / b` depends on the types of `a` and `b`. False means `a / b` is always float division. True means `a / b` is integer division if both `a` and `b` are integers. """ SAFE_DIVISION = False """Determines whether division by zero throws an error (`False`) or returns NULL (`True`).""" CONCAT_COALESCE = False """A `NULL` arg in `CONCAT` yields `NULL` by default, but in some dialects it yields an empty string.""" DATE_FORMAT = "'%Y-%m-%d'" DATEINT_FORMAT = "'%Y%m%d'" TIME_FORMAT = "'%Y-%m-%d %H:%M:%S'" TIME_MAPPING: t.Dict[str, str] = {} """Associates this dialect's time formats with their equivalent Python `strftime` format.""" # https://cloud.google.com/bigquery/docs/reference/standard-sql/format-elements#format_model_rules_date_time # https://docs.teradata.com/r/Teradata-Database-SQL-Functions-Operators-Expressions-and-Predicates/March-2017/Data-Type-Conversions/Character-to-DATE-Conversion/Forcing-a-FORMAT-on-CAST-for-Converting-Character-to-DATE FORMAT_MAPPING: t.Dict[str, str] = {} """ Helper which is used for parsing the special syntax `CAST(x AS DATE FORMAT 'yyyy')`. If empty, the corresponding trie will be constructed off of `TIME_MAPPING`. """ ESCAPE_SEQUENCES: t.Dict[str, str] = {} """Mapping of an unescaped escape sequence to the corresponding character.""" PSEUDOCOLUMNS: t.Set[str] = set() """ Columns that are auto-generated by the engine corresponding to this dialect. For example, such columns may be excluded from `SELECT *` queries. """ PREFER_CTE_ALIAS_COLUMN = False """ Some dialects, such as Snowflake, allow you to reference a CTE column alias in the HAVING clause of the CTE. This flag will cause the CTE alias columns to override any projection aliases in the subquery. For example, WITH y(c) AS ( SELECT SUM(a) FROM (SELECT 1 a) AS x HAVING c > 0 ) SELECT c FROM y; will be rewritten as WITH y(c) AS ( SELECT SUM(a) AS c FROM (SELECT 1 AS a) AS x HAVING c > 0 ) SELECT c FROM y; """ # --- Autofilled --- tokenizer_class = Tokenizer parser_class = Parser generator_class = Generator # A trie of the time_mapping keys TIME_TRIE: t.Dict = {} FORMAT_TRIE: t.Dict = {} INVERSE_TIME_MAPPING: t.Dict[str, str] = {} INVERSE_TIME_TRIE: t.Dict = {} INVERSE_ESCAPE_SEQUENCES: t.Dict[str, str] = {} # Delimiters for quotes, identifiers and the corresponding escape characters QUOTE_START = "'" QUOTE_END = "'" IDENTIFIER_START = '"' IDENTIFIER_END = '"' # Delimiters for bit, hex, byte and unicode literals BIT_START: t.Optional[str] = None BIT_END: t.Optional[str] = None HEX_START: t.Optional[str] = None HEX_END: t.Optional[str] = None BYTE_START: t.Optional[str] = None BYTE_END: t.Optional[str] = None UNICODE_START: t.Optional[str] = None UNICODE_END: t.Optional[str] = None @classmethod def get_or_raise(cls, dialect: DialectType) -> Dialect: """ Look up a dialect in the global dialect registry and return it if it exists. Args: dialect: The target dialect. If this is a string, it can be optionally followed by additional key-value pairs that are separated by commas and are used to specify dialect settings, such as whether the dialect's identifiers are case-sensitive. Example: >>> dialect = dialect_class = get_or_raise("duckdb") >>> dialect = get_or_raise("mysql, normalization_strategy = case_sensitive") Returns: The corresponding Dialect instance. """ if not dialect: return cls() if isinstance(dialect, _Dialect): return dialect() if isinstance(dialect, Dialect): return dialect if isinstance(dialect, str): try: dialect_name, *kv_pairs = dialect.split(",") kwargs = {k.strip(): v.strip() for k, v in (kv.split("=") for kv in kv_pairs)} except ValueError: raise ValueError( f"Invalid dialect format: '{dialect}'. " "Please use the correct format: 'dialect [, k1 = v2 [, ...]]'