Lucia Cerchie has a pair of posts. First up, Lucia sets the stage:
n part 1 of this series, we’ll make an app, hosted on Streamlit, that allows a user to select a stock, in this case SPY, or the SPDR S&P 500 ETF Trust. Upon selection, a live chart of the stock’s bid prices, calculated every five seconds, will appear.
What are the pieces that go into making this work? The source of the data is the Alpaca Market Data API. We’ll hook up a Kafka producer to the websocket stream and send data to a Kafka topic in Confluent Cloud. Then we’ll use Flink SQL within Confluent Cloud’s Flink SQL workspace to tumble an average bid price every five seconds. Finally, we’ll use a Kafka consumer to receive that data and populate it to a Streamlit component in real time. This frontend component will be deployed on Streamlit as well.
In part one of this series, we walked through how to use Streamlit, Apache Kafka®, and Apache Flink® to create a live data-driven user interface for a market data application to select a stock (e.g., SPY) and discussed the structure of the app at a high level. First, data with information on stock bid prices is moved via an Alpaca websocket, then, it’s produced to a Kafka topic in Confluent Cloud where it is also processed with Flink SQL.
Now comes the tricky part: running the Kafka consumer and producer in the same application.
Click through for a good demonstration of a practical solution. Lucia also has a GitHub repo with all of the code, a demo of the site in action, and some links to additional resources.