sql-metadata
Uses sqlglot to parse SQL queries and extract metadata
Decision gist · record as of 2026-08-14
Yes. Low install friction, active maintenance, MIT license, no known vulnerabilities, and a single well-maintained dependency. Install it if you need to extract or analyze SQL query structure—it handles the parsing complexity so you don't have to.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Low friction: pure Python wheel with a single runtime dependency (sqlglot).
- Actively maintained with a release 45 days ago and 882 repository stars.
License · maintenance · safety
MIT (permissive) — MIT license permits unrestricted use, modification, and distribution in both open-source and commercial projects.
last release 2026-06-30 (45 days) · last repo commit 2026-08-14 · 882 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 6,799,628 downloads/mo, #1,845 on PyPI
Alternatives
Verify before relying
pip install sql-metadata
from sql_metadata import Parser
parser = Parser("SELECT a, b FROM users WHERE id = 1")
print(parser.columns) # ['a', 'b']
print(parser.tables) # ['users']- Whether performance characteristics are acceptable for large or complex queries
- Coverage completeness for edge cases across all five supported SQL dialects
What it is and what it does
sql-metadata wraps sqlglot to parse SQL queries and extract structural metadata without executing them. It identifies columns, tables, aliases, query types (SELECT, INSERT, UPDATE, DELETE, etc.), and values from INSERT statements. The parser automatically resolves column aliases back to their source columns, table aliases to their actual table names, and subquery aliases to their definitions—useful when you need to understand query dependencies without running the query itself.
The package supports MySQL, PostgreSQL, SQLite, MSSQL, and Apache Hive syntax. It provides both raw token extraction and semantic analysis: you can get columns grouped by their clause (SELECT, WHERE, JOIN, ORDER BY, etc.), output column names preserving aliases, WITH clause definitions, and limit/offset values. It raises InvalidQueryDefinition for structurally invalid SQL, making error handling straightforward.
Use it for
- Extract column and table dependencies from queries to build data lineage or impact analysis tools
- Validate query structure and detect referenced tables before execution in data pipelines
- Resolve aliases and normalize queries for logging, auditing, or query rewriting systems
- Analyze INSERT statements to map input values to their target columns programmatically
- Build IDE or documentation tools that need to understand query structure without parsing SQL yourself
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
Low install friction, active maintenance, MIT license, no known vulnerabilities, and a single well-maintained dependency. Install it if you need to extract or analyze SQL query structure—it handles the parsing complexity so you don't have to.
Install
sql-metadata on PyPI
Before you install
Low friction: pure Python wheel with a single runtime dependency (sqlglot). Actively maintained with a release 45 days ago and 882 repository stars.
License in practice
MIT license permits unrestricted use, modification, and distribution in both open-source and commercial projects.
Quickstart
pip install sql-metadata
from sql_metadata import Parser
parser = Parser("SELECT a, b FROM users WHERE id = 1")
print(parser.columns) # ['a', 'b']
print(parser.tables) # ['users']Verify before relying
- Whether performance characteristics are acceptable for large or complex queries
- Coverage completeness for edge cases across all five supported SQL dialects
Package facts
| License | MIT permissive |
| Python support | Supports the current Python release <4.0,>=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 1 packagesqlglot |
| Maintenance | Actively maintained 45 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 6,799,628 / month, #1,845 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | License :: OSI Approved :: MIT LicenseProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14 |
Evidence: sql_metadata-3.0.1-py3-none-any.whl
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