{"id":13460267,"url":"https://github.com/tobymao/sqlglot","last_synced_at":"2025-05-13T10:51:59.219Z","repository":{"id":37001857,"uuid":"347277349","full_name":"tobymao/sqlglot","owner":"tobymao","description":"Python SQL Parser and Transpiler","archived":false,"fork":false,"pushed_at":"2025-05-05T16:38:17.000Z","size":512464,"stargazers_count":7639,"open_issues_count":1,"forks_count":842,"subscribers_count":46,"default_branch":"main","last_synced_at":"2025-05-05T20:28:51.840Z","etag":null,"topics":["bigquery","clickhouse","databricks","duckdb","hive","mysql","optimizer","parser","postgres","presto","python","redshift","snowflake","spark","sql","sqlite","sqlparser","transpiler","trino","tsql"],"latest_commit_sha":null,"homepage":"https://sqlglot.com/","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/tobymao.png","metadata":{"files":{"readme":"README.md","changelog":"CHANGELOG.md","contributing":"CONTRIBUTING.md","funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2021-03-13T05:01:56.000Z","updated_at":"2025-05-05T16:38:20.000Z","dependencies_parsed_at":"2023-10-16T06:47:41.039Z","dependency_job_id":"7337e6a2-1249-4fa0-ad83-2087f2041674","html_url":"https://github.com/tobymao/sqlglot","commit_stats":{"total_commits":4622,"total_committers":183,"mean_commits":"25.256830601092897","dds":0.6086109909130246,"last_synced_commit":"0a936bcb2c17112b6b43b61c442b37658155a943"},"previous_names":[],"tags_count":658,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tobymao%2Fsqlglot","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tobymao%2Fsqlglot/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tobymao%2Fsqlglot/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tobymao%2Fsqlglot/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/tobymao","download_url":"https://codeload.github.com/tobymao/sqlglot/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":253929155,"owners_count":21985798,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["bigquery","clickhouse","databricks","duckdb","hive","mysql","optimizer","parser","postgres","presto","python","redshift","snowflake","spark","sql","sqlite","sqlparser","transpiler","trino","tsql"],"created_at":"2024-07-31T10:00:38.393Z","updated_at":"2025-05-13T10:51:59.187Z","avatar_url":"https://github.com/tobymao.png","language":"Python","readme":"![SQLGlot logo](sqlglot.png)\n\nSQLGlot is a no-dependency SQL parser, transpiler, optimizer, and engine. It can be used to format SQL or translate between [24 different dialects](https://github.com/tobymao/sqlglot/blob/main/sqlglot/dialects/__init__.py) like [DuckDB](https://duckdb.org/), [Presto](https://prestodb.io/) / [Trino](https://trino.io/), [Spark](https://spark.apache.org/) / [Databricks](https://www.databricks.com/), [Snowflake](https://www.snowflake.com/en/), and [BigQuery](https://cloud.google.com/bigquery/). It aims to read a wide variety of SQL inputs and output syntactically and semantically correct SQL in the targeted dialects.\n\nIt is a very comprehensive generic SQL parser with a robust [test suite](https://github.com/tobymao/sqlglot/blob/main/tests/). It is also quite [performant](#benchmarks), while being written purely in Python.\n\nYou can easily [customize](#custom-dialects) the parser, [analyze](#metadata) queries, traverse expression trees, and programmatically [build](#build-and-modify-sql) SQL.\n\nSQLGlot can detect a variety of [syntax errors](#parser-errors), such as unbalanced parentheses, incorrect usage of reserved keywords, and so on. These errors are highlighted and dialect incompatibilities can warn or raise depending on configurations.