." ) result = cls.get(dialect_name.strip()) if not result: from difflib import get_close_matches similar = seq_get(get_close_matches(dialect_name, cls.classes, n=1), 0) or "" if similar: similar = f" Did you mean {similar}?" raise ValueError(f"Unknown dialect '{dialect_name}'.{similar}") return result(**kwargs) raise ValueError(f"Invalid dialect type for '{dialect}': '{type(dialect)}'.") @classmethod def format_time( cls, expression: t.Optional[str | exp.Expression] ) -> t.Optional[exp.Expression]: """Converts a time format in this dialect to its equivalent Python `strftime` format.""" if isinstance(expression, str): return exp.Literal.string( # the time formats are quoted format_time(expression[1:-1], cls.TIME_MAPPING, cls.TIME_TRIE) ) if expression and expression.is_string: return exp.Literal.string(format_time(expression.this, cls.TIME_MAPPING, cls.TIME_TRIE)) return expression def __init__(self, **kwargs) -> None: normalization_strategy = kwargs.get("normalization_strategy") if normalization_strategy is None: self.normalization_strategy = self.NORMALIZATION_STRATEGY else: self.normalization_strategy = NormalizationStrategy(normalization_strategy.upper()) def __eq__(self, other: t.Any) -> bool: # Does not currently take dialect state into account return type(self) == other def __hash__(self) -> int: # Does not currently take dialect state into account return hash(type(self)) def normalize_identifier(self, expression: E) -> E: """ Transforms an identifier in a way that resembles how it'd be resolved by this dialect. For example, an identifier like `FoO` would be resolved as `foo` in Postgres, because it lowercases all unquoted identifiers. On the other hand, Snowflake uppercases them, so it would resolve it as `FOO`. If it was quoted, it'd need to be treated as case-sensitive, and so any normalization would be prohibited in order to avoid "breaking" the identifier. There are also dialects like Spark, which are case-insensitive even when quotes are present, and dialects like MySQL, whose resolution rules match those employed by the underlying operating system, for example they may always be case-sensitive in Linux. Finally, the normalization behavior of some engines can even be controlled through flags, like in Redshift's case, where users can explicitly set enable_case_sensitive_identifier. SQLGlot aims to understand and handle all of these different behaviors gracefully, so that it can analyze queries in the optimizer and successfully capture their semantics. """ if ( isinstance(expression, exp.Identifier) and not self.normalization_strategy is NormalizationStrategy.CASE_SENSITIVE and ( not expression.quoted or self.normalization_strategy is NormalizationStrategy.CASE_INSENSITIVE ) ): expression.set( "this", ( expression.this.upper() if self.normalization_strategy is NormalizationStrategy.UPPERCASE else expression.this.lower() ), ) return expression def case_sensitive(self, text: str) -> bool: """Checks if text contains any case sensitive characters, based on the dialect's rules.""" if self.normalization_strategy is NormalizationStrategy.CASE_INSENSITIVE: return False unsafe = ( str.islower if self.normalization_strategy is NormalizationStrategy.UPPERCASE else str.isupper ) return any(unsafe(char) for char in text) def can_identify(self, text: str, identify: str | bool = "safe") -> bool: """Checks if text can be identified given an identify option. Args: text: The text to check. identify: `"always"` or `True`: Always returns `True`. `"safe"`: Only returns `True` if the identifier is case-insensitive. Returns: Whether or not the given text can be identified. """ if identify is True or identify == "always": return True if identify == "safe": return not self.case_sensitive(text) return False def quote_identifier(self, expression: