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.
Speakers: Alexander CS Hendorf