2025-04-23 –, Europium2
In our quest to improve Python deployments, we explored Pixi, a tool designed to enhance dependency management within the Conda ecosystem. This talk recounts our experience integrating Pixi into a setup used in production. We leveraged Pixi to create lockfiles, ensuring consistent builds, and to automate deployments via CI/CD pipelines. This integration led to greater reliability and efficiency, minimizing deployment errors and allowing us to concentrate more on development. Join us as we share how Pixi transformed our deployment process and offer insights into optimizing your own workflows.
In modern software development, managing dependencies effectively is crucial for ensuring that applications run smoothly across various environments. This talk explores our journey to optimize Python deployments by integrating Pixi into our workflow. As a tool that enhances the Conda ecosystem, Pixi offers a reliable and efficient solution to the common challenges in dependency management. While concepts such as consistent builds, reproducibility, and automated deployments are well-established, Pixi simplifies their implementation within a Conda-based environment, making these practices more accessible and manageable.
The talk will cover
- DevOps Concept
Introducing concepts like lockfile, reproducible environments and CI/CD pipeline to set out a good
baseline for deploying python code productively
- Conda vs Pypi comparison
Considering the tradeoffs between isolation and development comfort
- Pixi introduction
An introduction to the philosphy of pixi and how it compares to other conda tooling.
This also covers how Pixi streamlines the implementation of DevOps concepts
- Implementing DevOps concepts using pixi
This talk is designed for professional software developers who prioritize a robust setup for deploying Python code as services into production. While familiarity with the Conda ecosystem is beneficial, it is not a prerequisite for this session.
Intermediate
Expected audience expertise: Python:Intermediate
Hey there! I'm Dennis Weyland, and I've been part of the Blue Yonder team for the last five years. I kicked off my career as a Data Scientist but soon found my groove in Data Engineering. Python has been my go-to language for the past seven years, and I love diving into project setups to make everything run smoothly. Before diving into my professional career, I studied Physics at KIT, where I completed my master's thesis and discovered my passion for Python software development and machine learning.
Outside of work I'm passionate about running, diving, and climbing.