Pointblank: Data Validation That's Actually Beautiful

Your Data Is Lying to You That CSV your pipeline ingested at 3 AM? It has NULL customer IDs. The revenue column has negative values. And that status field someone added "cancled" to (yes, misspelled) last Tuesday? It's been silently corrupting your analytics for a week. Every data team has a version of this story. The uncomfortable truth is that most data quality issues aren't caught: they're discovered (usually by someone staring at a dashboard that doesn't add up). We built Pointblank to change that. What Is Pointblank? Pointblank is an open-source Python library for assessing and monitoring data quality. You define validation rules, Pointblank interrogates your data, and you get clear, visual reporting that the whole team can act on. It works with the tools you already use: Polars, Pandas, DuckDB, PostgreSQL, MySQL, SQLite, Parquet, PySpark, and Snowflake. No new infrastructure required. What makes Pointblank different from other validation libraries? Two things: Communication-first