E, identify: bool = True) -> E: """ Adds quotes to a given identifier. Args: expression: The expression of interest. If it's not an `Identifier`, this method is a no-op. identify: If set to `False`, the quotes will only be added if the identifier is deemed "unsafe", with respect to its characters and this dialect's normalization strategy. """ if isinstance(expression, exp.Identifier): name = expression.this expression.set( "quoted", identify or self.case_sensitive(name) or not exp.SAFE_IDENTIFIER_RE.match(name), ) return expression def parse(self, sql: str, **opts) -> t.List[t.Optional[exp.Expression]]: return self.parser(**opts).parse(self.tokenize(sql), sql) def parse_into( self, expression_type: exp.IntoType, sql: str, **opts ) -> t.List[t.Optional[exp.Expression]]: return self.parser(**opts).parse_into(expression_type, self.tokenize(sql), sql) def generate(self, expression: exp.Expression, copy: bool = True, **opts) -> str: return self.generator(**opts).generate(expression, copy=copy) def transpile(self, sql: str, **opts) -> t.List[str]: return [ self.generate(expression, copy=False, **opts) if expression else "" for expression in self.parse(sql) ] def tokenize(self, sql: str) -> t.List[Token]: return self.tokenizer.tokenize(sql) @property def tokenizer(self) -> Tokenizer: if not hasattr(self, "_tokenizer"): self._tokenizer = self.tokenizer_class(dialect=self) return self._tokenizer def parser(self, **opts) -> Parser: return self.parser_class(dialect=self, **opts) def generator(self, **opts) -> Generator: return self.generator_class(dialect=self, **opts) DialectType = t.Union[str, Dialect, t.Type[Dialect], None] def rename_func(name: str) -> t.Callable[[Generator, exp.Expression], str]: return lambda self, expression: self.func(name, *flatten(expression.args.values())) def approx_count_distinct_sql(self: Generator, expression: exp.ApproxDistinct) -> str: if expression.args.get("accuracy"): self.unsupported("APPROX_COUNT_DISTINCT does not support accuracy") return self.func("APPROX_COUNT_DISTINCT", expression.this) def if_sql( name: str = "IF", false_value: t.Optional[exp.Expression | str] = None ) -> t.Callable[[Generator, exp.If], str]: def _if_sql(self: Generator, expression: exp.If) -> str: return self.func( name, expression.this, expression.args.get("true"), expression.args.get("false") or false_value, ) return _if_sql def arrow_json_extract_sql(self: Generator, expression: exp.JSONExtract | exp.JSONBExtract) -> str: return self.binary(expression, "->") def arrow_json_extract_scalar_sql( self: Generator, expression: exp.JSONExtractScalar | exp.JSONBExtractScalar ) -> str: return self.binary(expression, "->>") def inline_array_sql(self: Generator, expression: exp.Array) -> str: return f"[{self.expressions(expression, flat=True)}]" def no_ilike_sql(self: Generator, expression: exp.ILike) -> str: return self.like_sql( exp.Like(this=exp.Lower(this=expression.this), expression=expression.expression) ) def no_paren_current_date_sql(self: Generator, expression: exp.CurrentDate) -> str: zone = self.sql(expression, "this") return f"CURRENT_DATE AT TIME ZONE {zone}" if zone else "CURRENT_DATE" def no_recursive_cte_sql(self: Generator, expression: exp.With) -> str: if expression.args.get("recursive"): self.unsupported("Recursive CTEs are unsupported") expression.args["recursive"] = False return self.with_sql(expression) def no_safe_divide_sql(self: Generator, expression: exp.SafeDivide) -> str: n = self.sql(expression, "this") d = self.sql(expression, "expression") return f"IF(({d}) <> 0, ({n}) / ({d}), NULL)" def no_tablesample_sql(self: Generator, expression: exp.TableSample) -> str: self.unsupported("TABLESAMPLE unsupported") return self.sql(expression.this) def no_pivot_sql(self: Generator, expression: