tl;dr we’re releasing python bindings for writing stream processing jobs using the Denormalized Rust library.<p>Hey HN,<p>A few months ago we released Denormalized, our embeddable stream processing engine written in rust [0]. Today we’re excited to showcase python bindings for the library.<p>Python is still very much the language of data and we wanted to make it easy for more engineers to write fast streaming jobs without having to learn Rust.<p>Currently, you can use the library to write streaming aggregations, stream joins, and user defined aggregate functions (thought the API for this is quite clunk).<p>The library is available on pypi: `pip install denormalized` and we’ve created a simple docker container that will quickly spin up an instance of kafka along with a script to write fake data to make running the examples [1] really easy: `docker run --rm -p 9092:9092 emgeee/kafka_emit_measurements:latest`<p>We’d love to hear your feedback<p>[0] <a href="https://news.ycombinator.com/item?id=41258276">https://news.ycombinator.com/item?id=41258276</a>
[1] <a href="https://github.com/probably-nothing-labs/denormalized/tree/main/py-denormalized/python/examples">https://github.com/probably-nothing-labs/denormalized/tree/m...</a>
Looks great! I remember seeing your post from a few months ago and I tried out <a href="https://github.com/finos/perspective">https://github.com/finos/perspective</a> but it wasn't for me. Will be giving this a try later this week!