09-04, 16:30–16:45 (UTC), Track 1 (Mitxelena)
Jupyter notebooks are often a mess. The code produced is working for one notebook, but it's hard to maintain or to re-use. In this talks I will present some best practices to make code more readable, better to maintain and re-usable.
Jupyter notebooks are often a mess. The code produced is working for one notebook, but it's hard to maintain or to re-use.
In this talks I will present some best practices to make code more readable, better to maintain and re-usable.
This will include:
- versioning best practices
- how to use submodules
- coding methods to avoid (e.g. closures)
Jupyter notebooks' code is often a mess. I will present some best practices how to code better in Jupyter.
Python Skill Level –professional
Domain Expertise –some
Domains –General-purpose Python, Jupyter
Alexander' professional career was always about digitalization: starting from vinyl records in the nineties to advanced data analytics nowadays. He's a Python Software Foundation fellow, program chair of Europe's main Python conference EuroPython, PyConDE and the scientific Python conference EuroSciPy. He’s one of the 25 mongoDB masters and a regular contributor to the tech community. As regular speaker at international conferences in he love to talk about, discuss and train tech.
Being a partner at Königsweg - a boutique consultancy based in Mannheim, Germany - he's advising and training industry clients in Ai, data science and big data matters.