Short Updates

Excited to announce the Inflector Extension for DuckDB by Query.Farm!

Transform string cases and inflect column names directly in SQL—no more wrestling with naming conventions across your data pipeline. What does it do? ✅...

Transform string cases and inflect column names directly in SQL—no more wrestling with naming conventions across your data pipeline.

What does it do?

✅ Convert between any case style: camelCase, snake_case, kebab-case, PascalCase, and more ✅ Pluralize/singularize words automatically ✅ Transform ALL column names in tables or structs with one function ✅ Validate naming conventions across your schemas ✅ Handle foreign keys and module paths

Real-world use cases:

🔹 Normalize API responses before loading into your database 🔹 Migrate schemas between naming conventions (Rails → JavaScript, etc.) 🔹 Standardize CSV/JSON imports on the fly 🔹 Validate data quality by checking naming compliance 🔹 Generate foreign key names automatically

Quick example:

INSTALL inflector FROM community; LOAD inflector;

— Transform all column names at once

SELECT * FROM inflect(‘snake’, read_csv(‘UserData.csv’));

— FirstName, LastName → first_name, last_name

No more manual column renaming. No external scripts. Just pure SQL.

The extension is available now in the DuckDB Community Extensions repository and works seamlessly with your existing workflows.

Check it out: https://query.farm/duckdb_extension_inflector.html

Originally posted on LinkedIn.

#DuckDB #Data Engineering #SQL #ETL #Data Pipelines #Open Source #DuckDB Extensions