\n\nLearn more about SQLGlot in the API [documentation](https://sqlglot.com/) and the expression tree [primer](https://github.com/tobymao/sqlglot/blob/main/posts/ast_primer.md).\n\nContributions are very welcome in SQLGlot; read the [contribution guide](https://github.com/tobymao/sqlglot/blob/main/CONTRIBUTING.md) and the [onboarding document](https://github.com/tobymao/sqlglot/blob/main/posts/onboarding.md) to get started!\n\n## Table of Contents\n\n* [Install](#install)\n* [Versioning](#versioning)\n* [Get in Touch](#get-in-touch)\n* [FAQ](#faq)\n* [Examples](#examples)\n   * [Formatting and Transpiling](#formatting-and-transpiling)\n   * [Metadata](#metadata)\n   * [Parser Errors](#parser-errors)\n   * [Unsupported Errors](#unsupported-errors)\n   * [Build and Modify SQL](#build-and-modify-sql)\n   * [SQL Optimizer](#sql-optimizer)\n   * [AST Introspection](#ast-introspection)\n   * [AST Diff](#ast-diff)\n   * [Custom Dialects](#custom-dialects)\n   * [SQL Execution](#sql-execution)\n* [Used By](#used-by)\n* [Documentation](#documentation)\n* [Run Tests and Lint](#run-tests-and-lint)\n* [Benchmarks](#benchmarks)\n* [Optional Dependencies](#optional-dependencies)\n\n## Install\n\nFrom PyPI:\n\n```bash\npip3 install \"sqlglot[rs]\"\n\n# Without Rust tokenizer (slower):\n# pip3 install sqlglot\n```\n\nOr with a local checkout:\n\n```\nmake install\n```\n\nRequirements for development (optional):\n\n```\nmake install-dev\n```\n\n## Versioning\n\nGiven a version number `MAJOR`.`MINOR`.`PATCH`, SQLGlot uses the following versioning strategy:\n\n- The `PATCH` version is incremented when there are backwards-compatible fixes or feature additions.\n- The `MINOR` version is incremented when there are backwards-incompatible fixes or feature additions.\n- The `MAJOR` version is incremented when there are significant backwards-incompatible fixes or feature additions.\n\n## Get in Touch\n\nWe'd love to hear from you. Join our community [Slack channel](https://tobikodata.com/slack)!\n\n## FAQ\n\nI tried to parse SQL that should be valid but it failed, why did that happen?\n\n* Most of the time, issues like this occur because the \"source\" dialect is omitted during parsing. For example, this is how to correctly parse a SQL query written in Spark SQL: `parse_one(sql, dialect=\"spark\")` (alternatively: `read=\"spark\"`). If no dialect is specified, `parse_one` will attempt to parse the query according to the \"SQLGlot dialect\", which is designed to be a superset of all supported dialects. If you tried specifying the dialect and it still doesn't work, please file an issue.\n\nI tried to output SQL but it's not in the correct dialect!\n\n* Like parsing, generating SQL also requires the target dialect to be specified, otherwise the SQLGlot dialect will be used by default. For example, to transpile a query from Spark SQL to DuckDB, do `parse_one(sql, dialect=\"spark\").sql(dialect=\"duckdb\")` (alternatively: `transpile(sql, read=\"spark\", write=\"duckdb\")`).\n\nWhat happened to sqlglot.dataframe?\n\n* The PySpark dataframe api was moved to a standalone library called [SQLFrame](https://github.com/eakmanrq/sqlframe) in v24. It now allows you to run queries as opposed to just generate SQL.