exp.Pivot) -> str: self.unsupported("PIVOT unsupported") return "" def no_trycast_sql(self: Generator, expression: exp.TryCast) -> str: return self.cast_sql(expression) def no_properties_sql(self: Generator, expression: exp.Properties) -> str: self.unsupported("Properties unsupported") return "" def no_comment_column_constraint_sql( self: Generator, expression: exp.CommentColumnConstraint ) -> str: self.unsupported("CommentColumnConstraint unsupported") return "" def no_map_from_entries_sql(self: Generator, expression: exp.MapFromEntries) -> str: self.unsupported("MAP_FROM_ENTRIES unsupported") return "" def str_position_sql(self: Generator, expression: exp.StrPosition) -> str: this = self.sql(expression, "this") substr = self.sql(expression, "substr") position = self.sql(expression, "position") if position: return f"STRPOS(SUBSTR({this}, {position}), {substr}) + {position} - 1" return f"STRPOS({this}, {substr})" def struct_extract_sql(self: Generator, expression: exp.StructExtract) -> str: return ( f"{self.sql(expression, 'this')}.{self.sql(exp.to_identifier(expression.expression.name))}" ) def var_map_sql( self: Generator, expression: exp.Map | exp.VarMap, map_func_name: str = "MAP" ) -> str: keys = expression.args["keys"] values = expression.args["values"] if not isinstance(keys, exp.Array) or not isinstance(values, exp.Array): self.unsupported("Cannot convert array columns into map.") return self.func(map_func_name, keys, values) args = [] for key, value in zip(keys.expressions, values.expressions): args.append(self.sql(key)) args.append(self.sql(value)) return self.func(map_func_name, *args) def format_time_lambda( exp_class: t.Type[E], dialect: str, default: t.Optional[bool | str] = None ) -> t.Callable[[t.List], E]: """Helper used for time expressions. Args: exp_class: the expression class to instantiate. dialect: target sql dialect. default: the default format, True being time. Returns: A callable that can be used to return the appropriately formatted time expression. """ def _format_time(args: t.List): return exp_class( this=seq_get(args, 0), format=Dialect[dialect].format_time( seq_get(args, 1) or (Dialect[dialect].TIME_FORMAT if default is True else default or None) ), ) return _format_time def time_format( dialect: DialectType = None, ) -> t.Callable[[Generator, exp.UnixToStr | exp.StrToUnix], t.Optional[str]]: def _time_format(self: Generator, expression: exp.UnixToStr | exp.StrToUnix) -> t.Optional[str]: """ Returns the time format for a given expression, unless it's equivalent to the default time format of the dialect of interest. """ time_format = self.format_time(expression) return time_format if time_format != Dialect.get_or_raise(dialect).TIME_FORMAT else None return _time_format def create_with_partitions_sql(self: Generator, expression: exp.Create) -> str: """ In Hive and Spark, the PARTITIONED BY property acts as an extension of a table's schema. When the PARTITIONED BY value is an array of column names, they are transformed into a schema. The corresponding columns are removed from the create statement. """ has_schema = isinstance(expression.this, exp.Schema) is_partitionable = expression.args.get("kind") in ("TABLE", "VIEW") if has_schema and is_partitionable: prop = expression.find(exp.PartitionedByProperty) if prop and prop.this and not isinstance(prop.this, exp.Schema): schema = expression.this columns = {v.name.upper() for v in prop.this.expressions} partitions = [col for col in schema.expressions if col.name.upper() in columns] schema.set("expressions", [e for e in schema.expressions if e not in partitions]) prop.replace(exp.PartitionedByProperty(this=exp.Schema(expressions=partitions))) expression.set("this", schema) return self.create_sql(expression) def