169 Semantic Types
Dates, emails, IPs, UUIDs, coordinates, phone numbers, and financial identifiers — across 6 domains and 16+ locales.
Open-source tools for analysts who need to understand their data before they query it.
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Point FineType at a CSV. Get the semantic type and confidence score for every column.
$ finetype profile -f contacts.csv
Column Type Confidence──────────── ────────────────────────────────── ──────────name identity.person.full_name 0.92email identity.person.email 0.99created_at datetime.timestamp.iso_8601 0.98ip_address technology.internet.ip_v4 0.97amount representation.numeric.decimal 0.94Is that column of numbers a postal code, a year, or a price? Are those dates US or European? FineType detects 169 semantic types and maps each one to a DuckDB expression — so your casts work on every row, not just the first ten.
Every type prediction is a guarantee, not a guess.
169 Semantic Types
Dates, emails, IPs, UUIDs, coordinates, phone numbers, and financial identifiers — across 6 domains and 16+ locales.
Guaranteed Casts
Every type maps to a DuckDB SQL expression. Profile your data, then cast with confidence. No more surprises at row 47,000.
Fast and Local
Pure Rust, no Python. 600+ classifications per second, 8.5 MB memory. Runs on your laptop — no cloud required.
FineType is free, open source (MIT), and ready to use.
Install & First Workflow
Install FineType and DuckDB, profile your first dataset in five minutes. Get started →
FineType Reference
Full CLI, DuckDB extension, taxonomy, and performance benchmarks. Read the docs →