ultravin

An extremely fast, fully offline NHTSA vPIC VIN decoder, written in Rust.

VINs decoded per second: ultravin 111,496 batched / 19,331 single-core vs corgi v3 83, corgi v2 33, NHTSA MSSQL 22.5, NHTSA Postgres 19.5
_{VINs decoded per second over a random corpus, single sequential caller — ultravin also batches across cores.}

⚡️ ~0.045 ms per decode — orders of magnitude faster than the NHTSA SQL procedures (corgi, Postgres, MSSQL)
🦀 Pure Rust core, shipped as a Python library
📦 The entire vPIC vehicle database baked into the wheel
🔌 Fully offline — no network, no database, no data files at runtime
🎯 Byte-for-byte parity with vPIC's spVinDecode, verified across every decodable VIN
🐍 Installable via pip, with a CLI and a library API
🧵 Batches in parallel to ~110,000 VIN/s on 10 cores

ultravin is a faithful port of NHTSA's spVinDecode — the SQL procedure behind vPIC — reimplemented in Rust and verified against the reference Postgres implementation. Because the vehicle database ships inside the binary, decoding needs no network, no database server, and no data files. Install it and decode.

Getting Started

Installation

uv add ultravin

Prebuilt wheels require Python 3.10+ and nothing else — the data ships inside the wheel.

Usage

From Python:

import ultravin

r = ultravin.decode("1HGCM82633A004352")

r["model_year"]         # 2003
r["wmi"]                # '1HG'
r["check_digit_valid"]  # True
r["error_codes"]        # [0]

# `elements` is the full decoded attribute list; index it by variable name:
attrs = {e["variable"]: e["value"] for e in r["elements"]}
attrs["Make"]           # 'HONDA'
attrs["Model"]          # 'Accord'

decode(vin) returns a dict with keys vin, wmi, descriptor, model_year, error_codes, check_digit_valid, corrected_vin, and elements — a list of per-attribute dicts (group_name, variable, value, element_id, source, …). Decode many at once with decode_batch:

results = ultravin.decode_batch(["1HGCM82633A004352", "5YJ3E1EA7JF000000"])

From the command line:

ultravin decode 1HGCM82633A004352          # human-readable table
ultravin decode 1HGCM82633A004352 --json   # full JSON
ultravin decode-batch vins.txt --json      # one VIN per line
ultravin version

Benchmarks

How many VINs each engine decodes per second, single sequential caller, over an identical random corpus of 5,000 valid VINs (measured over 60 s; Apple Silicon, 10 cores):

engine	VIN/s	vs ultravin (1 core)
ultravin — batched, 10 cores	111,496	~5.8× faster
ultravin — 1 core	19,331	1×
corgi v3 — `@cardog/corgi` (binary index)	~83	~233× slower
corgi v2 — `@cardog/corgi` 2.0.1 (SQLite)	~33	~586× slower
NHTSA MSSQL — `spVinDecode` (SQL Server)	22.5	~859× slower
NHTSA Postgres — `spvindecode`	19.5	~991× slower
NHTSA vPIC web API — public rate limit	~10	~1,933× slower

ultravin runs in-process with the database embedded — no server, no round-trip. The corgi figures are derived from its project's published per-VIN latency (~12 ms v3 / ~30 ms v2, not re-measured here). The NHTSA Postgres and MSSQL oracles run the unmodified spVinDecode over localhost; MSSQL is SQL Server under amd64 emulation on Apple Silicon, so its number understates native hardware — ultravin is still ~859× faster. The NHTSA vPIC web API row is its published ~10 req/s rate limit, not a decode time — a hard ceiling regardless of hardware. Methodology and reproduction: docs/BENCHMARKS.md.

License

MIT

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ultravin 0.0.5

ultravin

Getting Started

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