parse_date_delta( exp_class: t.Type[E], unit_mapping: t.Optional[t.Dict[str, str]] = None ) -> t.Callable[[t.List], E]: def inner_func(args: t.List) -> E: unit_based = len(args) == 3 this = args[2] if unit_based else seq_get(args, 0) unit = args[0] if unit_based else exp.Literal.string("DAY") unit = exp.var(unit_mapping.get(unit.name.lower(), unit.name)) if unit_mapping else unit return exp_class(this=this, expression=seq_get(args, 1), unit=unit) return inner_func def parse_date_delta_with_interval( expression_class: t.Type[E], ) -> t.Callable[[t.List], t.Optional[E]]: def func(args: t.List) -> t.Optional[E]: if len(args) < 2: return None interval = args[1] if not isinstance(interval, exp.Interval): raise ParseError(f"INTERVAL expression expected but got '{interval}'") expression = interval.this if expression and expression.is_string: expression = exp.Literal.number(expression.this) return expression_class( this=args[0], expression=expression, unit=exp.Literal.string(interval.text("unit")) ) return func def date_trunc_to_time(args: t.List) -> exp.DateTrunc | exp.TimestampTrunc: unit = seq_get(args, 0) this = seq_get(args, 1) if isinstance(this, exp.Cast) and this.is_type("date"): return exp.DateTrunc(unit=unit, this=this) return exp.TimestampTrunc(this=this, unit=unit) def date_add_interval_sql( data_type: str, kind: str ) -> t.Callable[[Generator, exp.Expression], str]: def func(self: Generator, expression: exp.Expression) -> str: this = self.sql(expression, "this") unit = expression.args.get("unit") unit = exp.var(unit.name.upper() if unit else "DAY") interval = exp.Interval(this=expression.expression, unit=unit) return f"{data_type}_{kind}({this}, {self.sql(interval)})" return func def timestamptrunc_sql(self: Generator, expression: exp.TimestampTrunc) -> str: return self.func( "DATE_TRUNC", exp.Literal.string(expression.text("unit").upper() or "DAY"), expression.this ) def no_timestamp_sql(self: Generator, expression: exp.Timestamp) -> str: if not expression.expression: return self.sql(exp.cast(expression.this, to=exp.DataType.Type.TIMESTAMP)) if expression.text("expression").lower() in TIMEZONES: return self.sql( exp.AtTimeZone( this=exp.cast(expression.this, to=exp.DataType.Type.TIMESTAMP), zone=expression.expression, ) ) return self.function_fallback_sql(expression) def locate_to_strposition(args: t.List) -> exp.Expression: return exp.StrPosition( this=seq_get(args, 1), substr=seq_get(args, 0), position=seq_get(args, 2) ) def strposition_to_locate_sql(self: Generator, expression: exp.StrPosition) -> str: return self.func( "LOCATE", expression.args.get("substr"), expression.this, expression.args.get("position") ) def left_to_substring_sql(self: Generator, expression: exp.Left) -> str: return self.sql( exp.Substring( this=expression.this, start=exp.Literal.number(1), length=expression.expression ) ) def right_to_substring_sql(self: Generator, expression: exp.Left) -> str: return self.sql( exp.Substring( this=expression.this, start=exp.Length(this=expression.this) - exp.paren(expression.expression - 1), ) ) def timestrtotime_sql(self: Generator, expression: exp.TimeStrToTime) -> str: return self.sql(exp.cast(expression.this, "timestamp")) def datestrtodate_sql(self: Generator, expression: exp.DateStrToDate) -> str: return self.sql(exp.cast(expression.this, "date")) # Used for Presto and Duckdb which use functions that don't support charset, and assume utf-8 def encode_decode_sql( self: Generator, expression: exp.Expression, name: str, replace: bool = True ) -> str: charset = expression.args.get("charset") if charset and charset.name.lower() != "utf-8": self.unsupported(f"Expected utf-8 character set, got {charset}.") return self.func(name, expression.this, expression.args.get("replace") if