Pure-Rust NHTSA vPIC VIN decoder — CLI + library, with spVinDecode parity.
Project description
ultravin
An extremely fast, fully offline NHTSA vPIC VIN decoder, written in Rust.
VINs decoded per second over a random corpus, single sequential caller — ultravin also batches across cores.
- ⚡️ ~0.07 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 ~55,000 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 | 54,801 | ~3.8× faster |
| ultravin — 1 core | 14,291 | 1× |
corgi v3 — @cardog/corgi (binary index) |
~83 | ~172× slower |
corgi v2 — @cardog/corgi 2.0.1 (SQLite) |
~33 | ~433× slower |
NHTSA MSSQL — spVinDecode (SQL Server) |
22.5 | ~635× slower |
NHTSA Postgres — spvindecode |
19.5 | ~733× slower |
| NHTSA vPIC web API — public rate limit | ~10 | ~1,430× 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 ~635× 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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