py-sql-cleaner is a CLI tool for finding, formatting, and extracting SQL embedded in Python files.

It is built for Python codebases where long SQL queries are written directly inside triple-quoted Python strings. The current MVP uses SQLGlot for formatting, defaults to SQLGlot's generic dialect, and can format with database-specific dialects that this project has explicitly enabled via --dialect.

query = """
select user_id, updated_at
from users
qualify row_number() over(partition by user_id order by updated_at desc)=1
"""

py-sql-cleaner can format that SQL in place, or extract it into an external .sql file.

py-sql-cleaner is an early MVP. It uses SQLGlot internally for best-effort SQL formatting. It does not connect to databases and does not execute SQL. Dialect support means SQLGlot parser/formatter mode selection, not exhaustive database validation. With -d redshift, Redshift command-style statements such as COPY and UNLOAD are preserved rather than reformatted to avoid changing load/export options.

Features

• Format SQL embedded in Python triple-quoted strings
• Extract embedded SQL into external .sql files
• Replace embedded SQL strings with file references
• Detect common SQL variable names such as sql, query, *_sql, and *_query
• Skip unsafe blocks, including f-strings, Jinja-like templates, and runtime placeholders, by default
• Support explicit dialect selection with --dialect / -d
• Support check mode for CI
• Support dry-run mode before rewriting files

Installation

Install py-sql-cleaner from PyPI:

pip install py-sql-cleaner

Or install it as an isolated CLI tool with pipx:

pipx install py-sql-cleaner

Release archives and wheels are also attached to GitHub Releases.

You can also run it without installing:

uvx py-sql-cleaner --help

Quick Start

1. List embedded SQL blocks:

   py-sql-cleaner list jobs/load_users.py

2. Preview formatting changes:

   py-sql-cleaner format jobs/load_users.py --dry-run

3. Format embedded SQL in place:

   py-sql-cleaner format jobs/load_users.py

4. Format with a database-specific dialect:

   py-sql-cleaner format jobs/load_users.py -d redshift

   Currently enabled dialects are generic, mysql, postgres, and redshift.

5. Extract embedded SQL into .sql files:

   py-sql-cleaner extract jobs/load_users.py --out-dir sql

6. Check formatting for CI:

   py-sql-cleaner check jobs/load_users.py

Example

Before:

query = """
select user_id, updated_at
from users
qualify row_number() over(partition by user_id order by updated_at desc)=1
"""

After py-sql-cleaner format jobs/load_users.py:

query = """
SELECT
  user_id,
  updated_at
FROM users
QUALIFY
  ROW_NUMBER() OVER (PARTITION BY user_id ORDER BY updated_at DESC) = 1
"""

Exact formatting is produced by SQLGlot and may change as SQLGlot changes.

After py-sql-cleaner extract jobs/load_users.py --out-dir sql:

Supported Input

The current MVP targets Python triple-quoted strings.

Supported:

query = """
SELECT *
FROM users
"""

load_users_sql = '''
SELECT *
FROM users
'''

Not targeted in the MVP:

query = "SELECT * FROM users"

Safety

py-sql-cleaner is conservative by default. It skips unsafe blocks instead of rewriting them.

Always skipped by format and extract:

query = f"""
SELECT *
FROM users
WHERE user_id = {user_id}
"""

query = """
SELECT *
FROM users
WHERE ds = '{{ ds }}'
"""

query = """
SELECT *
FROM users
WHERE user_id = :user_id
"""

query = """
SELECT *
FROM users
WHERE user_id = %s
"""

f-strings, Jinja-like templates, and parameterized SQL are not complete SQL at rest. Python, a template engine, or a database driver fills those values at runtime, so rewriting or extracting the file contents directly could change runtime behavior.

py-sql-cleaner does not:

• connect to databases
• execute SQL
• validate SQL against a database
• inspect schemas
• provide autocomplete
• guarantee full database compatibility
• fully support f-strings
• fully support Jinja templates
• rewrite parameterized SQL safely
• format every possible SQL string

Commands

Use py-sql-cleaner --version to print the installed CLI version.

Documentation

• Documentation site source
• Usage Guide
• Safety and Limitations
• Contributing

Status

py-sql-cleaner is currently an early MVP.

The current focus is:

• Python files
• triple-quoted SQL strings
• SQLGlot-backed SQL formatting, defaulting to generic SQL with --dialect support for explicitly enabled database-specific formatting
• formatting
• extracting SQL into .sql files

License

MIT