replace else None) def min_or_least(self: Generator, expression: exp.Min) -> str: name = "LEAST" if expression.expressions else "MIN" return rename_func(name)(self, expression) def max_or_greatest(self: Generator, expression: exp.Max) -> str: name = "GREATEST" if expression.expressions else "MAX" return rename_func(name)(self, expression) def count_if_to_sum(self: Generator, expression: exp.CountIf) -> str: cond = expression.this if isinstance(expression.this, exp.Distinct): cond = expression.this.expressions[0] self.unsupported("DISTINCT is not supported when converting COUNT_IF to SUM") return self.func("sum", exp.func("if", cond, 1, 0)) def trim_sql(self: Generator, expression: exp.Trim) -> str: target = self.sql(expression, "this") trim_type = self.sql(expression, "position") remove_chars = self.sql(expression, "expression") collation = self.sql(expression, "collation") # Use TRIM/LTRIM/RTRIM syntax if the expression isn't database-specific if not remove_chars and not collation: return self.trim_sql(expression) trim_type = f"{trim_type} " if trim_type else "" remove_chars = f"{remove_chars} " if remove_chars else "" from_part = "FROM " if trim_type or remove_chars else "" collation = f" COLLATE {collation}" if collation else "" return f"TRIM({trim_type}{remove_chars}{from_part}{target}{collation})" def str_to_time_sql(self: Generator, expression: exp.Expression) -> str: return self.func("STRPTIME", expression.this, self.format_time(expression)) def concat_to_dpipe_sql(self: Generator, expression: exp.Concat) -> str: return self.sql(reduce(lambda x, y: exp.DPipe(this=x, expression=y), expression.expressions)) def concat_ws_to_dpipe_sql(self: Generator, expression: exp.ConcatWs) -> str: delim, *rest_args = expression.expressions return self.sql( reduce( lambda x, y: exp.DPipe(this=x, expression=exp.DPipe(this=delim, expression=y)), rest_args, ) ) def regexp_extract_sql(self: Generator, expression: exp.RegexpExtract) -> str: bad_args = list(filter(expression.args.get, ("position", "occurrence", "parameters"))) if bad_args: self.unsupported(f"REGEXP_EXTRACT does not support the following arg(s): {bad_args}") return self.func( "REGEXP_EXTRACT", expression.this, expression.expression, expression.args.get("group") ) def regexp_replace_sql(self: Generator, expression: exp.RegexpReplace) -> str: bad_args = list( filter(expression.args.get, ("position", "occurrence", "parameters", "modifiers")) ) if bad_args: self.unsupported(f"REGEXP_REPLACE does not support the following arg(s): {bad_args}") return self.func( "REGEXP_REPLACE", expression.this, expression.expression, expression.args["replacement"] ) def pivot_column_names(aggregations: t.List[exp.Expression], dialect: DialectType) -> t.List[str]: names = [] for agg in aggregations: if isinstance(agg, exp.Alias): names.append(agg.alias) else: """ This case corresponds to aggregations without aliases being used as suffixes (e.g. col_avg(foo)). We need to unquote identifiers because they're going to be quoted in the base parser's `_parse_pivot` method, due to `to_identifier`. Otherwise, we'd end up with `col_avg(`foo`)` (notice the double quotes). """ agg_all_unquoted = agg.transform( lambda node: ( exp.Identifier(this=node.name, quoted=False) if isinstance(node, exp.Identifier) else node ) ) names.append(agg_all_unquoted.sql(dialect=dialect, normalize_functions="lower")) return names def binary_from_function(expr_type: t.Type[B]) -> t.Callable[[t.List], B]: return lambda args: expr_type(this=seq_get(args, 0), expression=seq_get(args, 1)) # Used to represent DATE_TRUNC in Doris, Postgres and Starrocks dialects def parse_timestamp_trunc(args: t.List) -> exp.TimestampTrunc: return exp.TimestampTrunc(this=seq_get(args, 1), unit=seq_get(args, 0)) def