\n\n## Examples\n\n### Formatting and Transpiling\n\nEasily translate from one dialect to another. For example, date/time functions vary between dialects and can be hard to deal with:\n\n```python\nimport sqlglot\nsqlglot.transpile(\"SELECT EPOCH_MS(1618088028295)\", read=\"duckdb\", write=\"hive\")[0]\n```\n\n```sql\n'SELECT FROM_UNIXTIME(1618088028295 / POW(10, 3))'\n```\n\nSQLGlot can even translate custom time formats:\n\n```python\nimport sqlglot\nsqlglot.transpile(\"SELECT STRFTIME(x, '%y-%-m-%S')\", read=\"duckdb\", write=\"hive\")[0]\n```\n\n```sql\n\"SELECT DATE_FORMAT(x, 'yy-M-ss')\"\n```\n\nIdentifier delimiters and data types can be translated as well:\n\n```python\nimport sqlglot\n\n# Spark SQL requires backticks (`) for delimited identifiers and uses `FLOAT` over `REAL`\nsql = \"\"\"WITH baz AS (SELECT a, c FROM foo WHERE a = 1) SELECT f.a, b.b, baz.c, CAST(\"b\".\"a\" AS REAL) d FROM foo f JOIN bar b ON f.a = b.a LEFT JOIN baz ON f.a = baz.a\"\"\"\n\n# Translates the query into Spark SQL, formats it, and delimits all of its identifiers\nprint(sqlglot.transpile(sql, write=\"spark\", identify=True, pretty=True)[0])\n```\n\n```sql\nWITH `baz` AS (\n  SELECT\n    `a`,\n    `c`\n  FROM `foo`\n  WHERE\n    `a` = 1\n)\nSELECT\n  `f`.`a`,\n  `b`.`b`,\n  `baz`.`c`,\n  CAST(`b`.`a` AS FLOAT) AS `d`\nFROM `foo` AS `f`\nJOIN `bar` AS `b`\n  ON `f`.`a` = `b`.`a`\nLEFT JOIN `baz`\n  ON `f`.`a` = `baz`.`a`\n```\n\nComments are also preserved on a best-effort basis:\n\n```python\nsql = \"\"\"\n/* multi\n   line\n   comment\n*/\nSELECT\n  tbl.cola /* comment 1 */ + tbl.colb /* comment 2 */,\n  CAST(x AS SIGNED), # comment 3\n  y               -- comment 4\nFROM\n  bar /* comment 5 */,\n  tbl #          comment 6\n\"\"\"\n\n# Note: MySQL-specific comments (`#`) are converted into standard syntax\nprint(sqlglot.transpile(sql, read='mysql', pretty=True)[0])\n```\n\n```sql\n/* multi\n   line\n   comment\n*/\nSELECT\n  tbl.cola /* comment 1 */ + tbl.colb /* comment 2 */,\n  CAST(x AS INT), /* comment 3 */\n  y /* comment 4 */\nFROM bar /* comment 5 */, tbl /*          comment 6 */\n```\n\n\n### Metadata\n\nYou can explore SQL with expression helpers to do things like find columns and tables in a query:\n\n```python\nfrom sqlglot import parse_one, exp\n\n# print all column references (a and b)\nfor column in parse_one(\"SELECT a, b + 1 AS c FROM d\").find_all(exp.Column):\n    print(column.alias_or_name)\n\n# find all projections in select statements (a and c)\nfor select in parse_one(\"SELECT a, b + 1 AS c FROM d\").find_all(exp.Select):\n    for projection in select.expressions:\n        print(projection.alias_or_name)\n\n# find all tables (x, y, z)\nfor table in parse_one(\"SELECT * FROM x JOIN y JOIN z\").find_all(exp.Table):\n    print(table.name)\n```\n\nRead the [ast primer](https://github.com/tobymao/sqlglot/blob/main/posts/ast_primer.md) to learn more about SQLGlot's internals.\n\n### Parser Errors\n\nWhen the parser detects an error in the syntax, it raises a `ParseError`:\n\n```python\nimport sqlglot\nsqlglot.transpile(\"SELECT foo FROM (SELECT baz FROM t\")\n```\n\n```\nsqlglot.errors.ParseError: Expecting ). Line 1, Col: 34.\n  SELECT foo FROM (SELECT baz FROM t\n                                   ~\n```\n\nStructured syntax errors are accessible for programmatic use:\n\n```python\nimport sqlglot\ntry:\n    sqlglot.transpile(\"SELECT foo FROM (SELECT baz FROM t\")\nexcept sqlglot.errors.ParseError as e:\n    print(e.errors)\n```\n\n```python\n[{\n  'description': 'Expecting )',\n  'line': 1,\n  'col': 34,\n  'start_context': 'SELECT foo FROM (SELECT baz FROM ',\n  'highlight': 't',\n  'end_context': '',\n  'into_expression': None\n}]\n```\n\n### Unsupported Errors\n\nIt may not be possible to translate some queries between certain dialects. For these cases, SQLGlot may emit a warning and will proceed to do a best-effort translation by default:\n\n```python\nimport sqlglot\nsqlglot.transpile(\"SELECT