How to Deduplicate 100,000 Records in 13 Seconds with Python

You have a CSV with duplicate records. Maybe it's customer data exported from two CRMs, a product catalog merged from multiple vendors, or academic papers from different databases. You need to find the duplicates, decide which to merge, and produce a clean dataset. Here's how to do it in one command: pip install goldenmatch goldenmatch dedupe your_data.csv That's the zero-config path. GoldenMatch auto-detects your column types (name, email, phone, zip, address), picks appropriate matching algorithms, chooses a blocking strategy, and launches an interactive TUI where you review the results. But let's go deeper. I'll walk through what happens under the hood and how to tune it for better results. What happens when you run goldenmatch dedupe 1. Column Classification GoldenMatch profiles your data and classifies each column: Detected Type Scorer Why Name Ensemble (best of Jaro-Winkler, token sort, soundex) Handles misspellings, nicknames, word order Email Exact (after normalization) Emails