Simple ETL in python 3.5+ with Bonobo [EuroPython 2017 - Talk - 2017-07-12 - Arengo] [Rimini, Italy] Simple is better than complex, right? That’s true for data pipelines too. For more than 5 years, I hacked together extract-transform-load (ETL) processes in various different positions (ETL is just a fancy term for «bunch of things that take data somewhere and put it elsewhere, eventually transformed»). I did it as a founder, as a consultant, as a technical co-founder, for some side projects, and now in a big corp (to be continued…). In each case, I felt frustrated with the tools available, and in some serious cases, I had to hack things myself to get the job done. https://www.bonobo-project.org/ Bonobo is the repackaging of my past experiences for python 3.5+, and grasping the basics should not take more than the length of the presentation. Topics outline (subject to small changes) : • INTRO : State of the art / different tools for different needs. • Where does it come from. • Writing a data processor. • Running and monitoring data jobs. • OUTRO : The road ahead. • Q&A Bonobo is the glue you need to tie together regular functions in a transformation graph (think unix pipes). Execution strategies are abstracted so you can focus on the real operations. As a result, you can engineer simple and testable systems, using the same good computer development practices as you use in -insert your favorite field here-. Spoiler : there is no «big data» in this talk