APPROX_DISTINCT(a, 0.1) FROM foo\", read=\"presto\", write=\"hive\")\n```\n\n```sql\nAPPROX_COUNT_DISTINCT does not support accuracy\n'SELECT APPROX_COUNT_DISTINCT(a) FROM foo'\n```\n\nThis behavior can be changed by setting the [`unsupported_level`](https://github.com/tobymao/sqlglot/blob/b0e8dc96ba179edb1776647b5bde4e704238b44d/sqlglot/errors.py#L9) attribute. For example, we can set it to either `RAISE` or `IMMEDIATE` to ensure an exception is raised instead:\n\n```python\nimport sqlglot\nsqlglot.transpile(\"SELECT APPROX_DISTINCT(a, 0.1) FROM foo\", read=\"presto\", write=\"hive\", unsupported_level=sqlglot.ErrorLevel.RAISE)\n```\n\n```\nsqlglot.errors.UnsupportedError: APPROX_COUNT_DISTINCT does not support accuracy\n```\n\nThere are queries that require additional information to be accurately transpiled, such as the schemas of the tables referenced in them. This is because certain transformations are type-sensitive, meaning that type inference is needed in order to understand their semantics. Even though the `qualify` and `annotate_types` optimizer [rules](https://github.com/tobymao/sqlglot/tree/main/sqlglot/optimizer) can help with this, they are not used by default because they add significant overhead and complexity.\n\nTranspilation is generally a hard problem, so SQLGlot employs an \"incremental\" approach to solving it. This means that there may be dialect pairs that currently lack support for some inputs, but this is expected to improve over time. We highly appreciate well-documented and tested issues or PRs, so feel free to [reach out](#get-in-touch) if you need guidance!\n\n### Build and Modify SQL\n\nSQLGlot supports incrementally building SQL expressions:\n\n```python\nfrom sqlglot import select, condition\n\nwhere = condition(\"x=1\").and_(\"y=1\")\nselect(\"*\").from_(\"y\").where(where).sql()\n```\n\n```sql\n'SELECT * FROM y WHERE x = 1 AND y = 1'\n```\n\nIt's possible to modify a parsed tree:\n\n```python\nfrom sqlglot import parse_one\nparse_one(\"SELECT x FROM y\").from_(\"z\").sql()\n```\n\n```sql\n'SELECT x FROM z'\n```\n\nParsed expressions can also be transformed recursively by applying a mapping function to each node in the tree:\n\n```python\nfrom sqlglot import exp, parse_one\n\nexpression_tree = parse_one(\"SELECT a FROM x\")\n\ndef transformer(node):\n    if isinstance(node, exp.Column) and node.name == \"a\":\n        return parse_one(\"FUN(a)\")\n    return node\n\ntransformed_tree = expression_tree.transform(transformer)\ntransformed_tree.sql()\n```\n\n```sql\n'SELECT FUN(a) FROM x'\n```\n\n### SQL Optimizer\n\nSQLGlot can rewrite queries into an \"optimized\" form. It performs a variety of [techniques](https://github.com/tobymao/sqlglot/blob/main/sqlglot/optimizer/optimizer.py) to create a new canonical AST. This AST can be used to standardize queries or provide the foundations for implementing an actual engine. For example:\n\n```python\nimport sqlglot\nfrom sqlglot.optimizer import optimize\n\nprint(\n    optimize(\n        sqlglot.parse_one(\"\"\"\n            SELECT A OR (B OR (C AND D))\n            FROM x\n            WHERE Z = date '2021-01-01' + INTERVAL '1' month OR 1 = 0\n        \"\"\"),\n        schema={\"x\": {\"A\": \"INT\", \"B\": \"INT\", \"C\": \"INT\", \"D\": \"INT\", \"Z\": \"STRING\"}}\n    ).sql(pretty=True)\n)\n```\n\n```sql\nSELECT\n  (\n    \"x\".\"a\" \u003c\u003e 0 OR \"x\".\"b\" \u003c\u003e 0 OR \"x\".\"c\" \u003c\u003e 0\n  )\n  AND (\n    \"x\".\"a\" \u003c\u003e 0 OR \"x\".\"b\" \u003c\u003e 0 OR \"x\".\"d\" \u003c\u003e 0\n  ) AS \"_col_0\"\nFROM \"x\" AS \"x\"\nWHERE\n  CAST(\"x\".