In this talk, I will share my journey with Python, spanning over 20 years, and how it has become an integral part of our work at E.ON. My experience with open source began over 30 years ago during my research as a Theoretical Particle Physicist, where sharing insights and code was a daily practice. Transitioning to a software developer role at a start-up, I initially used Perl for various tasks but soon realized the challenges of code readability and collaboration. Python, with its enforced indentation and readability, quickly became my language of choice.

At E.ON, Python is our go-to language for Data Science tasks. In our team we recently migrated another programming language codebase to Python to streamline our development framework and attract top talent. Python's straightforward modularization into packages and modules simplifies maintenance and lineage, especially in cloud-based pipelines, and helps prevent vendor lock-in. The robust toolchain for code quality checks, testing, and building packages makes Python a no-brainer for development and supports our MLOps principles.

I will discuss how Python facilitates collaboration globally at E.ON and share examples of our MLOps principles in action. Highlights include image analysis projects like object detection with batch inferencing and instance segmentation with real-time inference endpoints. Additionally, I will detail E.ON's steps towards open-sourcing some of our codebases, enabling other energy companies to build on our projects.

Join me to explore why Python is not just a tool but a catalyst for innovation and collaboration at E.ON.