any_value_to_max_sql(self: Generator, expression: exp.AnyValue) -> str: return self.func("MAX", expression.this) def bool_xor_sql(self: Generator, expression: exp.Xor) -> str: a = self.sql(expression.left) b = self.sql(expression.right) return f"({a} AND (NOT {b})) OR ((NOT {a}) AND {b})" def is_parse_json(expression: exp.Expression) -> bool: return isinstance(expression, exp.ParseJSON) or ( isinstance(expression, exp.Cast) and expression.is_type("json") ) def isnull_to_is_null(args: t.List) -> exp.Expression: return exp.Paren(this=exp.Is(this=seq_get(args, 0), expression=exp.null())) def generatedasidentitycolumnconstraint_sql( self: Generator, expression: exp.GeneratedAsIdentityColumnConstraint ) -> str: start = self.sql(expression, "start") or "1" increment = self.sql(expression, "increment") or "1" return f"IDENTITY({start}, {increment})" def arg_max_or_min_no_count(name: str) -> t.Callable[[Generator, exp.ArgMax | exp.ArgMin], str]: def _arg_max_or_min_sql(self: Generator, expression: exp.ArgMax | exp.ArgMin) -> str: if expression.args.get("count"): self.unsupported(f"Only two arguments are supported in function {name}.") return self.func(name, expression.this, expression.expression) return _arg_max_or_min_sql def ts_or_ds_add_cast(expression: exp.TsOrDsAdd) -> exp.TsOrDsAdd: this = expression.this.copy() return_type = expression.return_type if return_type.is_type(exp.DataType.Type.DATE): # If we need to cast to a DATE, we cast to TIMESTAMP first to make sure we # can truncate timestamp strings, because some dialects can't cast them to DATE this = exp.cast(this, exp.DataType.Type.TIMESTAMP) expression.this.replace(exp.cast(this, return_type)) return expression def date_delta_sql(name: str, cast: bool = False) -> t.Callable[[Generator, DATE_ADD_OR_DIFF], str]: def _delta_sql(self: Generator, expression: DATE_ADD_OR_DIFF) -> str: if cast and isinstance(expression, exp.TsOrDsAdd): expression = ts_or_ds_add_cast(expression) return self.func( name, exp.var(expression.text("unit").upper() or "DAY"), expression.expression, expression.this, ) return _delta_sql def prepend_dollar_to_path(expression: exp.GetPath) -> exp.GetPath: from sqlglot.optimizer.simplify import simplify # Makes sure the path will be evaluated correctly at runtime to include the path root. # For example, `[0].foo` will become `$[0].foo`, and `foo` will become `$.foo`. path = expression.expression path = exp.func( "if", exp.func("startswith", path, "'['"), exp.func("concat", "'$'", path), exp.func("concat", "'$.'", path), ) expression.expression.replace(simplify(path)) return expression def path_to_jsonpath( name: str = "JSON_EXTRACT", ) -> t.Callable[[Generator, exp.GetPath], str]: def _transform(self: Generator, expression: exp.GetPath) -> str: return rename_func(name)(self, prepend_dollar_to_path(expression)) return _transform def no_last_day_sql(self: Generator, expression: exp.LastDay) -> str: trunc_curr_date = exp.func("date_trunc", "month", expression.this) plus_one_month = exp.func("date_add", trunc_curr_date, 1, "month") minus_one_day = exp.func("date_sub", plus_one_month, 1, "day") return self.sql(exp.cast(minus_one_day, "date")) def merge_without_target_sql(self: Generator, expression: exp.Merge) -> str: """Remove table refs from columns in when statements.""" alias = expression.this.args.get("alias") normalize = lambda identifier: ( self.dialect.normalize_identifier(identifier).name if identifier else None ) targets = {normalize(expression.this.this)} if alias: targets.add(normalize(alias.this)) for when in expression.expressions: when.transform( lambda node: ( exp.column(node.this) if isinstance(node, exp.Column) and normalize(node.args.get("table")) in targets else node ), copy=False, ) return self.merge_sql(expression)