I am a quantitative developer at Cubist Systematic Strategies and an adjunct professor in the Computer Science Department at Columbia University. My background is primarily in application development with a focus on streaming analytics. I have been involved in the formation of several corporate open source efforts, and am a proud member and maintainer of open source projects in the FINOS, JupyterLab, and Conda Forge organizations.
Dataflow graphs have become indispensable tools for data science, from ETL batch processes to live streaming data pipelines. A variety of tools exist for constructing and scheduling graphs, but few generic tools exist for visualizing them, and even fewer let you analyze and interact with them from inside a notebook.
Audience: Jupyter - Novice, familiarity with any graph engine recommended e.g. Apache Airflow, Dask, networkx, etc