Sunday, 6th October 2019
Streamlit: Turn Python Scripts into Beautiful ML Tools (via) A really interesting new tool / application development framework. Streamlit is designed to help machine learning engineers build usable web frontends for their work. It does this by providing a simple, productive Python environment which lets you declaratively build up a sort-of Notebook style interface for your code. It includes the ability to insert a DataFrame, geospatial map rendering, chart or image into the application with a single Python function call. It’s hard to describe how it works, but the tutorial and demo worked really well for me: “pip install streamlit” and then “streamlit hello” to get a full-featured demo in a browser, then you can run through the tutorial to start building a real interactive application in a few dozen lines of code.
twitter-to-sqlite 0.6, with track and follow. I shipped a new release of my twitter-to-sqlite command-line tool this evening. It now includes experimental features for subscribing to the Twitter streaming API: you can track keywords or follow users and matching Tweets will be written to a SQLite database in real-time as they come in through the API. Since Datasette supports mutable databases now you can run Datasette against the database and run queries against the tweets as they are inserted into the tables.