\"z\" AS DATE) = CAST('2021-02-01' AS DATE)\n```\n\n### AST Introspection\n\nYou can see the AST version of the parsed SQL by calling `repr`:\n\n```python\nfrom sqlglot import parse_one\nprint(repr(parse_one(\"SELECT a + 1 AS z\")))\n```\n\n```python\nSelect(\n  expressions=[\n    Alias(\n      this=Add(\n        this=Column(\n          this=Identifier(this=a, quoted=False)),\n        expression=Literal(this=1, is_string=False)),\n      alias=Identifier(this=z, quoted=False))])\n```\n\n### AST Diff\n\nSQLGlot can calculate the semantic difference between two expressions and output changes in a form of a sequence of actions needed to transform a source expression into a target one:\n\n```python\nfrom sqlglot import diff, parse_one\ndiff(parse_one(\"SELECT a + b, c, d\"), parse_one(\"SELECT c, a - b, d\"))\n```\n\n```python\n[\n  Remove(expression=Add(\n    this=Column(\n      this=Identifier(this=a, quoted=False)),\n    expression=Column(\n      this=Identifier(this=b, quoted=False)))),\n  Insert(expression=Sub(\n    this=Column(\n      this=Identifier(this=a, quoted=False)),\n    expression=Column(\n      this=Identifier(this=b, quoted=False)))),\n  Keep(\n    source=Column(this=Identifier(this=a, quoted=False)),\n    target=Column(this=Identifier(this=a, quoted=False))),\n  ...\n]\n```\n\nSee also: [Semantic Diff for SQL](https://github.com/tobymao/sqlglot/blob/main/posts/sql_diff.md).\n\n### Custom Dialects\n\n[Dialects](https://github.com/tobymao/sqlglot/tree/main/sqlglot/dialects) can be added by subclassing `Dialect`:\n\n```python\nfrom sqlglot import exp\nfrom sqlglot.dialects.dialect import Dialect\nfrom sqlglot.generator import Generator\nfrom sqlglot.tokens import Tokenizer, TokenType\n\n\nclass Custom(Dialect):\n    class Tokenizer(Tokenizer):\n        QUOTES = [\"'\", '\"']\n        IDENTIFIERS = [\"`\"]\n\n        KEYWORDS = {\n            **Tokenizer.KEYWORDS,\n            \"INT64\": TokenType.BIGINT,\n            \"FLOAT64\": TokenType.DOUBLE,\n        }\n\n    class Generator(Generator):\n        TRANSFORMS = {exp.Array: lambda self, e: f\"[{self.expressions(e)}]\"}\n\n        TYPE_MAPPING = {\n            exp.DataType.Type.TINYINT: \"INT64\",\n            exp.DataType.Type.SMALLINT: \"INT64\",\n            exp.DataType.Type.INT: \"INT64\",\n            exp.DataType.Type.BIGINT: \"INT64\",\n            exp.DataType.Type.DECIMAL: \"NUMERIC\",\n            exp.DataType.Type.FLOAT: \"FLOAT64\",\n            exp.DataType.Type.DOUBLE: \"FLOAT64\",\n            exp.DataType.Type.BOOLEAN: \"BOOL\",\n            exp.DataType.Type.TEXT: \"STRING\",\n        }\n\nprint(Dialect[\"custom\"])\n```\n\n```\n\u003cclass '__main__.Custom'\u003e\n```\n\n### SQL Execution\n\nSQLGlot is able to interpret SQL queries, where the tables are represented as Python dictionaries. The engine is not supposed to be fast, but it can be useful for unit testing and running SQL natively across Python objects. Additionally, the foundation can be easily integrated with fast compute kernels, such as [Arrow](https://arrow.apache.org/docs/index.html) and [Pandas](https://pandas.pydata.org/).