Bytewax: The Next Data Processing Framework Generation in Python

Spoiler Alert = Mind-Blowing Content

Have you ever asked yourself if someone has thought about how to unwrap and simplify stream processing?

Or, would stream processing be available in Python using the best-of-breed libraries and Pythonic code and yet scale horizontally?

If you're about to listen to this episode, this one may not only change your mind but also would drastically change the way you look at Python.

Zander Matheson is a distinguished Python engineer and founder of the Bytewax company, which aims to simplify real-time stream processing using today's lingua franca, Python.

Bytewax is an Open-Source Python framework that simplifies end-to-end data pipeline workflows. It offers a non-JVM approach to abstract and solves complex data problems.

Hence, it's wicked fast and straightforward to use. It also offers a CLI where you can easily deploy the DataFlows.

In this episode, we wade through the following topics:

• Python for Data Engineers and Scientists
• Popularity and Libraries
• Bytewax & Motivators
• Main Capabilities
• Adoption
• Upcoming Features

Zander Matheson = https://www.linkedin.com/in/alexandermatheson/
Bytewax = https://bytewax.io/  

Luan Moreno =
https://www.linkedin.com/in/luanmoreno/

Chapters

• 0:57 Intruduction
• 4:44 Who is Zander Matheson?
• 6:39 The role of data scientist
• 14:10 Why does choosing python for data science and data engineering?
• 18:21 Distributed and parallel processing in python
• 20:11 Main motivators to build Bytewax
• 32:29 Main capabilities of the Bytewax stream processing
• 35:59 How the community can help with Bytewax adoption?
• 39:45 Next Bytewax features
• 48:23 Future python programming language and a relation with Bytewax
• 50:01 Bytewax main goals in the next 2-3 years
• 51:59 How people from community can help the Bytewax?
• 53:00 Kafka realase from Bytewax