Karlsruhe Python Meetup at Blue Yonder
Python Meetup with two talks about python usage in a data science environment and the different stages of a python package in this environment.
For the third time, we hosted the Karlsruhe Python Meetup at Blue Yonder. Both presenters are part of my data engineering team.
A Blue Yonder Python Habitat by Bjoern Meier
This talk was about how Blue Yonder has set itself up as a Python software company. In particular, Bjoern showed how we make our applications available for execution. Questions like
- How do open source packages find their way into the company?
- How do we address the risks of open source usage?
- How do we distribute our internal packages?
were answered in this talk.
Blue Yonder has an application execution model similar to what Azure and others offer, but it is tailored more to Python and data science applications.
Development Stages of Internal Python Packages by Jakob Herpel
After learning in the first part how Blue Yonder distributes internal packages, Jakob delved into the path that written code takes to become a usable Python package. He showed how his team handles cross-cutting issues like
- code style
- testing
- vulnerability scanning
uniformly across artifacts with the help of pytest, Jenkins, Sentry, Black, Flake8, and pip-tools.