ipython_memory_usage VS snipp.in

Years back I built IPython Memory Usage[0] which shows how much RAM and time was used per cell in Jupyter Notebooks (and originally the IPython shell). This is very useful for diagnosing why some Pandas and NumPy operations use a lot of RAM [1] which can also point at slow-downs, so you can compare different approaches to find more efficient solutions rather than randomly trying stuff until something no longer breaks.

0: https://github.com/ianozsvald/ipython_memory_usage

1: https://github.com/ianozsvald/ipython_memory_usage/blob/mast...

I built https://snipp.in because I was top frustrated about the loading times of notion. I am a developer and I take notes quite often, most of us spend a lot of time on an IDE and when we need format a quick json or copy a tiny snippet we often find ourselves in opening another instance of an editor with a txt file or random website to formate json. Snipp.in is a tiny jn browser editor, note taking app and a snippet manager all in one which looks like an Editor but really fast without any bs of signin/signups or cloud. It just stores everything in your browser using IndexedDB. It's also open-sourced at https://github.com/haxzie/snipp.in