2022-09-01 –, HS 120
In this talk, I'll give an overview of software quality and why it's important - especially for scientists. Provide best practices and libraries to dive deeper into, hypes to ignore, and simple guidelines to follow to write code that your peers will love.
After the talk, the audience will have a guide on how to develop better code and be aware of potential blind spots.
In this talk I will provide an overview of best practices for software quality. Practices and libraries to look deeper into included, hypes to be ignored providing simple guidelines to follow for writing code your peers will love.
Jupyter notebooks are often messy, scripted applications like to contain redundant code and like to fail just before the result - wasting precious time. The code works for one-time use, but is difficult to maintain, reuse, or read by colleagues.
In this talk I will present best practices to make code:
- more readable
- better to maintain
- re-usable
Flag potentially bad practices as:
- closures
- using too many third libraries
Practices how to best design applications including:
- refactoring
- versioning
- DRY
- when to write tests
- documentation
Provide an overview of the habitats production-ready code likes to live in like CI/CD pipelines.
After the talk the audience will have a guideline on how to develop better code, and be aware of potential blind spots.
Software quality is important - especially for research! This talk provides an overview of best practices and libraries to dive deeper into, hypes to ignore, and simple guidelines to follow to write code that your peers will love.
Software quality is important - especially for reasearch! This talks provides and overview of best practices and libraries to dive deeper into, hypes to ignore, and simple guidelines to follow to write code that your peers will love.
Domains –General-purpose Python, Jupyter
Expected audience expertise: Domain –none
Expected audience expertise: Python –some
Alexander Hendorf is responsible for data and artificial intelligence at the digital excellence consultancy KÖNIGSWEG GmbH. Through his commitment as a speaker and chair of various international conferences, he is a proven expert in the field of data intelligence. He has many years of experience in the practical application, introduction and communication of data and AI-driven strategies and decision-making processes. He is a Python Software Foundation Fellow, likes to work in small dedicated teams and loves to work with and contribute to the Python and PyData community.