Anyscale Academy

Ray Core Tutorial

Thursday, June 24, 4:00PM UTC

A Guided Tour of Ray Core covers an introductory, hands-on coding tour through the core features of Ray, which provide powerful yet easy-to-use design patterns for implementing distributed systems in Python. This training includes a brief talk to provide overview of concepts, then coding for remote functions, actors, parallel iterators, and so on. Then we'll follow with Q&A. All code is available in notebooks in the GitHub repo.

Intended Audience

  • Python developers who want to learn how to parallelize their application code

Note: this morning material is not intended as an introduction to the higher level components in Ray, such as RLlib and Ray Tune. The afternoon tutorial will cover RLlib and Ray Tune.


  • Some prior experience developing code in Python

  • Basic understanding of distributed systems

Key Takeaways

  • What are the Ray core features and how to use them?

  • In which contexts are the different approaches indicated?

  • Profiling methods, to decide when to make trade-offs (compute cost, memory, I/O, etc.)?


Paco Nathan

Paco Nathan

Evil Mad Scientist, Derwen, Inc.

Known as a "player/coach", with core expertise in data science, natural language, cloud computing; ~40 years tech industry experience, ranging from Bell Labs to early-stage start-ups. Advisor for Amplify Partners, IBM Data Science Community, Recognai, KUNGFU.AI, Primer. Lead committer PyTextRank, kglab. Formerly: Director, Community Evangelism @ Databricks and Apache Spark. Cited in 2015 as one of the Top 30 People in Big Data and Analytics by Innovation Enterprise.