Decoupling Systems to Get Closer to the Data

What are the benefits of using a decoupled data processing system? How do you write reusable queries for a variety of backend data platforms? This week on the show, Phillip Cloud, the lead maintainer of Ibis, will discuss this portable Python dataframe library.

Phillip contrasts Ibis’s workflow with other Python dataframe libraries. We discuss how “getting close to the data” speeds things up and conserves memory.

He describes the different approaches Ibis provides for querying data and how to select a specific backend. We discuss ways to get started with the library and how to access example data sets to experiment with the platform.

Phillip discovered Ibis while looking for a tool that allowed him to reuse SQL queries written for a specific data platform on a different one. He recounts how he got involved with the Ibis project, sharing his background in open source and learning how to contribute to a first project.

This episode is sponsored by Mailtrap.

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Topics:

00:00:00 – Introduction

00:02:18 – How did you get started with Ibis?

00:08:10 – First contribution to open source

00:13:46 – Comparing Ibis to other dataframe libraries

00:20:09 – Sponsor: Mailtrap

00:20:43 – What goes into the selection of backend?

00:27:07 – Database connections vs SQL compilers

00:30:03 – Raw SQL approach

00:34:06 – Dataframe approach

00:38:31 – What does “getting close to the data” mean?

00:41:52 – Video Course Spotlight

00:43:24 – Phillip in the cloud - YouTube channel

00:44:56 – Access to sample data sets

00:50:11 – Additional resources

00:52:50 – What are some of the backends Ibis supports?

00:54:13 – Entry points to the platform

00:55:00 – How are you supported?

00:57:10 – Exporting a SQL query

00:59:23 – What are you excited about in the world of Python?

01:04:28 – What do you want to learn next?

01:07:12 – How can people follow your work online?

01:08:00 – Thanks and goodbye

Show Links:

Ibis - the portable Python dataframe library

The Leading Designer and Builder of Enterprise Data Systems - Voltron Data

PEP 249 – Python Database API Specification v2.0

sqlglot: Python SQL Parser and Transpiler - GitHub

Ibis – getting_started

ibis-examples: A repository of runnable examples using ibis

Ibis – Reference Documentation

PyScript - Run Python in your HTML

pixi - Prefix.dev

uv: An extremely fast Python package installer and resolver, written in Rust

PyCon US 2024

LearnCraft Spanish – Fluency for Serious Learners

ibis: the portable Python dataframe library - GitHub

Ibis – Blog Posts

Phillip in the Cloud - YouTube

Phillip Cloud (@cpcloudy) / X

cpcloud (Phillip Cloud) · GitHub

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