Quickstart

import goldenmatch as gm

result = gm.dedupe("customers.csv")
print(result)  # DedupeResult(records=5000, clusters=847, match_rate=12.0%)
result.golden.write_csv("deduped.csv")

import { dedupe } from "goldenmatch";

const rows = [
  { id: 1, name: "John Smith", email: "john@example.com", zip: "12345" },
  { id: 2, name: "Jon Smith",  email: "john@example.com", zip: "12345" },
  { id: 3, name: "Jane Doe",   email: "jane@example.com", zip: "54321" },
];

const result = dedupe(rows, { fuzzy: { name: 0.85 }, blocking: ["zip"], threshold: 0.85 });
console.log(result.stats);

pip install goldenpipe

import goldenpipe as gp

result = gp.run("customers.csv")
print(result.status)     # "success"
print(result.reasoning)  # why each stage ran or was skipped

pip install goldenmatch[llm]          # Claude / OpenAI borderline scoring
pip install goldenmatch[duckdb]       # out-of-core backend
pip install goldenmatch[ray]          # distributed backend (50M+ rows)
pip install goldenmatch[web]          # localhost browser workbench
pip install goldenmatch[mcp]          # MCP server for Claude Desktop

goldenmatch setup