installing a CLI. Some databases like DuckDB also have a feature to query the metadata, but that means writing SQL for every little thing you want to check, and the output is still text.

I wanted something I could just drop a file into, and immediately see the structure visualized — so I built Parquetastic, a browser-based visual Parquet metadata inspector tool.

What it does:

- Visualizes the full Parquet file structure: row groups, column chunks, pages (if your file has a page index), encodings, compression, statistics

- Shows key specs at a glance without writing any code or queries (e.g., footer size, page index size)

- Runs entirely in the browser — the data never leaves your device

- No download, no installation, no signup

Live demo: https://parquetastic.dev

GitHub: https://github.com/FlorianPfisterer/parquetastic

I'd love your feedback, especially from anyone who regularly works with Parquet files!

Disclaimer: This project was fully built in my free time and has nothing to do with my employer. And before you ask: Yes, this was mostly vibe-coded (or rather "agentically engineered"). Without these tools, I wouldn't have had the time to build it!18:T48e,A friend who's a corporate photographer came to me with an interesting problem: aligning multiple portrait photos for team pages, yearbooks, directories, so that faces are consistently positioned.

Fundamentally, when you take dozens of photos in a day, they are likely to be all slightly different in terms of crop.

As I had done some work with facial feature recognition, my friend asked if the same tech could be used for his problem... and here's why [FaceCrop](http://facecrop.puntofisso.net/) came to be :-)

How does it work:

A fun Python puzzle with circular imports