\n\nThe example below showcases the execution of a query that involves aggregations and joins:\n\n```python\nfrom sqlglot.executor import execute\n\ntables = {\n    \"sushi\": [\n        {\"id\": 1, \"price\": 1.0},\n        {\"id\": 2, \"price\": 2.0},\n        {\"id\": 3, \"price\": 3.0},\n    ],\n    \"order_items\": [\n        {\"sushi_id\": 1, \"order_id\": 1},\n        {\"sushi_id\": 1, \"order_id\": 1},\n        {\"sushi_id\": 2, \"order_id\": 1},\n        {\"sushi_id\": 3, \"order_id\": 2},\n    ],\n    \"orders\": [\n        {\"id\": 1, \"user_id\": 1},\n        {\"id\": 2, \"user_id\": 2},\n    ],\n}\n\nexecute(\n    \"\"\"\n    SELECT\n      o.user_id,\n      SUM(s.price) AS price\n    FROM orders o\n    JOIN order_items i\n      ON o.id = i.order_id\n    JOIN sushi s\n      ON i.sushi_id = s.id\n    GROUP BY o.user_id\n    \"\"\",\n    tables=tables\n)\n```\n\n```python\nuser_id price\n      1   4.0\n      2   3.0\n```\n\nSee also: [Writing a Python SQL engine from scratch](https://github.com/tobymao/sqlglot/blob/main/posts/python_sql_engine.md).\n\n## Used By\n\n* [SQLMesh](https://github.com/TobikoData/sqlmesh)\n* [Apache Superset](https://github.com/apache/superset)\n* [Dagster](https://github.com/dagster-io/dagster)\n* [Fugue](https://github.com/fugue-project/fugue)\n* [ibis](https://github.com/ibis-project/ibis)\n* [mysql-mimic](https://github.com/kelsin/mysql-mimic)\n* [Querybook](https://github.com/pinterest/querybook)\n* [Quokka](https://github.com/marsupialtail/quokka)\n* [Splink](https://github.com/moj-analytical-services/splink)\n* [SQLFrame](https://github.com/eakmanrq/sqlframe)\n\n## Documentation\n\nSQLGlot uses [pdoc](https://pdoc.dev/) to serve its API documentation.\n\nA hosted version is on the [SQLGlot website](https://sqlglot.com/), or you can build locally with:\n\n```\nmake docs-serve\n```\n\n## Run Tests and Lint\n\n```\nmake style  # Only linter checks\nmake unit   # Only unit tests (or unit-rs, to use the Rust tokenizer)\nmake test   # Unit and integration tests (or test-rs, to use the Rust tokenizer)\nmake check  # Full test suite \u0026 linter checks\n```\n\n## Benchmarks\n\n[Benchmarks](https://github.com/tobymao/sqlglot/blob/main/benchmarks/bench.py) run on Python 3.10.12 in seconds.\n\n|           Query |         sqlglot |       sqlglotrs |        sqlfluff |         sqltree |        sqlparse |  moz_sql_parser |        sqloxide |\n| --------------- | --------------- | --------------- | --------------- | --------------- | --------------- | --------------- | --------------- |\n|            tpch |   0.00944 (1.0) | 0.00590 (0.625) | 0.32116 (33.98) | 0.00693 (0.734) | 0.02858 (3.025) | 0.03337 (3.532) | 0.00073 (0.077) |\n|           short |   0.00065 (1.0) | 0.00044 (0.687) | 0.03511 (53.82) | 0.00049 (0.759) | 0.00163 (2.506) | 0.00234 (3.601) | 0.00005 (0.073) |\n|            long |   0.00889 (1.0) | 0.00572 (0.643) | 0.36982 (41.56) | 0.00614 (0.690) | 0.02530 (2.844) | 0.02931 (3.294) | 0.00059 (0.066) |\n|           crazy |   0.02918 (1.0) | 0.01991 (0.682) | 1.88695 (64.66) | 0.02003 (0.686) | 7.46894 (255.9) | 0.64994 (22.27) | 0.00327 (0.112) |\n\n```\nmake bench            # Run parsing benchmark\nmake bench-optimize   # Run optimization benchmark\n```\n\n## Optional Dependencies\n\nSQLGlot uses [dateutil](https://github.com/dateutil/dateutil) to simplify literal timedelta expressions. The optimizer will not simplify expressions like the following if the module cannot be found:\n\n```sql\nx + interval '1' month\n```\n","funding_links":[],"categories":["Python","Language bindings","语言资源库","其他__大数据","Tools Powered by DuckDB","📦 Projects","Official Resources","sqlite","🗃️ SQL \u0026 Databases","\u003ca name=\"Python\"\u003e\u003c/a\u003ePython","Table of Contents","SQL"],"sub_categories":["Python","python","网络服务_其他","Fine-tuning","Tools","Developer Tools","Parsers"],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftobymao%2Fsqlglot","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ftobymao%2Fsqlglot","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftobymao%2Fsqlglot/lists"}