Guides
Short recipes for common Finetype tasks: profile a Parquet file, build a typed DuckDB pipeline, and validate a data delivery against a saved schema.
Short, self-contained recipes for real tasks. Each one states its goal and the problem it solves, lists what you need, then walks through the steps on sample data you can save and run.
Recipes
| Recipe | What you'll do |
|---|---|
| Profile a Parquet File | Read the semantic type of every column in a Parquet file, with the CLI or from inside DuckDB with the extension |
| Build a Typed DuckDB Pipeline | Go from raw CSV to a fully typed DuckDB database: profile, export a schema, then validate and materialise |
| Validate a Data Delivery | Save a schema from a known-good batch and validate new deliveries against it |
Before you start
Every recipe assumes you have Finetype and DuckDB installed. If you haven't set those up yet, follow the Quick Start guide first.
See also
- CLI Reference — flags, defaults, and output formats for every command
- DuckDB Extension — using Finetype directly inside SQL queries
- Type Registry — browse the 251 semantic types Finetype detects
taxonomy
Browse Finetype's type taxonomy with finetype taxonomy: list every type, filter by domain or category, and export one type's JSON Schema or the whole set.
Profile a Parquet File
Profile data stored in Parquet with Finetype, directly with the CLI or inside DuckDB with the community extension, and read the semantic type of each column.