Why matching commercial vehicle OEM part numbers in SQL is messy (and how we open-sourced our parser)

Description and use

In automotive data, the same OEM part number appears in many formats, making SQL matching unreliable. The open‑source TypeScript library @crazypartsnatcher/oem-normalizer normalizes numbers, generates search variants, and detects manufacturer formats, improving matching accuracy.

Problem

Inconsistent OEM and OES part numbers across supplier feeds make SQL matching unreliable, causing missed offers in a commercial vehicle price comparison engine.

Outcome

The open‑source normalizer library resolved the part number mismatch issue, enabling accurate matching across supplier feeds and improving the reliability of the price comparison engine.

Workflow

• 1. Install the package via npm: npm install @crazypartsnatcher/oem-normalizer
• 2. Import functions in Node.js/TypeScript: import { normalizeOem, generateSearchVariants, detectManufacturerFormat, buildPartSearchUrl } from '@crazypartsnatcher/oem-normalizer';
• 3. Normalize raw input: const cleanKey = normalizeOem(rawInput);
• 4. Generate search variants: const variants = generateSearchVariants(rawInput);
• 5. Detect manufacturer format: const formats = detectManufacturerFormat(rawInput);
• 6. Build comparison URL: const comparisonUrl = buildPartSearchUrl(cleanKey);
• 7. Use normalized key for SQL/MariaDB lookups and variants for fuzzy search queries.

Evidence

When building an automotive or commercial vehicle price comparison engine, the biggest data bottleneck isn't scraping or API rate limits—it's inconsistent OEM and OES part numbers across different supplier feeds.

Source

We extracted it into a lightweight, zero-dependency TypeScript/JavaScript package and published it on npm and GitHub.

Source

It handles four core tasks out of the box: normalizeOem, generateSearchVariants, detectManufacturerFormat, buildPartSearchUrl.

Source

Install via npm: npm install @crazypartsnatcher/oem-normalizer

Source