{"categories":[{"label":"Software Development","url":"https://skillfed.io/packages/category/software-development/10"},{"label":"Libraries","url":"https://skillfed.io/packages/category/software-development-libraries/7"},{"label":"Python Modules","url":"https://skillfed.io/packages/category/software-development-libraries-python-modules/14"},{"label":"Utilities","url":"https://skillfed.io/packages/category/utilities/7"}],"enrichment":{"capability":"Parses SQL DDL statements and their dialect variants into structured Python dictionaries or JSON, extracting table schemas, columns, constraints, and dialect-specific properties.","skillfed_tags":["sql-parsing","schema-extraction","ddl"],"use_cases":["Extract table and column metadata from existing SQL databases to generate documentation or ERD diagrams.","Convert DDL from one SQL dialect to another by parsing and reshaping output with custom schemas.","Validate and normalize DDL statements programmatically in data pipeline or schema migration tools.","Parse Hive or BigQuery DDL to extract partition, storage, and location metadata for data lake management.","Generate Python ORM models or database client code from DDL definitions."],"what_it_does":"Simple DDL Parser is a Python library built on ply (Python's lex and yacc implementation) that converts SQL Data Definition Language statements into structured dictionaries or JSON. It supports multiple SQL dialects including HQL, MSSQL, Oracle, MySQL, PostgreSQL, BigQuery, Redshift, Snowflake, SparkSQL, IBM DB2, and others. The parser extracts detailed schema information\u2014table names, column definitions with types and sizes, primary keys, constraints, defaults, and references\u2014while preserving dialect-specific properties like partitioning and storage formats when requested.\n\nThe library is case-insensitive and designed to handle real-world DDL variations. It offers both a Python API for programmatic use and a command-line tool (sdp) for batch processing. Output can be customized via output_mode to include dialect-specific fields or reshaped into formats like BigQuery JSON schema. The maintainer actively adds support for new statements and dialects based on user requests and maintains functional test coverage.","worth_installing":"Yes. The package is actively maintained, has no known vulnerabilities, installs with minimal friction, and is widely used. It solves a real problem\u2014parsing diverse SQL dialects into structured data\u2014with a permissive MIT license. Install it if you need to programmatically extract or transform SQL schema definitions."},"id":"simple-ddl-parser","links":{"html":"https://skillfed.io/packages/simple-ddl-parser","md":"https://skillfed.io/packages/simple-ddl-parser.md","pypi":"https://pypi.org/project/simple-ddl-parser/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-03-28","license_spdx":null,"license_treatment":"permissive","name":"simple-ddl-parser","python_support":"supports_current","summary":"Simple DDL Parser to parse SQL & dialects like HQL, TSQL (MSSQL), Oracle, AWS Redshift, Snowflake, MySQL, PostgreSQL, etc ddl files to json/python dict with full information about columns: types, defaults, primary keys, etc.; sequences, alters, custom types & other entities from ddl."},"popularity":{"monthly_downloads":264743,"position":8333,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"1.13.0"}