Faust, your Python-based streaming library

Robinhood is a very popular California based FinTech, included by Forbes in the top 50 FinTechs to watch in 2019. Their primary mission is to bring down stock trading fees for the common Joe/Jane, although their roadmap also includes cryptocurrency trading.

Due to the nature of the bidding market, their data stack probably includes a lot of stream tooling. Also (probably) due to the lack of quick and easy tooling for streaming with Python, supported with the growing demand for Python in the developer community, they launched their own port of Kafka Streams, called Faust.

In this post, we’re going to show how to easy it is to bootstrap a project with Faust to put your stream related business logic needs in practice very quickly. The demo we prepared is of an app which filters words from a Kafka topic and then keeps a count of how many times it has seen the colors “red”, “green” and “blue”.

In a nutshell, Faust is:

Continue reading “Faust, your Python-based streaming library”

Using Akka Streaming for “saving alerts” – part 2

This blog post is the second and final part of the post Using akka streaming for “saving alerts”. Part 1 is available here.  In this part we enter the details on how the application was designed.

Full disclosure: this post was initially published at Bonial tech blog here. If you are looking for positions in tech, I would definitely recommend checking their career page.

Application Actor System

The following illustration gives you a schematic view of all the actors used in our application, and (hopefully) some of the mechanics of their interaction:

akka-streaming-pipeline

As previously mentioned, one could divide the application lifecycle logically into three main stages. We will get into more detail about each one of them next, but for now let us walk through them narrowly and try to map to our application Continue reading “Using Akka Streaming for “saving alerts” – part 2″