sqlglot.dialects API documentation

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## Dialects

While there is a SQL standard, most SQL engines support a variation of that standard. This makes it difficult to write portable SQL code. SQLGlot bridges all the different variations, called "dialects", with an extensible SQL transpilation framework.

The base `sqlglot.dialects.dialect.Dialect` class implements a generic dialect that aims to be as universal as possible.

Each SQL variation has its own `Dialect` subclass, extending the corresponding `Tokenizer`, `Parser` and `Generator` classes as needed.

### Implementing a custom Dialect

Consider the following example:

    from sqlglot import exp
    from sqlglot.dialects.dialect import Dialect
    from sqlglot.generator import Generator
    from sqlglot.tokens import Tokenizer, TokenType

    class Custom(Dialect):
        class Tokenizer(Tokenizer):
            QUOTES = ["'", '"']
            IDENTIFIERS = ["`"]

            KEYWORDS = {
                **Tokenizer.KEYWORDS,
                "INT64": TokenType.BIGINT,
                "FLOAT64": TokenType.DOUBLE,
            }

        class Generator(Generator):
            TRANSFORMS = {exp.Array: lambda self, e: f"[{self.expressions(e)}]"}

            TYPE_MAPPING = {
                exp.DataType.Type.TINYINT: "INT64",
                exp.DataType.Type.SMALLINT: "INT64",
                exp.DataType.Type.INT: "INT64",
                exp.DataType.Type.BIGINT: "INT64",
                exp.DataType.Type.DECIMAL: "NUMERIC",
                exp.DataType.Type.FLOAT: "FLOAT64",
                exp.DataType.Type.DOUBLE: "FLOAT64",
                exp.DataType.Type.BOOLEAN: "BOOL",
                exp.DataType.Type.TEXT: "STRING",
            }

This is a typical example of adding a new dialect implementation in SQLGlot: we specify its identifier and string delimiters, as well as what tokens it uses for its types and how they're associated with SQLGlot types. Since the `Expression` classes are common for each dialect supported in SQLGlot, we may also need to override the generation logic for some expressions; this is usually done by adding new entries to the `TRANSFORMS` mapping.

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     1"""
     2## Dialects
     3
     4While there is a SQL standard, most SQL engines support a variation of that standard. This makes it difficult
     5to write portable SQL code. SQLGlot bridges all the different variations, called "dialects", with an extensible
     6SQL transpilation framework.
     7
     8The base `sqlglot.dialects.dialect.Dialect` class implements a generic dialect that aims to be as universal as possible.
     9
    10Each SQL variation has its own `Dialect` subclass, extending the corresponding `Tokenizer`, `Parser` and `Generator`
    11classes as needed.
    12
    13### Implementing a custom Dialect
    14
    15Consider the following example:
    16
    17```python
    18from sqlglot import exp
    19from sqlglot.dialects.dialect import Dialect
    20from sqlglot.generator import Generator
    21from sqlglot.tokens import Tokenizer, TokenType
    22
    23
    24class Custom(Dialect):
    25    class Tokenizer(Tokenizer):
    26        QUOTES = ["'", '"']
    27        IDENTIFIERS = ["`"]
    28
    29        KEYWORDS = {
    30            **Tokenizer.KEYWORDS,
    31            "INT64": TokenType.BIGINT,
    32            "FLOAT64": TokenType.DOUBLE,
    33        }
    34
    35    class Generator(Generator):
    36        TRANSFORMS = {exp.Array: lambda self, e: f"[{self.expressions(e)}]"}
    37
    38        TYPE_MAPPING = {
    39            exp.DataType.Type.TINYINT: "INT64",
    40            exp.DataType.Type.SMALLINT: "INT64",
    41            exp.DataType.Type.INT: "INT64",
    42            exp.DataType.Type.BIGINT: "INT64",
    43            exp.DataType.Type.DECIMAL: "NUMERIC",
    44            exp.DataType.Type.FLOAT: "FLOAT64",
    45            exp.DataType.Type.DOUBLE: "FLOAT64",
    46            exp.DataType.Type.BOOLEAN: "BOOL",
    47            exp.DataType.Type.TEXT: "STRING",
    48        }
    49```
    50
    51This is a typical example of adding a new dialect implementation in SQLGlot: we specify its identifier and string
    52delimiters, as well as what tokens it uses for its types and how they're associated with SQLGlot types. Since
    53the `Expression` classes are common for each dialect supported in SQLGlot, we may also need to override the generation
    54logic for some expressions; this is usually done by adding new entries to the `TRANSFORMS` mapping.
    55
    56----
    57"""
    58
    59from sqlglot.dialects.bigquery import BigQuery
    60from sqlglot.dialects.clickhouse import ClickHouse
    61from sqlglot.dialects.databricks import Databricks
    62from sqlglot.dialects.dialect import Dialect, Dialects
    63from sqlglot.dialects.doris import Doris
    64from sqlglot.dialects.drill import Drill
    65from sqlglot.dialects.duckdb import DuckDB
    66from sqlglot.dialects.hive import Hive
    67from sqlglot.dialects.mysql import MySQL
    68from sqlglot.dialects.oracle import Oracle
    69from sqlglot.dialects.postgres import Postgres
    70from sqlglot.dialects.presto import Presto
    71from sqlglot.dialects.redshift import Redshift
    72from sqlglot.dialects.snowflake import Snowflake
    73from sqlglot.dialects.spark import Spark
    74from sqlglot.dialects.spark2 import Spark2
    75from sqlglot.dialects.sqlite import SQLite
    76from sqlglot.dialects.starrocks import StarRocks
    77from sqlglot.dialects.tableau import Tableau
    78from sqlglot.dialects.teradata import Teradata
    79from sqlglot.dialects.trino import Trino
    80from sqlglot.dialects.tsql import TSQL