In this talk, I will be sharing about Ibis, a software package that provides a more Pythonic way of interacting with multiple database engines. In my own adventures living in Zimbabwe, I’ve always encountered ibises (the bird versions) perched on top of elephants. If you’ve never seen an elephant in real life I can confirm that they are huge, complex creatures. The image of a small bird sitting on top of a large elephant serves as a metaphor for how ibis (the package) provides a less complex, more performant way for Pythonistas to interact with multiple big data engines.

I'll use the metaphor of elephants and ibises to show how this package can make a data workflow more Pythonic. The Zen of Python lets us know that simple is better than complex. The bigger and more complex your data, the more of an argument there is to use Ibis. Raw SQL can be quite difficult to maintain when your queries are very complex. For Python programmers, Ibis offers a way to write SQL in Python that allows for unit-testing, composability, and abstraction over specific query engines (e.g.BigQuery)! You can carry out joins, filters, and other operations on your data in a familiar, Pandas-like syntax. Overall, using Ibis simplifies your workflows, makes you more productive, and keeps your code readable.

Come meet some of the folks working on Diversity and Inclusion in the global Python Community!
Join the live panel discussion to hear about the challenges and the work they do.

With Marlene Mhangami, Nabanita Roy, Iqbal Abdullah, Tereza Iofciu. Chaired by Naomi Ceder.