---
id: ddlparse
version: "1.10.0"
license: BSD-3-Clause
license_treatment: permissive
maintenance: dormant
---

# ddlparse — DDL parase and Convert to BigQuery JSON schema

License: permissive · Maintenance: dormant · Downloads: 86.0K/mo

## What it is and what it does

ddlparse is a Python library that reads CREATE TABLE statements written in MySQL, MariaDB, PostgreSQL, Oracle, or Redshift SQL dialects and extracts the schema structure into a programmatic object model. It then converts that schema to BigQuery-compatible JSON schema format or generates equivalent BigQuery CREATE TABLE DDL statements. The package depends only on pyparsing and installs as a pure Python wheel.

You use it when you need to migrate table definitions from one of those source databases to BigQuery, or when you need to programmatically inspect and transform table structure from raw DDL. It exposes column-level metadata (data types, constraints, precision, scale, nullability, keys, defaults, comments) and supports case normalization of identifiers during conversion.

Use it for:

- Migrate table schemas from MySQL or PostgreSQL to BigQuery by parsing existing DDL and generating BigQuery-compatible schema.
- Extract column metadata (types, constraints, nullability) from Oracle or Redshift CREATE TABLE statements for documentation or validation.
- Programmatically transform DDL identifiers to uppercase or lowercase during schema conversion pipelines.
- Generate BigQuery JSON schema files from legacy database DDL without manual rewriting.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Parses CREATE TABLE DDL statements from MySQL, MariaDB, PostgreSQL, Oracle, and Redshift, extracting table schema information and converting it to BigQuery JSON schema and DDL formats.

Yes, if you need to parse and convert CREATE TABLE DDL from MySQL, PostgreSQL, Oracle, or Redshift to BigQuery format. The package is stable, has no known vulnerabilities, and installs cleanly. However, maintenance is dormant (last release July 2021); if you need support for newer SQL features or active bug fixes, verify that the package handles your specific dialect variations before committing to it.

## Install

pip install ddlparse
uv add ddlparse
poetry add ddlparse

## Installing ddlparse

Before you install: Low friction: pure Python wheel with a single runtime dependency (pyparsing). Maintenance is dormant—last release was 2021-07-09 and last commit 2023-10-23—but the package is marked Production/Stable and has seen no security issues.

License in practice: BSD-3-Clause is permissive; you may use, modify, and distribute this package freely in commercial and private projects provided you include the license text and a notice of changes.

Quickstart:

from ddlparse import DdlParse

sample_ddl = "CREATE TABLE My_Schema.Sample_Table (Id integer PRIMARY KEY, Name varchar(100) NOT NULL);"
table = DdlParse().parse(sample_ddl)
print(table.to_bigquery_fields())

Requires Python >= 3.5; only CREATE TABLE statements are supported, not other DDL operations.

Verify before relying:

- Whether the parser handles all MySQL, PostgreSQL, Oracle, and Redshift dialect variations equally well, or if some databases have better coverage than others.
- Performance characteristics on large or complex DDL statements.
- Whether dormant status (last release 2021-07-09) means the package is stable enough for production or if it lacks support for newer SQL features.

## Package facts

- License: BSD-3-Clause (permissive)
- Python support: unspecified
- Install friction: low
- Maintenance: dormant
- Downloads: 86.0K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

ddl parser sql, bigquery schema conversion, create table parser, sql schema extraction, database ddl to bigquery, mysql postgresql oracle ddl parse, schema-migration, bigquery, sql-parsing

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